Interventions for improving medication‐taking ability and adherence in older adults prescribed multiple medications

Abstract

Background

Older people taking multiple medications represent a large and growing proportion of the population. Managing multiple medications can be challenging, and this is especially the case for older people, who have higher rates of comorbidity and physical and cognitive impairment than younger adults. Good medication‐taking ability and medication adherence are necessary to ensure safe and effective use of medications.

Objectives

To evaluate the effectiveness of interventions designed to improve medication‐taking ability and/or medication adherence in older community‐dwelling adults prescribed multiple long‐term medications.

Search methods

We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO, CINAHL Plus, and International Pharmaceutical Abstracts from inception until June 2019. We also searched grey literature, online trial registries, and reference lists of included studies.

Selection criteria

We included randomised controlled trials (RCTs), quasi‐RCTs, and cluster‐RCTs. Eligible studies tested interventions aimed at improving medication‐taking ability and/or medication adherence among people aged ≥ 65 years (or of mean/median age > 65 years), living in the community or being discharged from hospital back into the community, and taking four or more regular prescription medications (or with group mean/median of more than four medications). Interventions targeting carers of older people who met these criteria were also included.

Data collection and analysis

Two review authors independently reviewed abstracts and full texts of eligible studies, extracted data, and assessed risk of bias of included studies. We conducted meta‐analyses when possible and used a random‐effects model to yield summary estimates of effect, risk ratios (RRs) for dichotomous outcomes, and mean differences (MDs) or standardised mean differences (SMDs) for continuous outcomes, along with 95% confidence intervals (CIs). Narrative synthesis was performed when meta‐analysis was not possible. We assessed overall certainty of evidence for each outcome using Grades of Recommendation, Assessment, Development and Evaluation (GRADE). Primary outcomes were medication‐taking ability and medication adherence. Secondary outcomes included health‐related quality of life (HRQoL), emergency department (ED)/hospital admissions, and mortality.

Main results

We identified 50 studies (14,269 participants) comprising 40 RCTs, six cluster‐RCTs, and four quasi‐RCTs. All included studies evaluated interventions versus usual care; six studies also reported a comparison between two interventions as part of a three‐arm RCT design.

Interventions were grouped on the basis of their educational and/or behavioural components: 14 involved educational components only, 7 used behavioural strategies only, and 29 provided mixed educational and behavioural interventions. Overall, our confidence in results regarding the effectiveness of interventions was low to very low due to a high degree of heterogeneity of included studies and high or unclear risk of bias across multiple domains in most studies.

Five studies evaluated interventions for improving medication‐taking ability, and 48 evaluated interventions for improving medication adherence (three studies evaluated both outcomes).

No studies involved educational or behavioural interventions alone for improving medication‐taking ability. Low‐quality evidence from five studies, each using a different measure of medication‐taking ability, meant that we were unable to determine the effects of mixed interventions on medication‐taking ability.

Low‐quality evidence suggests that behavioural only interventions (RR 1.22, 95% CI 1.07 to 1.38; 4 studies) and mixed interventions (RR 1.22, 95% CI 1.08 to 1.37; 12 studies) may increase the proportions of people who are adherent compared with usual care. We could not include in the meta‐analysis results from two studies involving mixed interventions: one had a positive effect on adherence, and the other had little or no effect. Very low‐quality evidence means that we are uncertain of the effects of educational only interventions (5 studies) on the proportions of people who are adherent.

Low‐quality evidence suggests that educational only interventions (SMD 0.16, 95% CI ‐0.12 to 0.43; 5 studies) and mixed interventions (SMD 0.47, 95% CI ‐0.08 to 1.02; 7 studies) may have little or no impact on medication adherence assessed through continuous measures of adherence. We excluded 10 studies (4 educational only and 6 mixed interventions) from the meta‐analysis including four studies with unclear or no available results. Very low‐quality evidence means that we are uncertain of the effects of behavioural only interventions (3 studies) on medication adherence when assessed through continuous outcomes.

Low‐quality evidence suggests that mixed interventions may reduce the number of ED/hospital admissions (RR 0.67, 95% CI 0.50 to 0.90; 11 studies) compared with usual care, although results from six further studies that we were unable to include in meta‐analyses indicate that the intervention may have a smaller, or even no, effect on these outcomes. Similarly, low‐quality evidence suggests that mixed interventions may lead to little or no change in HRQoL (7 studies), and very low‐quality evidence means that we are uncertain of the effects on mortality (RR 0.93, 95% CI 0.67 to 1.30; 7 studies).

Moderate‐quality evidence shows that educational interventions alone probably have little or no effect on HRQoL (6 studies) or on ED/hospital admissions (4 studies) when compared with usual care. Very low‐quality evidence means that we are uncertain of the effects of behavioural interventions on HRQoL (1 study) or on ED/hospital admissions (2 studies). We identified no studies evaluating effects of educational or behavioural interventions alone on mortality.

Six studies reported a comparison between two interventions; however due to the limited number of studies assessing the same types of interventions and comparisons, we are unable to draw firm conclusions for any outcomes.

Authors' conclusions

Behavioural only or mixed educational and behavioural interventions may improve the proportion of people who satisfactorily adhere to their prescribed medications, but we are uncertain of the effects of educational only interventions. No type of intervention was found to improve adherence when it was measured as a continuous variable, with educational only and mixed interventions having little or no impact and evidence of insufficient quality to determine the effects of behavioural only interventions. We were unable to determine the impact of interventions on medication‐taking ability. The quality of evidence for these findings is low due to heterogeneity and methodological limitations of studies included in the review. Further well‐designed RCTs are needed to investigate the effects of interventions for improving medication‐taking ability and medication adherence in older adults prescribed multiple medications.

Plain language summary

Interventions for helping older adults prescribed multiple medications to use and take their medications

Background: Older people are often prescribed multiple medications, which can be challenging to manage. Medication‐taking errors and non‐adherence (under‐use or over‐use of medication) can lead to negative health outcomes. Assisting older people to better use and adhere to their medications could reduce adverse medication events, such as medication‐related hospital admissions, and could improve health outcomes.

Question: What are the findings of studies testing ways to improve older people's ability to use and adhere to multiple medications?

Search strategy: To find relevant studies, we searched seven online databases, trial registries, and the reference lists of previous reviews, retrieving studies published until June 2019.

Selection criteria: We included randomised controlled trials (RCT) or studies of similar design comparing a group of people receiving an intervention to improve medication‐taking ability or medication adherence with a group receiving usual care (no intervention) or receiving a different intervention. We included trials that studied older adults (≥ 65 years) living at home (or being discharged from hospital back to home) who were using four or more regular prescription medications.

Main results: We identified 50 studies, involving 14,269 participants. All studies tested interventions versus usual care, with six studies also comparing two different types of interventions.

Fourteen studies tested educational interventions whereby people received education regarding their medications or a health professional reviewed their medications. Seven studies tested behavioural interventions such as changing dosing times, re‐packaging medications into multi‐compartment pill boxes to make medication regimens easier to take, or sending text message adherence reminders. Twenty‐nine studies tested mixed educational and behavioural interventions.

The studies identified were very different in terms of what interventions people received, where interventions were delivered, and how and when people's medication‐taking ability or adherence was measured. Due to these differences and problems with how the trials were conducted, the quality of the evidence was considered low or very low overall.

Low‐quality evidence means that the impact of mixed interventions on medication‐taking ability could not be determined, and no studies were identified that assessed educational only or behavioural only interventions for improving medication‐taking ability.

Low‐quality evidence suggests that compared with usual care, behavioural only and mixed interventions may improve the proportions of people who satisfactorily adhere to their prescribed medication, but very low‐quality evidence means that the effects of educational only interventions are uncertain. Low‐ and very low‐quality evidence means that no interventions were found to be effective in improving medication adherence when assessed by continuous measures such as percentage of medications consumed.

Low‐quality evidence also suggests that mixed interventions may reduce the number of emergency department visits or hospital admissions, and may lead to little or no change in health‐related quality of life (HRQoL). Moderate‐quality evidence shows that educational interventions alone probably have little or no effect on HRQoL or on emergency department or hospital admissions. The effects of behavioural interventions alone on HRQoL or emergency department or hospital admissions are uncertain because of very low‐quality evidence. We are uncertain of the effects of behavioural, educational, or mixed interventions on mortality.

Studies comparing one type of intervention with another were limited in number, and we are unable to draw firm conclusions for any key outcomes.

Authors' conclusions: Interventions varied greatly among studies, and there were problems regarding how the trials were conducted, which may have affected their results. We were unable to determine the impact of interventions on medication‐taking ability. Low‐quality evidence suggests that behavioural only and mixed educational and behavioural interventions may improve the proportions of people who adhere to their prescribed medication regimen. Low‐ and very low‐quality evidence found no type of intervention to be effective in improving medication adherence when this was assessed by a continuous measure. High‐quality studies are necessary to identify the most effective way to improve medication‐taking ability and medication adherence among older adults prescribed multiple medications.

Background

Description of the condition

Older people, conventionally defined as those aged 65 years and older, often have multiple chronic health problems that require ongoing healthcare interventions (Hilmer 2007; WHO 2000). Increasing multi‐morbidity and an expanding evidence base supporting multi‐drug regimens in the management of many chronic diseases mean that polypharmacy (use of multiple medications) is often unavoidable in older people. Polypharmacy has a range of definitions but is commonly defined as the use of four or more medications (Department of Health (UK) 2001; Patterson 2014). The prevalence of polypharmacy is increasing. For example, in the United Kingdom, the number of adults aged over 65 years and taking five or more medications daily has quadrupled from 12% to 49% over the past two decades (Gao 2017). There is also a substantial subgroup of the older population who are prescribed an average of 10 or more different medications, which is sometimes referred to as hyperpolypharmacy (Elliott 2014).

Medication‐taking ability refers to a person’s ability to accurately follow a prescribed medication regimen. It includes knowing what medications to take and when to take them and being able to correctly administer the medication (Maddigan 2003). Managing multiple long‐term medications can be a complex and challenging task, especially for older people, who may experience a decline in the cognitive and physical abilities required for taking medication (Barbas 2001; Beckman 2005). More than a quarter of older people experience difficulties when opening medication packages, including opening bottles and removing medication from blister packs (Philbert 2014). Older people with visual impairment are more than twice as likely to require help in managing their medication as those without visual impairment (McCann 2012). Many older people receive assistance from informal or non‐professional carers when taking medication (ACSQHC 2012). Thus, interventions that aim to improve medication‐taking ability in older adults may need to target carers as well as consumers.

Medication adherence refers to the extent to which a person’s medication‐taking behaviour corresponds with agreed upon treatment recommendations from a healthcare provider (WHO 2003). Non‐adherence refers to deviations from that agreed upon treatment and includes under‐utilisation, over‐utilisation, and incorrect use of medication. There are two broad types of non‐adherence: unintentional non‐adherence – which may be due to factors such as forgetfulness, lack of understanding, physical problems, or the complexity of the regimen; and intentional non‐adherence – which occurs when a person decides not to take his or her treatment as instructed (Wroe 2002). A person is generally considered adherent if he or she takes between 80% and 120% of prescribed medication over a given time period (WHO 2003). Non‐adherence to medications has been reported in up to 50% of older people in different countries and settings (George 2006; Gilbert 1993;Gray 2001; Hemminki 1975;Lau 1996; Lee 2010; Mansur 2008; McElnay 1997;Okuno 1999;Sewitch 2008; Spagnoli 1989;Stoehr 2008; Thorpe 2009; Vik 2006). The World Health Organization (WHO) has recognised the importance of enhancing adherence as a strategy to tackle chronic health conditions effectively (WHO 2003).

Consequences of poor medication‐taking ability and of non‐adherence may include suboptimal response to treatment, recurrence of illness, adverse drug events (ADEs), increased healthcare service utilisation, unplanned hospitalisations, increased morbidity and mortality, and increased healthcare costs (Balkrishnan 2003; Col 1990;DiMatteo 2002;Howard 2003; Leendertse 2008; Tafreshi 1999). Among older adults, ADEs are a significant and increasing problem (Burgess 2005;Elliott 2014). Almost a quarter of preventable ADEs in older people are attributable to consumer error (Field 2007; Gurwitz 2003). Between US$100 and US$300 billion of avoidable healthcare costs has been attributed to non‐adherence in the United States annually (IMS 2013).

Medication‐taking ability and adherence are influenced by a range of factors related to healthcare consumers, their therapies, their medical conditions, social factors, and healthcare provider‐, and health system‐related factors (Balkrishnan 1998; Jin 2008; WHO 2003). Medication‐taking ability and adherence can be inter‐related. For example non‐adherence may result from a patient being unable to follow instructions or remove medications from packaging. Age itself is generally not an independent predictor of poor medication‐taking ability nor of non‐adherence (DiMatteo 2004; Vik 2004). Nevertheless, the prevalence of risk factors for medication use problems increases with age (Col 1990). These include polypharmacy (Gray 2001;Vik 2006), medication regimen complexity (Corsonello 2009; Jansa 2010; Vik 2006), cognitive and functional decline (Gray 2001; Hutchison 2006; Spiers 1995;Vik 2006), inadequate contact with health professionals (George 2006), depressive symptoms (Vik 2006), poor social support (DiMatteo 2000; Spiers 1995), and absence of assistance with administration of medications (Vik 2006). The risk factors for suboptimal use of medications by older people have been studied extensively in cross‐sectional studies (George 2006; Gilbert 1993; Gray 2001; Hemminki 1975; Jerant 2011; Lau 1996; McElnay 1997; Okuno 1999; Sears 2012; Spagnoli 1989; Tavares 2013; Vik 2006). Many adverse health outcomes may be preventable if appropriate measures are taken to address these risk factors and to optimise medication‐taking ability and adherence (George 2008; Jokanovic 2016; Sorensen 2004).

Description of the intervention

A range of simple to complex behavioural and educational interventions, given alone or in combination, have been tested for improving the medication‐taking ability and adherence of consumers (George 2008). Behavioural strategies include:

• alarm/beeper;

• calendar/diary;

• reminder chart/medication list;

• large print labels;

• packaging change;

• multi‐compartment pillbox/calendar pack/compliance aid (also known as dose administration aid (DAA));

• contracting (verbal or written agreement);

• adherence monitoring with or without feedback;

• reminders (mail, telephone, email);

• inpatient programs of self‐administration of medications;

• simplification of medication regimens;

• skill building (supervised, group);

• tailoring (routinisation); and

• follow‐up (home visit, scheduled clinic visit, video/teleconferencing).

Educational strategies comprise group (inpatient, family, and support group) and/or individual (verbal, audiovisual, visual, written, telephone, mail) education provided by physicians, pharmacists, nurses, allied health professionals, and others.

How the intervention might work

Behavioural and educational interventions, used alone or in combination, are intended to improve the ability of older people (and/or the ability of their carers) to manage medications and adhere to medication regimens. Interventions may target medication‐taking ability, medication adherence, or both.

These interventions may also lead to improvements in knowledge about medications and in confidence regarding medication management; greater satisfaction with treatment; better health‐related quality of life (HRQoL); reductions in the incidence of ADEs; and reductions in health service utilisation.

Why it is important to do this review

Older people taking multiple medications represent a large and growing proportion of consumers seen by health professionals in clinical practice. They are also the group most likely to experience ADEs. Evidence from well‐designed studies testing interventions to improve medication‐taking ability and adherence among older people prescribed multiple long‐term medications could provide valuable information for practitioners, researchers, and consumers to help optimise medication use among older people living in the community.

Interventions to improve medication adherence have been widely investigated (Nieuwlaat 2014; Ryan 2014). However previous reviews of interventions focusing on medication adherence in older people taking multiple medications are more than 10 years old (George 2008), or they have identified few studies for inclusion (Patton 2017; Zelko 2016). Older people form a heterogeneous population in terms of their medication consumption and disease patterns; therefore studies recruiting relatively homogenous samples of people experiencing one specific disease or consuming one type of medication have limited generalisability.

To date, no systematic review has included measures of medication‐taking other than adherence, such as ability to manage medications. Standardised methods for measuring the ability of people to manage medications have been developed (Elliott 2009; Elliott 2015), some of which have been used in studies of medication use in older people (Lam 2011). Two of the best‐studied assessment tools for evaluating medication‐taking are the Drug Regimen Unassisted Grading Scale (DRUGS) (Edelberg 1999), which utilises a person’s own medications, and the Medication Management Ability Assessment (MMAA) (Patterson 2002), which uses a simulated medication regimen.

Our review will focus on interventions to improve medication‐taking ability or adherence, or both, in older adults who are prescribed multiple medications, or their carers (who are not health professionals).

This review will complement previous Cochrane reviews looking at interventions for improving medication adherence in the general population (Nieuwlaat 2014), including the impact of dose reminder packaging (Mahtani 2011), and interventions for improving clinical outcomes in people with multi‐morbidities (Smith 2016). The appropriateness of people's medication regimens is dependent on a number of factors and will not be considered as part of this review, but only their ability to take (or use) the medications and their adherence to the agreed regimen. There has been a previous Cochrane review of interventions targeted at health professionals, designed to improve the appropriateness of prescribing and polypharmacy (Patterson 2014).

Objectives

To evaluate the effectiveness of interventions designed to improve medication‐taking ability and/or medication adherence in older community‐dwelling people (or their carers) whose treatment consists of multiple long‐term prescribed medications.

Methods

Criteria for considering studies for this review

Types of studies

We included randomised controlled trials (RCTs), cluster‐RCTs, and quasi‐RCTs, as specified by the Cochrane Consumers and Communication Group (CCCRG 2014).

Types of participants

We included studies in which:

• most participants (≥ 80%) were aged 65 years and over, or the mean/median age was over 65 years. Studies were identified that did not meet these criteria but had relevant data regarding older people that could be extracted separately; these were also included;

• participants were living in the community or were discharged from a hospital or other healthcare facility to the community (living in the community includes in a person’s own home or retirement village/independent living unit, with or without additional support; it does not include situations in which professional carers or nurses administer the person's medications, such as in nursing homes, residential care facilities or full nursing care in the home); and

• participants used at least four long‐term regular prescription medications, or the group mean/median was greater than four (irrespective of participants’ number of medical conditions).

Studies that involved carers of consumers who met these criteria were also included. Carers were defined as “people who provide unpaid care and support to family members and friends who have disability, mental illness, a chronic condition, terminal illness, or general frailty” (ACSQHC 2012).

Types of interventions

We included studies that tested single interventions or combinations of interventions directed at the consumer or the carer that sought to improve medication‐taking ability and/or adherence by the consumer.

Examples included:

• support for behaviour change;

• provision of medication aids (e.g. DAAs, medication lists);

• medication regimen simplification;

• remote monitoring of medication use with or without feedback;

• facilitation of communication and decision‐making about medications;

• provision of information or education; and

• acquisition of skills and competencies.

This list of interventions is not exhaustive. Therefore the search strategy (see Appendix 1) also focused on terms that described the outcomes of interest to avoid missing potentially relevant studies that tested novel interventions.

We included the following comparisons.

• Interventions to improve medication‐taking ability and/or adherence versus standard or usual care.

• One form of intervention to improve medication‐taking ability and/or adherence versus another − including simple versus complex interventions.

In future updates, we will consider including interventions to improve medication‐taking ability and/or adherence versus no intervention, but for this review, we identified no studies of this nature.

Types of outcome measures

Primary outcomes

This review focused on two outcomes directly related to medication‐taking behaviour of older adults (or their carers): ability to manage medications and adherence to medication regimens. To be eligible for inclusion, studies had to have assessed at least one of these outcome measures for at least four regular prescribed medications (which could be the person’s own medications or, for assessment of ability to manage medication, a validated, simulated medication regimen instrument) (Elliott 2009). These two outcomes were evaluated separately.

Ability to manage medications

This outcome assessed participants' (or carers') ability to manage medications using objective and/or subjective measures.

• Objective measures: direct observation using standardised assessment instruments/methods (e.g. Drug Regimen Unassisted Grading Scale (DRUGS), Medication Management Ability Assessment (MMAA), device technique checklists (Elliott 2006; Elliott 2009; Patterson 2002)).

• Subjective measures: self‐reported ability or self‐efficacy (e.g. Self‐Efficacy for Appropriate Medication Use Scale (SEAMS)) (Risser 2007).

Adherence to medication regimens

This outcome assessed consumer adherence to prescribed medication regimens, using objective and/or subjective measures.

• Objective measures: refill data, pharmaceutical claims data, electronic monitoring, biological assay, measure of used/unused medications (e.g. pill count).

• Subjective measures: self‐report of missed/used doses, validated questionnaires (e.g. Morisky scale (Morisky 1986)).

If an included study measured adherence and/or ability by using more than one type of outcome measure, review authors extracted the most reliable measure (i.e. objective measures were preferentially reported over subjective measures).

Secondary outcomes

We analysed the following secondary outcomes from studies that also measured at least one of the primary outcomes listed above.

• Consumer (or carer) knowledge about their medications.

• Consumer (or carer) satisfaction with the intervention.

• Health‐related quality of life (HRQoL).

• Adverse clinical health outcomes (e.g. unplanned hospital or emergency department presentations, general practitioner visits, ADEs).

• Condition‐specific outcomes (e.g. cardiovascular events, blood pressure, blood glucose levels, lung function).

• Cost‐effectiveness of the intervention.

Timing of outcome assessment

For adherence outcomes, the minimum duration of follow‐up was four weeks. For medication‐taking ability outcomes, a follow‐up period of at least 48 hours after the intervention was required.

If an included study measured adherence and/or ability more than once, we extracted the outcome measure with the longest follow‐up.

Search methods for identification of studies

Electronic searches

We searched the following electronic databases in June 2019, using search strategies tailored to each database.

• Cochrane Central Register of Controlled Trials (CENTRAL), in the Cochrane Library (to 2019).

• MEDLINE (OvidSP) (1966 to 2019).

• Embase (OvidSP) (1973 to 2019).

• PsycINFO (OvidSP) (1967 to 2019).

• Cumulative Index to Nursing and Allied Health Literature (CINAHL) Plus (EBSCOhost) (1981 to 2019).

• International Pharmaceutical Abstracts (IPA) (ProQuest) (1971 to 2019).

The search strategies are presented in Appendix 1.

We applied no language restrictions (provided title and abstract were in English).

Searching other resources

We searched grey literature and online trial registries in November 2017.

For grey literature, we searched:

• Joanna Briggs Institute Evidence Based Practice Database; and

• conference proceedings (Scopus).

We checked the reference lists of included studies and of previously published relevant systematic reviews to locate potentially eligible studies that were not identified via electronic searches.

We also searched the following online trial registries for ongoing and recently completed studies.

• World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP).

• ClinicalTrials.gov.

• ClinicalTrials.com.

• TrialsCentral.

• Australian New Zealand Clinical Trials Registry (ANZCTR).

• United Kingdom Clinical Research Network (UKCRN).

• Networked Digital Library of Theses and Dissertations (NDLTD).

• International Standard Randomised Controlled Trial Number (ISRCTN) registry.

Non‐English language studies were translated and included if they met the eligibility criteria. Studies that were translated are noted in the Characteristics of included studies tables.

Data collection and analysis

Selection of studies

Two review authors (AC and KP, LK, or JG) independently screened abstracts and retrieved the full text of any papers identified as potentially relevant by at least one review author. Two review authors independently screened full‐text articles for inclusion or exclusion (AC and RE, KP, LK, or JG), with discrepancies resolved by discussion and by consulting a third review author if necessary to reach consensus (RE or JG). Review authors were not responsible for screening studies in which they were involved or that they were associated with. We listed as excluded studies all potentially relevant papers excluded from the review and provided reasons in the Characteristics of excluded studies table. We also provided citation details and any available information about ongoing studies, and we collated and reported details of duplicate publications, so that each study (rather than each report or manuscript) was the unit of interest in the review. We reported the screening and selection process in an adapted PRISMA flow chart (Liberati 2009).

Data extraction and management

Two review authors extracted data independently from included studies (AC and, RE, KP, LK, or JG). We resolved any discrepancies by discussion until consensus was reached, or through consultation with a third review author when necessary (RE or JG). We developed and piloted a data extraction form using the Cochrane Consumers and Communication Review Group Data Extraction Template (cccrg.cochrane.org/author-resources). Data extracted included the following study details: aim of the intervention, study design, study population, intervention details, control/comparison group(s), outcome(s), and follow‐up period(s). One review author (AC) entered all extracted data into Review Manager version 5.3 (RevMan 2014), and an independent person checked these data for accuracy against the data extraction sheets.

Assessment of risk of bias in included studies

We assessed and reported on the methodological risks of bias of included studies in accordance with the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011), and according to Cochrane Consumers and Communication Group guidelines (CCCRG 2014), which recommend explicit reporting of the following individual elements for RCTs: random sequence generation; allocation sequence concealment; blinding (participants, personnel); blinding (outcome assessment); completeness of outcome data; selective outcome reporting; and other sources of bias. Other sources of bias included concerns related to sample size, fidelity, potential conflict of interest (e.g. influence of funding bodies), changes to methods (e.g. trial being ceased early), or trial results not published in a peer‐reviewed journal (e.g. thesis). We considered blinding separately for different outcomes when appropriate (e.g. blinding may have the potential to differently affect subjective versus objective outcome measures). We judged each item as being at high, low, or unclear risk of bias, as set out in the criteria provided by Higgins 2011, and we provided a quote or information from the study report and a justification for our judgement for each item in the "Risk of bias" table.

We deemed studies to be at highest risk of bias if they were scored at high or unclear risk of bias for the sequence generation or the allocation concealment domain, based on growing empirical evidence that these factors are particularly important potential sources of bias (Higgins 2011).

We assessed and reported quasi‐RCTs as being at high risk of bias on the random sequence generation item of the "Risk of bias" tool. For cluster‐RCTs, we also assessed and reported risk of bias associated with another domain: selective recruitment of cluster participants.

In all cases, two review authors independently assessed the risk of bias of included studies, with disagreements resolved by discussion to reach consensus. We contacted study authors for additional information about the included studies, or for clarification of study methods as required. We incorporated results of the "Risk of bias" assessment into the review through standard tables and systematic narrative description and commentary about each of the elements, leading to an overall assessment of the risk of bias of included studies and a judgement about the internal validity of review results.

Measures of treatment effect

We considered the primary outcomes as dichotomous variables when possible, that is, the person (or the carer) was assessed as able to manage medications or not, and similarly to have satisfactory adherence (80% to 120%) or not (< 80% or > 120%). If a study did not report its outcome as dichotomous, we extracted and analysed continuous outcomes.

For dichotomous outcomes, we analysed data based on the number of events and the number of people assessed in the intervention and comparison groups. We used these data to calculate the risk ratio (RR) and the 95% confidence interval (CI). Given heterogeneity in study measures, we analysed data for continuous measures using the standardised mean difference (SMD) and 95% CI approach via the inverse variance method in Review Manager 5.

Unit of analysis issues

For included cluster‐RCTs, we checked for unit of analysis errors. If errors were found, and if sufficient information was available, we re‐analysed data using the appropriate unit of analysis by taking into account the intracluster correlation coefficient (ICC). We obtained estimates of the ICC by contacting authors of included studies. When this was not possible, we reported effect estimates and annotated "unit of analysis errors." For future updates, we may impute missing ICCs using estimates from external sources, but this was not required for any of the trials included in this review.

Of the six cluster‐RCTs, three reported ICCs but did not report effective sample sizes. We recalculated effective sample sizes based on information reported in each study and divided the reported sample size by the design effect (Higgins 2011). We reported the adjusted sample sizes in meta‐analyses and reduced the weightings given to these studies.

Muth 2016 reported an ICC of 0.00; thus no adjustment was required.

Moral 2015 reported an ICC of 0.05 and had an average cluster size of 5.4 for intervention and 6.0 for control. There were 70 participants in the intervention group and 84 participants in the control group, which we adjusted to 57 for intervention and 67 for control for all outcomes.

Willeboordse 2017 reported an ICC of 0.08 but was not included in any meta‐analyses due to alternate reporting methods; thus effective sample sizes were not calculated.

For the three studies that did not report an ICC (Bernsten 2001;Volume 2001; Wood 1992), we contacted study authors for further information. As we received no response, we could make no adjustments. We conducted sensitivity analyses while excluding these studies to adjust for possible unit of analysis errors.

Dealing with missing data

We attempted to contact study authors to obtain missing data (participant, outcome, or summary data). When possible, we conducted analyses of participant data on an intention‐to‐treat (ITT) basis; otherwise we analysed data as reported. We reported on levels of loss to follow‐up and assessed this as a potential source of bias.

For missing outcome or summary data, we planned to impute missing data when possible and to report any assumptions, but this was not required or possible for any included studies.

We conducted sensitivity analyses that excluded studies presenting data with loss to follow‐up greater than 20% for the primary outcomes (medication‐taking ability and/or medication adherence) including total reported lost to follow‐up and differential loss to follow‐up between groups. This was due to potential serious threats to validity associated with high proportions of participants lost to follow‐up (Sackett 2000).

Assessment of heterogeneity

We identified substantial variations in types of interventions, populations studied, and study designs and settings. When studies were considered similar enough to enable data pooling via meta‐analysis, we assessed the degree of heterogeneity by visually inspecting forest plots and examining the Chi² test for heterogeneity. We quantified heterogeneity by using the I² statistic. We considered an I² value of 50% or more to represent substantial levels of heterogeneity, but we interpreted this value in light of the size and direction of effects and the strength of evidence for heterogeneity, based on the P value from the Chi² test (Higgins 2011). When heterogeneity was present in pooled effect estimates, we explored possible reasons for variability by conducting subgroup analyses.

When we detected substantial heterogeneity, particularly in relation to types of outcome measures or methods of reporting outcome measures, we did not report pooled results from meta‐analysis but instead used a narrative approach to data synthesis.

Assessment of reporting biases

We assessed reporting bias qualitatively based on the characteristics of included studies (e.g. if only small studies with positive findings were identified for inclusion), and based on information obtained by contacting authors of studies which suggested there might have been relevant unpublished data or studies.

We did not construct funnel plots to investigate publication bias because we found insufficient studies per outcome and intervention type and because multiple studies were not suitable for inclusion in meta‐analyses.

For future updates, if we should identify sufficient studies (at least 10) for inclusion in the review, we will construct a funnel plot to investigate small‐study effects and to formally test for funnel plot asymmetry, with test selection based on advice provided in Higgins 2011, while bearing in mind there may be several reasons for funnel plot asymmetry when results are interpreted.

Data synthesis

We conducted meta‐analyses on extracted data for some outcomes. Due to variability in the interventions of included studies, we used a random‐effects model for all meta‐analyses.

For studies not included in meta‐analyses, and for outcomes for which we were unable to pool data, we have presented data in tables and have narratively summarised the results for each outcome.

Subgroup analysis and investigation of heterogeneity

We conducted subgroup analyses to investigate heterogeneity of mixed interventions for medication adherence. We conducted three planned subgroup analyses.

• Duration of intervention (short versus long).

• Type of outcome measure (objective versus subjective).

• Health professional group/system delivering the intervention (e.g. pharmacist versus nurse versus medical professional versus automated).

We were not able to conduct additional planned subgroup analyses to investigate heterogeneity because we found insufficient studies or poor reporting of participant characteristics. For future updates, should more studies be included (especially for other outcomes or other intervention types), we plan to also look at the following.

• Duration of follow‐up (short, medium, and long term) as described under "Timing of outcome assessment."

• Person managing the medication (consumer versus carer).

• Number of medications (up to 10 versus 11 or more medications).

• Frailty and/or functional ability (e.g. level of home assistance required) and/or cognitive function/ability.

Sensitivity analysis

We conducted sensitivity analyses for the primary outcomes that excluded studies assessed to have losses to follow‐up greater than 20%, and that excluded studies with unit of analysis errors. We had planned to also conduct sensitivity analyses that excluded studies with high risk of bias; however there were too few included studies assessed as having low risk of bias. Future updates of this review should conduct these sensitivity analyses if sufficient studies with low risk of bias are identified.

"Summary of findings" table

We prepared "Summary of findings" tables to present results of meta‐analyses based on methods described in Chapter 14 of the Cochrane Handbook for Systematic Reviews of Interventions (Schünemann 2011). We presented results of meta‐analyses for the major comparisons of the review and for each of the primary outcomes, as outlined under Types of outcome measures. We provided a source and a rationale for each assumed risk cited in the tables and used Grades of Recommendation, Assessment, Development and Evaluation (GRADE) criteria to rank the quality of evidence using GRADEprofile (GRADEpro) software (Schünemann 2011). When meta‐analysis was not possible, we present results in a narrative "Summary of findings" table format, such as that used by Chan 2011.

Ensuring relevance to decisions in health care

Authors of this review received feedback from a consumer referee and a health professional as part of the standard editorial process of the Cochrane Consumers and Communication Group.

Results

Description of studies

See Characteristics of included studies,Characteristics of excluded studies,Characteristics of ongoing studies, and Characteristics of studies awaiting classification.

Results of the search

The database search yielded 27,854 titles. We found 65 additional records through a search of grey literature. After removing duplicates, we screened 19,192 studies and reviewed 482 full‐text articles. We excluded 373 studies that did not meet the inclusion criteria and recorded our reasons for exclusion. We included 50 independent studies (from 68 citations); 40 were randomised controlled trials (RCTs), four were considered quasi‐RCTs (Begley 1997; Shimp 2012; Volume 2001; Winland‐Brown 2000), and six were cluster‐RCTs (Bernsten 2001; Moral 2015; Muth 2016; Volume 2001; Willeboordse 2017; Wood 1992). Eight studies (from 12 citations) are ongoing (see Characteristics of ongoing studies). Twenty‐six studies (from 29 citations) are awaiting classification; eight have no published results; 15 may be eligible for inclusion but provide insufficient information to allow determination of eligibility; and three will be included in the next update of this review (see Characteristics of studies awaiting classification) (Char 2017; Marusic 2018; Muth 2018). Refer to Figure 1 for a PRISMA diagram.

1.

Study flow diagram.

Included studies

Participants

A total of 14,269 participants were included in the 50 studies. Fifteen studies involved fewer than 100 participants, and six studies involved more than 500 participants. In 38 studies, the intervention was directed at patients; in one study, the intervention was directed at family caregivers (George 2016); and in 11 studies, the intervention involved both patients and caregivers. The mean/median age of included patients ranged from 65.6 to 87.0 years, and 52.4% (6893/13,143) of patients were female (three studies did not provide clear details on gender). The mean/median number of medications ranged from 4.2 to 16.3, but the definition of 'medication' varied greatly between studies and was poorly described in 24 studies (48%). Eighteen studies clearly referred to prescribed medications, but many restricted the count to regular and/or oral medications only. Non‐prescription/over‐the‐counter (OTC) medications were included in the total count in five studies (Haag 2016; Khdour 2009; Krska 2001; Lingler 2016; Marek 2013); these were reported separately in three studies (Begley 1997; Chrischilles 2014; Volume 2001). Four studies did not provide mean/median values but were included based on the published range of the number of medications being taken (Winland‐Brown 2000), or on the fact that inclusion criteria ‐ Hale 2016 ‐ or additional information provided by study authors ‐ Blalock 2010, Shively 2013 ‐ indicated that the mean/median number of medications would be greater than four. One study was included because the subgroup of people taking more than eight medications met our inclusion criteria (Truelove 2015).

Sixteen studies reported some measure of frailty and/or functional ability for included participants, but variation in the scales used prevented comparison. Twenty studies included a measure of cognitive function of participants or listed the proportion of people with cognitive impairment, but the heterogeneous nature of reporting cognitive impairment prevented comparison. Seventeen studies excluded people with cognitive impairment, and 13 did not specify any details. The total mean/median number of chronic conditions (or co‐morbidities) was mentioned in only 10 studies and ranged from three to nine chronic conditions.

Setting

Included studies were carried out across four continents: North America, Europe, Asia, and Australia (see Table A). Most studies were conducted in the USA (21), the UK (8), Canada (5), and Australia (3). Ten studies were conducted in European countries: Spain (4), Croatia (1), Denmark (1), Germany (1), the Netherlands (1), Portugal (1), and Switzerland (1). Two studies were conducted in Asian countries: China (1) and Singapore (1). One study was conducted across seven countries (Bernsten 2001).

Study healthcare settings were categorised according to where the interventions were initiated during the patient's healthcare journey. Twenty‐six studies were initiated at the interface between hospital and community: in hospital (2), immediately before discharge (11), post discharge (6), or in hospital outpatient clinics (7). Twenty‐four studies were initiated in the community/primary care setting including general practice/medical clinics/centres (11), community pharmacies (5), home healthcare services (2), a university clinic (1), an independent living facility (1), and in the home (4, with 2 delivered online and 2 involving visiting health professionals).

Table A. Study design, setting, and participants

Study ID	Study design	Target participants	Country	Stage of the patient's healthcare journey/healthcare setting where the intervention was initiated
				Hospital/Communityinterface	Community/Primary care
Al‐Rashed 2002	RCT	Patient	UK	Discharge
Begley 1997	RCT	Patient	UK	Post discharge
Bernsten 2001	Cluster‐RCT	Patient	7 countries		Pharmacy
Blalock 2010	RCT	Patient	USA		Pharmacy
Bond 2007	RCT	Patient	UK		Pharmacy
Cargill 1992	RCT	Patient + Carer	USA	Outpatient clinic*
Chrischilles 2014	RCT	Patient	USA		Home (online)
Cohen 2011	RCT	Patient	USA		Medical centre
Cossette 2015	RCT	Patient	Canada	ED discharge
George 2016	RCT	Carer	USA		Online (home)
Grymonpre 2001	RCT	Patient	Canada		Health clinic
Haag 2016	RCT	Patient	USA	Post discharge
Hale 2016	RCT	Patient	USA	Post discharge
Hanlon 1996	RCT	Patient + Carer	USA		General medicine clinic*
Holland 2007	RCT	Patient + Carer	UK	Post discharge
Khdour 2009	RCT	Patient	UK	Outpatient clinic
Krska 2001	RCT	Patient	UK		General practice clinic
Lee 2006	RCT	Patient	USA	Outpatient pharmacy*
Lim 2004	RCT	Patient	Singapore	Outpatient clinic
Lingler 2016	RCT	Patient + Carer	USA		Community
Lipton 1994	RCT	Patient + Carer	USA	Discharge
Lopez Cabezas 2006	RCT	Patient	Spain	Discharge
Manning 2007	RCT	Patient	USA	Discharge
Marek 2013	RCT	Patient	USA		Home healthcare service
Marusic 2013	RCT	Patient	Croatia	Discharge
Messerli 2016	RCT	Patient	Switzerland		Pharmacy
Moral 2015	Cluster‐RCT	Patient	Spain		General practice
Morales Suarez‐Vurela 2009	RCT	Patient + Carer	Spain		Home healthcare service
Murray 1993	RCT	Patient	USA	Outreach centre
Muth 2016	Cluster‐RCT	Patient	Germany		General practice
Nascimento 2016	RCT	Patient + Carer	Portugal		Diabetes clinic
Naunton 2003	RCT	Patient + Carer	Australia	Post discharge
Nazareth 2001	RCT	Patient + Carer	UK	Discharge
Olesen 2014	RCT	Patient	Denmark		Community
Pandey 2017	RCT	Patient	Canada	Post discharge
Pereles 1996	RCT	Patient	Canada	Inpatient
Rich 1996	RCT	Patient	USA	Discharge
Saez de la Fuente 2011	RCT	Patient + Carer	Spain	Discharge
Shimp 2012	RCT	Patient	USA		University clinic
Shively 2013	RCT	Patient	USA		Primary care clinic
Taylor 2003	RCT	Patient	USA		General practice clinic
Truelove 2015	RCT	Patient	Australia		General practice clinic
Vinluan 2015	RCT	Patient	USA	Discharge
Volume 2001	Cluster‐RCT	Patient	Canada		Pharmacy
Willeboordse 2017	Cluster‐RCT	Patient	Netherlands		General practice clinic
Williams 2012	RCT	Patient	Australia	Outpatient clinic
Winland‐Brown 2000	RCT	Patient	USA		Independent living facility
Wood 1992	Cluster‐RCT	Patient	UK	Inpatient
Wu 2006	RCT	Patient + Carer	China	Outpatient clinic
Young 2016	RCT	Patient	USA	Discharge

*Unclear whether health service provided primary or secondary care or both.

ED: emergency department.

RCT: randomised controlled trial.

Interventions

A range of simple to complex interventions were used across the included studies. Due to the heterogeneous nature of the interventions, we categorised them into three broad groups: educational interventions, behavioural interventions, and mixed interventions (both educational and behavioural). These categories have been used in a previous systematic review of interventions to improve medication‐taking in elderly patients prescribed multiple medications (George 2008).

Fourteen studies involved educational interventions comprising medication/health education (provided in writing or verbally) and/or medication review only; seven studies involved behavioural interventions only; and 29 studies had both educational and behavioural elements.

Educational interventions were identified in 38 studies delivering patient or carer education regarding medications and/or health conditions, and in 26 studies involving a review of patient medications.

A range of behavioural interventions were used (either alone or in combination) in 24 studies utilising follow‐up or monitoring; in seven studies providing regimen simplification (Begley 1997;Bernsten 2001;Lim 2004;Lipton 1994;Murray 1993;Olesen 2014; Rich 1996); in five studies practising motivational interviewing (Khdour 2009;Moral 2015;Olesen 2014;Shively 2013;Williams 2012); and in two studies implementing three‐step self‐administration of medications (Pereles 1996; Wood 1992). All participants in six studies utilised DAAs including simple pill boxes (Lee 2006; Marek 2013; Morales Suarez‐Vurela 2009; Winland‐Brown 2000), unit of use packages (Murray 1993), automated dosing devices (Marek 2013; Winland‐Brown 2000), and remotely monitored electronic devices (Hale 2016). Two studies utilised DAAs for some participants as required (Cargill 1992; Naunton 2003), and two studies provided participants with electronic pill reminder devices (Olesen 2014; Young 2016). Other types of interventions included text message adherence reminders (Pandey 2017), a four‐ingredient poly‐pill (Truelove 2015), use of online personal health records (Chrischilles 2014), and a three‐dimensional (3D ‐ durable display at discharge) medication discharge tool that involved patients affixing a tablet/capsule of each medication onto the 3D tool (Manning 2007).

Most interventions were delivered by pharmacists (31 studies), nurses (17 studies), and physicians (15 studies), either alone (31 studies) or in multi‐disciplinary teams of two or more health professionals (15 studies). Two interventions were delivered online (Chrischilles 2014; George 2016); one study involved text message reminders (Pandey 2017); and one study involved a remotely monitored electronic device (Hale 2016). Interventions varied in duration, ranging from one‐off ‐ Al‐Rashed 2002, Blalock 2010, Haag 2016, Lim 2004, Manning 2007, Marusic 2013, Muth 2016, Nascimento 2016, Naunton 2003, Saez de la Fuente 2011, Willeboordse 2017 ‐ to two years ‐ Wu 2006, and were most commonly delivered in the home (face‐to‐face or by phone calls), hospital, medical centre, or community pharmacy. Four studies were delivered across two settings (Lipton 1994; Moral 2015; Nazareth 2001; Rich 1996), and 11 studies involved both face‐to‐face meetings and phone calls (Cargill 1992; Cossette 2015; Khdour 2009; Lingler 2016; Lipton 1994; Lopez Cabezas 2006; Olesen 2014; Shively 2013; Vinluan 2015; Williams 2012; Young 2016).

An additional table summarising the intervention features of all included studies is located at https://latrobe.figshare.com/articles/Additional_tables_Cross_et_al_2020_docx/12247385.

Primary outcomes

Medication‐taking ability was measured in five studies. Four studies used objective measures including a five‐item dexterity test that assessed skills such as ability to open child‐resistant closures on containers (Begley 1997), a medication‐taking behaviour score (Cargill 1992), the Medication Management Instrument for Deficiencies in the Elderly (MedMaIDE) (Lingler 2016), performance in an inpatient self‐administration of medications programme, and/or pharmacist assessment (with input from other team members) of ability to self‐administer medications (Pereles 1996). One study used a subjective measure ‐ a self‐reported assessment of safety in taking medication (Manning 2007). Medication‐taking ability was typically measured at short follow‐up points (e.g. 7 to 14 days; Manning 2007), except for one study, which had an extended measure at 12 months (Begley 1997).

Medication adherence was measured in 48 studies (Table C). Twenty studies used an objective measure of adherence such as pill count (Begley 1997;Cargill 1992;Cohen 2011;Lee 2006;Lopez Cabezas 2006;Marusic 2013;Moral 2015;Murray 1993;Olesen 2014;Pereles 1996;Rich 1996;Williams 2012;Winland‐Brown 2000;Wood 1992), prescription claims/refills (Al‐Rashed 2002;Grymonpre 2001;Messerli 2016;Shimp 2012;Vinluan 2015), or machine‐recorded correct doses (Marek 2013). Twenty‐eight studies used a subjective measure of adherence; 16 of these used an original or modified version of the Morisky Medication Adherence Scale ‐ a validated measure of adherence (Bernsten 2001;Chrischilles 2014;Cossette 2015;George 2016;Haag 2016;Hale 2016;Khdour 2009;Morales Suarez‐Vurela 2009;Muth 2016;Nascimento 2016;Saez de la Fuente 2011;Volume 2001), the Medication Adherence Rating Scale (Bond 2007;Holland 2007;Muth 2016), the Brief Medication Questionnaire (Blalock 2010), and the Medical Outcome Study‐Specific Adherence Scale (Shively 2013). Four studies used structured interviews to enquire about adherence (Hanlon 1996;Lipton 1994;Nazareth 2001;Willeboordse 2017), and six studies asked participants a single question about forgotten or missed doses (Lim 2004;Naunton 2003;Taylor 2003;Truelove 2015;Wu 2006;Young 2016). One study used a patient‐completed daily log‐book of medication consumption (Pandey 2017), and one study included pharmacist review for pharmaceutical care issues including potential or actual adherence issues (Krska 2001). The longest follow‐up time points of post‐intervention adherence outcomes ranged from 1 month to 18 months, with the median time point of 6 months.

Secondary outcomes

Knowledge about medications was measured in 13 studies. Knowledge was assessed most often by asking participants about one or more of the following: name of medication, appearance of medication, purpose of medication, dose, dose frequency/interval, side effects, drug interactions, and special comments or cautions (Al‐Rashed 2002; Begley 1997; Bernsten 2001; Grymonpre 2001; Hanlon 1996; Lim 2004; Manning 2007; Messerli 2016; Nazareth 2001; Pereles 1996; Taylor 2003). One study asked participants on a 5‐point Likert scale if they "knew more about their medicines compared to a year ago" (Bond 2007), and another study assessed medication knowledge as part of a larger chronic obstructive pulmonary disease (COPD) knowledge questionnaire (Khdour 2009).

Satisfaction with the intervention was measured in 13 studies. Six studies used a previously validated measure (George 2016;Hanlon 1996;Lopez Cabezas 2006;Nazareth 2001;Volume 2001;Willeboordse 2017), but no two studies used the same measure. Satisfaction was most commonly assessed on a 5‐point Likert‐type scale (Bernsten 2001;Bond 2007;Hanlon 1996;Manning 2007), or on a 7‐point Likert‐type scale (George 2016;Volume 2001;Willeboordse 2017), which included between one ‐ Manning 2007, Willeboordse 2017 ‐ and 15 items (Bond 2007). Lopez Cabezas 2006 used a 0 to 10 analogue scale, and four studies did not adequately describe the measure used (Holland 2007;Lingler 2016;Naunton 2003;Taylor 2003).

Health‐related quality of life (HRQoL) was measured in 14 studies. The two most common measures were the validated Short Form Health Survey involving 36 items (SF‐36) used in eight studies ‐ Bernsten 2001, Bond 2007, Cohen 2011, Hanlon 1996, Krska 2001, Marek 2013, Taylor 2003, Volume 2001 ‐ and the European Quality of Life 5‐Dimension Instrument (EQ‐5D) used in five studies ‐ Bond 2007, Holland 2007, Lopez Cabezas 2006, Muth 2016, Willeboordse 2017. Other measures used by individual studies included the 12‐item Short Form Health Survey (SF‐12; Willeboordse 2017), as well as disease‐specific quality of life measures including the Minnesota Living With Heart Failure Questionnaire (MLHFQ) ‐ Hale 2016, Holland 2007 ‐ and St George's Respiratory Questionnaire (SGRQ) ‐ Khdour 2009.

Adverse clinical health outcomes were measured in 28 studies and included measures such as emergency department (ED) and/or hospital admissions (Al‐Rashed 2002; Bernsten 2001; Cossette 2015; Haag 2016; Hale 2016; Holland 2007; Khdour 2009; Lipton 1994; Lopez Cabezas 2006; Marusic 2013; Messerli 2016; Muth 2016; Naunton 2003; Nazareth 2001; Olesen 2014; Rich 1996; Saez de la Fuente 2011; Shively 2013; Taylor 2003; Vinluan 2015; Winland‐Brown 2000; Wu 2006; Young 2016), mortality (Holland 2007; Lopez Cabezas 2006; Naunton 2003; Nazareth 2001; Olesen 2014; Saez de la Fuente 2011; Vinluan 2015; Wu 2006), adverse drug reactions (Chrischilles 2014; Hanlon 1996; Lim 2004; Marusic 2013; Murray 1993; Willeboordse 2017), and physician visits (Al‐Rashed 2002; Khdour 2009; Nazareth 2001; Winland‐Brown 2000).

Condition‐specific outcomes were measured in seven studies and included changes in blood pressure (Lee 2006;Taylor 2003;Williams 2012), diabetes control ‐ glycosylated haemoglobin (HbA1c)/blood glucose (Nascimento 2016;Taylor 2003;Williams 2012), low‐density lipoprotein (LDL) cholesterol (Lee 2006;Taylor 2003), falls (Blalock 2010), international normalised ratio (INR) of time taken for blood to clot (Taylor 2003), and renal function (Williams 2012). Two studies reported composite measures of reaching multiple 'health' targets (Bond 2007;Cohen 2011).

Cost‐effectiveness of the intervention was measured in four studies; three studies used costs of the intervention, medicines, hospitalisations, and/or health consultations (Bernsten 2001;Bond 2007;Lopez Cabezas 2006), and one study used US Medicare Part B costs and total hospital inpatient costs (Lipton 1994).

Other outcome measures extracted included medication management problems from a list of eight problems (Chrischilles 2014), a medication deficiency checklist (Lingler 2016), medication errors defined as both prescriber and patient errors (Moral 2015), and medication misadventures defined as one or more medication errors, adverse drug events, or adverse drug reactions (Taylor 2003).

An additional table summarising the type and timing of primary and secondary outcomes assessed by included studies is located at https://latrobe.figshare.com/articles/Additional_tables_Cross_et_al_2020_docx/12247385.

Excluded studies

We excluded 373 studies in total (see Characteristics of excluded studies). We excluded 24 studies because study design did not meet Cochrane criteria for an RCT, a cluster‐RCT, or a quasi‐RCT. We excluded 149 studies on the basis of the age of participants; 88 studies based on the number of regular prescription medications (including 13 studies for which the number of medications was unknown and attempts to contact study authors were unsuccessful); and 10 studies because study authors did not collect information on the number of medications. We excluded 94 studies because they did not include a measure of medication‐taking ability or medication adherence as an outcome, and 8 studies because the follow‐up period for outcome measures was too short (i.e. < 48 hours for medication‐taking ability, < 4 weeks for adherence). We excluded 6 studies because the intervention did not target consumers, along with 4 studies because participants were not community‐dwelling.

Risk of bias in included studies

See Characteristics of included studies table, Figure 2, and Figure 3 for a summary assessment of the risk of bias of included studies.

2.

Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.

3.

Risk of bias summary: review authors' judgements about each risk of bias item for each included study.

Allocation

Risk of bias for random sequence generation was low in 22 studies (44%), unclear in 24 studies (48%), and high in four studies (8%). For concealment of allocation, risk of bias was low in 17 studies (34%), unclear in 30 studies (60%), and high in three studies (6%). Selective recruitment of cluster participants was assessed for the six cluster‐RCTs ‐ three were considered at high risk (Moral 2015;Willeboordse 2017;Volume 2001), two were considered at low risk (Muth 2016;Wood 1992), and one was considered at unclear risk of recruitment bias (Bernsten 2001).

Blinding

Blinding of both participants and personnel could not be achieved through the study design in 49 of the 50 studies (98%), leading to high risk of performance bias. One study was considered to have low risk of performance bias, as the intervention was delivered online and both intervention and control participants viewed the same interface and thus were unaware of their allocation (George 2016).

Seventeen studies (34%) stated that there was no blinding of outcome assessment; we considered these studies to have high risk of detection bias. Twenty studies (40%) were assessed as having 'unclear' risk of detection bias due to insufficient details regarding the method of outcome assessment. Studies with unclear detection bias included one study for which data collection was performed "where possible" by a member of staff other than the intervention pharmacist (Bernsten 2001), one study involving caregiver‐reported patient adherence when caregivers were assumed to be unaware of allocation (George 2016), and two studies in which assessors were reported as blinded but contamination from unblinded participants was thought to be highly likely (Saez de la Fuente 2011; Young 2016). We assessed 13 studies (26%) as having low risk of detection bias; five involved an objective measure of the primary outcome (Grymonpre 2001;Marusic 2013;Messerli 2016;Rich 1996; Williams 2012), and eight involved subjective measures but data were collected/analysed by blinded investigators (Bond 2007;Chrischilles 2014;Cossette 2015;Haag 2016;Hanlon 1996;Lipton 1994;Manning 2007;Nazareth 2001).

Incomplete outcome data

Twenty‐two (44%) studies were considered to have incomplete outcome data and therefore high risk of attrition bias – 19 of these cases were due to high loss to follow‐up. A further three (6%) studies were assessed as having high risk of attrition bias due to inconsistency between the average number of medicines and the number assessed for adherence (Grymonpre 2001), inconsistency between the number of patients with adherence reported and the number who saved their medication boxes enabling accurate pill count (Williams 2012), and lack of details regarding attrition of the control group (Shimp 2012). Thirteen studies were assessed as having unclear risk of bias mainly due to low to moderate attrition, which may have had an impact on the results, or insufficient details on number of, or reasons for, attrition. Fifteen studies reported minimal incomplete outcome data and/or adequately addressed this (low risk of bias).

Selective reporting

Fourteen studies (28%) were considered to have high risk of reporting bias ‐ 12 due to missing outcome data (Begley 1997;Blalock 2010;Cohen 2011;Krska 2001;Lim 2004;Lopez Cabezas 2006;Messerli 2016;Morales Suarez‐Vurela 2009;Murray 1993;Olesen 2014;Shimp 2012; Winland‐Brown 2000), one because study authors did not clearly specify how data were obtained (Vinluan 2015), and one because researchers changed the inclusion criteria mid‐way through the study to increase recruitment (Williams 2012).

Twelve studies (24%) were considered to have unclear risk of reporting bias due to minor deviations from study methods (Bond 2007;Grymonpre 2001;Lipton 1994;Wood 1992), missing information in the methods section (Bernsten 2001;Willeboordse 2017), missing baseline data (Lee 2006), and unclear reporting of results (Cargill 1992;Lingler 2016;Marek 2013;Moral 2015;Willeboordse 2017).

Although 24 studies (48%) were assessed as having low risk of selective reporting, 15 of these did not have a published protocol nor trial registration; thus it was difficult to accurately assess reporting bias.

Other potential sources of bias

Four studies were identified as having high risk of other types of bias. One study was assessed as having high risk because it was a research thesis and had not been published in a peer‐reviewed journal (George 2016), two studies because of poor intervention fidelity (Chrischilles 2014;Nazareth 2001), and one study because researchers measured adherence only for the first three medications mentioned by the patient (Lipton 1994).

Twenty‐seven studies were considered to have unclear risk of other types of bias. Sixteen studies did not reach their specified target sample size (Bernsten 2001;Blalock 2010;Bond 2007;Cossette 2015;Hale 2016;Khdour 2009;Lopez Cabezas 2006;Marek 2013;Messerli 2016;Moral 2015;Morales Suarez‐Vurela 2009;Pereles 1996;Truelove 2015;Volume 2001;Willeboordse 2017; Wu 2006); three studies had unbalanced participant groups likely influencing outcomes (Haag 2016; Murray 1993; Winland‐Brown 2000); and four studies had potential conflicts due to funding arrangements (Holland 2007; Shimp 2012) or participant compensation (Messerli 2016; Shively 2013), which may have biased results of the study. Two studies provided limited information regarding intervention fidelity (Manning 2007; Nascimento 2016), and four studies expressed concerns regarding the appropriateness of the adherence assessment (Nascimento 2016; Rich 1996; Pandey 2017; Williams 2012).

Trial authors also noted that 10 studies did not declare a funding source. However, given the differences in journal requirements and the age of those studies, this was not considered to introduce risk of bias for this review.

Effects of interventions

See: Table 1; Table 2; Table 3

Summary of findings 1. Summary of findings: mixed interventions.

Mixed educational and behavioural interventions aimed at improving medication‐taking ability and/or medication adherence compared with usual care for older community‐dwelling patients taking multiple medications
Patient or population: older patients using at least 4 regular prescription medications (and/or their carers) Settings: community setting (including discharge from a hospital or other healthcare facility to the community) Intervention: interventions involving both educational and behavioural components Comparison: usual care
Outcomes	Impacts	No of Studies	Quality of the evidence (GRADE)
Medication‐taking ability Follow‐up: 2 weeks to 12 months	The effects of mixed interventions on medication‐taking ability were unable to be determined. Meta‐analysis was not possible due to all 5 studies using different outcome measures. Of the 5 studies, 1 demonstrated significant improvement in medication‐taking ability, 2 showed no significant impact, 1 did not test for differences between groups, and 1 did not report results	5	Lowa,b
Medication adherence (dichotomous) Follow‐up: 1 to 18 months	Mixed interventions may improve the proportion of people who are adherent (dichotomous adherence outcome) Twelve studies (3147 participants) were included in a meta‐analysis. Risk ratio was 1.22 (95% CI 1.08 to 1.37), indicating interventions increased the absolute number of adherent participants by 12.8% (4.6% to 21.5%) Two studies were excluded from the meta‐analysis due to alternate reporting of outcome data: 1 study reported the intervention increased the number of medications taken correctly; 1 study showed no differences between groups	14	Lowa,b
Medication adherence (continuous) Follow‐up: 1 to 12 months	Mixed interventions may have little or no impact on medication adherence measured by continuous adherence outcomes (e.g. proportion of pills dispensed or taken) Seven studies (1825 participants) were included in a meta‐analysis. Standardised mean difference was 0.47 (95% CI ‐0.08 to 1.02), indicating that the mean adherence score in the intervention group was 0.47 standard deviations higher (0.08 lower to 1.02 higher) than in the usual care group Four studies were excluded from the meta‐analysis due to alternate reporting of outcome data: 1 study showed fewer medication errors as a proportion of total doses with the intervention; 3 studies showed no significant effect on adherence. Two additional studies were excluded due to unclear reporting of results	13	Lowb,c
Health‐related quality of life Follow‐up: 6 to 18 months	Mixed interventions may lead to little or no change in health‐related quality of life. Six of 7 studies showed no significant impact on this outcome. One study reported the intervention may improve both physical and mental summary scores on the SF‐36 at 12 months. Meta‐analysis was not possible due to differences in scales used and differences in reporting of results	7	Lowa,b
Emergency department (ED)/Hospital admissions Follow‐up: 1 to 24 months	Mixed interventions may reduce the number of emergency department (ED) and/or hospital admissions. Eleven studies (1827 participants) were included in meta‐analysis. Risk ratio was 0.67 (95% CI 0.50 to 0.90), indicating mixed interventions may reduce the absolute number of patients admitted to ED/hospital by 12.3% (18.7% to 3.7% fewer). Six studies were excluded from the meta‐analysis due to alternate reporting of outcome data; none of these studies reported differences between groups in ED/hospital admissions	17	Lowa,b
Mortality Follow‐up: 3 to 24 months	We are uncertain of the effects of mixed interventions on mortality. Seven studies (1776 participants) were included in a meta‐analysis. Risk ratio was 0.93 (95% CI 0.67 to 1.30), with an anticipated absolute effect of 0.9% fewer deaths (4.1% fewer to 3.8% more). One study was excluded from meta‐analysis due to incomplete information	8	Very lowa,b,d
CI: confidence interval; SF‐36: Short Form Health Survey‐36.
GRADE Working Group grades of evidence. High quality: further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: we are very uncertain about the estimate.

^aOne mark deducted due to high or unclear risk of bias across multiple domains including sequence generation and allocation concealment.

^bOne mark deducted due to variations in intervention, provider, setting, duration, and outcome measures, and because of high levels of heterogeneity in results.

^cOne mark deducted due to high or unclear risk of bias across multiple domains and inclusion of studies at risk of attrition bias in meta‐analysis.

^dOne mark deducted due to imprecision with limits of confidence intervals including both substantial potential benefit and harm.

Summary of findings 2. Summary of findings: educational interventions alone.

Educational interventions aimed at improving medication‐taking ability and/or medication adherence compared with usual care for older community‐dwelling patients taking multiple medications
Patient or population: older patients using at least 4 regular prescription medications (and/or their carers) Settings: community setting (including discharge from a hospital or other healthcare facility to the community) Intervention: interventions involving educational components only Comparison: usual care
Outcomes	Impacts	No of studies	Quality of the evidence (GRADE)
Medication‐taking ability Follow‐up: N/A	No studies that evaluated medication‐taking ability were found	‐	‐
Medication adherence (dichotomous) Follow‐up: 1 to 6 months	We are uncertain of the effects of educational interventions on the proportion of people who are adherent Two studies (182 participants) using dichotomous measures of adherence were included in a meta‐analysis. Risk ratio was 1.66 (95% CI 1.33 to 2.06), indicating that educational interventions increased the absolute number of adherent participants by 31.1% (15.6% to 50.1% more) Three studies were excluded from the meta‐analysis due to alternate reporting of outcome data: 1 study reported that the intervention increased the number of resolved medication issues (including non‐adherence); 2 studies reported no significant effect on adherence	5	Very lowa,b,c
Medication adherence (continuous) Follow‐up: 1 to 12 months	Educational interventions may have little or no impact on medication adherence measured by continuous adherence outcomes (e.g. proportion of pills dispensed or taken) Five studies (1165 participants) using continuous measures of adherence were included in a meta‐analysis. Standardised mean difference was 0.16 (95% CI ‐0.12 to 0.43), indicating that the mean adherence score in the intervention group was 0.16 standard deviations higher (0.12 lower to 0.43 higher) than in the usual care group Four studies were excluded from the meta‐analysis: 2 due to alternate reporting of outcome data (neither showed a difference between groups); 2 did not report results	9	Lowa,b
Health‐related quality of life Follow‐up: 3 to 12 months	Educational interventions probably have little or no effect on health‐related quality of life, with all 6 studies reporting no differences between groups. Meta‐analysis was not possible due to differences in scales used and differences in reporting of results	6	Moderatea
ED/Hospital admissions Follow‐up: 4 to 28 weeks	Educational interventions probably have little or no effect on ED/hospital admissions. Three studies (554 participants) were included in a meta‐analysis. Risk ratio was 1.02 (95% CI 0.71 to 1.48), indicating no change in the number of patients admitted to ED/hospital. One further study not included in meta‐analysis, reporting mean number of days in hospital, found no differences between groups	4	Moderatea
Mortality Follow‐up: N/A	No studies that evaluated the effects of educational interventions on mortality were found	‐	‐
CI: confidence interval; ED: emergency department.
GRADE Working Group grades of evidence. High quality: further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: we are very uncertain about the estimate.

^aOne mark deducted due to high or unclear risk of bias across multiple domains including sequence generation and allocation concealment.

^bOne mark deducted due to variations in intervention, provider, setting, duration, and outcome measures, and because of high levels of heterogeneity in results.

^cOne mark deducted due to imprecision ‐ small total number of participants and only two studies in meta‐analysis (one had very wide confidence interval and low events) plus the number of adherent patients (i.e. events) were not clearly reported in the two studies excluded from meta‐analysis.

Summary of findings 3. Summary of findings: behavioural interventions alone.

Behavioural interventions aimed at improving medication‐taking ability and/or medication adherence compared with usual care for older community‐dwelling patients taking multiple medications
Patient or population: older patients using at least 4 regular prescription medications (and/or their carers) Settings: community setting (including discharge from a hospital or other healthcare facility to the community) Intervention: interventions involving behavioural components only Comparison: usual care
Outcomes	Impacts	No of studies	Quality of the evidence (GRADE)
Medication‐taking ability Follow‐up: N/A	No studies that evaluated medication‐taking ability were found	‐	‐
Medication adherence (dichotomous) Follow‐up: 3 to 18 months	Behavioural interventions may improve the proportion of people who are adherent (dichotomous adherence outcome) Four studies (528 participants) were included in a meta‐analysis. Risk ratio was 1.22 (95% CI 1.07 to 1.38), indicating behavioural interventions increased the absolute number of adherent participants by 10.5% (3.3% to 18.1% more)	4	Lowa,b
Medication adherence (continuous) Follow‐up: 6 to 12 months	We are uncertain of the effects of behavioural interventions on medication adherence when continuous measures of adherence are used Three studies were identified, but results could not be pooled in a meta‐analysis due to differences in reporting. All 3 reported significant impact on medication adherence, 2 showed large effects on adherence based on pill count, and 1 showed moderate improvement in self‐reported adherence using daily logbooks to calculate percentage of days adherent	3	Very lowa,b,c
Health‐related quality of life Follow‐up: 3 months	We are uncertain of the effects of behavioural interventions on health‐related quality of life. Only 1 study was identified, which found that the intervention resulted in worsening quality of life using the Minnesota Living With Heart Failure Questionnaire	1	Very lowa,d,e
ED/Hospital admissions Follow‐up: 3 to 6 months	We are uncertain of the effects of behavioural interventions on ED/hospital admissions. Two studies (70 participants) were included in a meta‐analysis. Risk ratio was 0.21 (95% CI 0.08 to 0.55), indicating behavioural interventions may reduce the absolute number of patients admitted to ED/hospital by 42.9% (49.9% to 24.4% fewer)	2	Very lowa,f
Mortality Follow‐up: N/A	No studies that evaluated the effects of behavioural interventions on mortality were found	‐	‐
CI: confidence interval; ED: emergency department.
GRADE Working Group grades of evidence. High quality: further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: we are very uncertain about the estimate.

^aOne mark deducted due to high or unclear risk of bias across multiple domains including sequence generation and allocation concealment.

^bOne mark deducted due to variations in intervention, provider, setting, duration, and outcome measures.

^cOne mark deducted due to low participant numbers.

^dOne mark deducted due to indirectness of evidence as the Minnesota Living With Heart Failure Questionnaire is specific for heart failure populations and results may not be generalisable to general population of older people.

^eOne mark deducted due to low participant numbers from a single small study.

^fTwo marks deducted due to low participant numbers and low number of events.

See "Summary of findings" tables for the main comparison.

COMPARISON 1. Intervention versus usual care

Primary outcome ‐ medication‐taking ability

Educational interventions

No studies were identified.

Behavioural interventions

No studies were identified.

Mixed educational and behavioural interventions

Mixed educational and behavioural interventions were identified in five studies, which showed mixed impact on medication‐taking ability (Table 4; low‐certainty evidence). One study involving an educational intervention combined with telephone follow‐up directed at both patients and caregivers (group 3) showed slightly greater improvement in medication‐taking ability compared to usual care (group 1), as measured by a behaviour score at four to six weeks (mean scores presented visually; mean 86/100 versus 74/100; P = 0.01) (Cargill 1992). Another study, also involving an educational intervention plus follow‐up, demonstrated significant decreases in medication management problems, as measured by the Management Instrument for Deficiencies in the Elderly (MedMaIDE), in both intervention and usual care groups but did not report between‐group comparisons (Lingler 2016). Two studies showed no significant difference in patients' medication‐taking ability (Manning 2007; Pereles 1996). In Manning 2007, a medication chart with tablets/capsules affixed and medication discharge education had no significant impact on the number of self‐reported mistakes in taking medication. In Pereles 1996, an inpatient self‐administration of medication programme was reported to have no impact on the number of participants able to self‐administer their medications; however, different methods of assessing the outcome were used for intervention and control groups. One study involving patient‐focused education and regimen simplification did not report results (Begley 1997).

1. Primary outcome ‐ medication‐taking ability.

Study	Measure of medication‐taking ability	Outcome
Begley 1997	Objective measure: 5‐task dexterity test (e.g. opening child‐resistant closure), 1 point awarded for each successfully completed activity. Note: no difference across groups at baseline ‐ mean (SD) group A: 7.8 (1.3), group B: 7.5 (1.5), group C: 8.0 (1.4)	Objective measure: follow‐up results not reported
Cargill 1992	Objective measure: behaviour score/100 for congruency between supply of medications on hand and prescribed medications (/40), verbalising correct regimen (/30), maintaining each prescribed med (/20), appropriate use of OTC (/10). Points deducted for sequestering old scripts, inappropriate use of alternative medications, or mixing medications together	Mean read from graph: Control: 74 vs intervention (group 3); 86 vs intervention (group 2); 84 vs intervention (group 3): 86
Lingler 2016	Objective measure: Medication Management Instrument for Deficiencies in the Elderly (MedMaIDE). MedMaiDE uses interview and observation to assess ability to self‐administer medications in 3 areas: knowledge of medications, how to take medications, and how to procure medications. Each medication is reviewed during administration. Scores 0 to 13, max total deficiency score is 13	Baseline: mean ± SD intervention 0.833 ± 0.745 vs control 0.692 ± 0.768 Unpublished follow‐up results: mean ± SD: intervention 0.595 ± 0.725 vs control 0.297 ± 0.777; both groups showed significant decreases in number of medication management problems at 2 months (P < 0.01)
Manning 2007	Subjective measure: self‐reported safety. Since discharge, how many mistakes have you made taking your medications (score 0 to 4)?	Mean ± SD: intervention 0.78 ± 0.4187 (n = 72) vs control 0.79 ± 0.4113 (n = 57)
Pereles 1996	Objective measure: assessed differently for each group: intervention = pharmacist assessment with input from other team members, primarily based on having made 2 or fewer errors at stage 2 of the inpatient self‐medication programme ‐ considered able to self‐medicate at discharge. Control = pharmacist assessment with input from other team members at time of discharge counselling. YES/NO ‐ self‐medicating at discharge (note: there could be reasons other than failing the SMP that might explain why they were not self‐medicating at discharge, such as patient preference)	n (%): intervention 39 (76.5%) vs control 39 (69.6%)

OTC: over‐the‐counter.

SD: standard deviation.

Subgroup analysis was not possible due to the small number of eligible studies.

Overall,

• no studies were identified that evaluated the impact of educational or behavioural interventions alone on medication‐taking ability; and

• the effect of mixed interventions on medication‐taking ability was unable to be determined (low‐quality evidence). The evidence was downgraded due to high or unclear risk of bias across multiple domains (‐1) and for inconsistency (‐1) (variations in interventions, outcome measures, settings, duration, etc.).

Primary outcome ‐ adherence

Forty‐eight studies included a measure of adherence and were analysed based on the type of intervention provided: educational (n = 14 studies), behavioural (n = 7 studies), or mixed (n = 27 studies).

Meta‐analyses were possible for 31 studies: 18 involving dichotomous measures (Analysis 1.1), and 13 involving continuous measures (Analysis 1.2). The 17 studies not included in meta‐analyses are briefly summarised in Table 5 and in the following subsections.

1.1. Analysis.

Comparison 1: Interventions versus usual care, Outcome 1: Primary outcome: adherence, grouped by types of interventions (dichotomous)

1.2. Analysis.

Comparison 1: Interventions versus usual care, Outcome 2: Primary outcome: adherence, grouped by types of interventions (continuous)

2. Primary outcome ‐ adherence (studies not included in meta‐analyses).

Study	Measure of adherence	Outcome
Al‐Rashed 2002	Objective measure: percentage compliance using home medicines stocks and refill prescriptions between visits 1 and 2	Intervention: 70% (n = 342 medications) vs control 15.8% (n = 328 medications)
Blalock 2010	Subjective measure: Brief Medication Questionnaire (5‐item regimen screen that assesses how medication is used)	Not reported
Bond 2007	Subjective measure: Extended Medication Adherence Report Scale (MARS) questionnaire (12 statements about medicine‐taking; score range 12 to 60)	Med (IQR): intervention 59 (57 to 60) vs control 59 (57 to 60)
Cargill 1992	Objective measure: pill count, percentage of pills taken compared to those prescribed	Mean scores: control: 74.5; intervention (group 3): 76.2; intervention (group 2): 74; intervention (group 3): 76.2
Cohen 2011	Objective measure: medication possession ratios	Not clearly reported
Hanlon 1996	Subjective measure: self‐report proportion of medications for which the patient's response agreed with the directions for use on the action profile	Intervention 77.4% (n = 86 people) vs usual care 76.1% (n = 83 people)
Holland 2007	Subjective measure: Medication Adherence Report Scale (MARS) scores from 5 (very poor adherence) to 25 (perfect adherence)	Mean (median): 23.74 (25), n = 101 vs 23.55 (25), n = 103
Krska 2001	Subjective measure: pharmaceutical care issues including potential or actual compliance issues, number of baseline issues resolved at 3 months	51 of 74 issues resolved (n = 168) vs 21 of 69 issues resolved (n = 164)
Lim 2004	Subjective measure: self‐reported; patients asked if they 'forgot to take medication as directed'. Then categorised as least compliant (compliant base, not at 2 months), not compliant (not compliant at base or at 2 months), compliant (compliant at 2 months)	Not clearly reported; unadjusted OR 1.50, 90% CI 0.73 to 3.08
Marek 2013	Objective measure: machine recorded or nurse pill count, average percentage of correct doses per month	Not reported for control group MD.2: 98.8% (SD 0.32), planner: 97.4% (SD 5.19)
Pandey 2017	Subjective measure: participants used a logbook to record name and timing of medications taken on a daily basis. Absolute medication adherence calculated as percentage of total prescribed doses that were actually taken each month. 12 months adherence calculated as the mean of each of the 12 monthly measurements. Adherence outcome is % of days covered	Intervention: 91% (n = 9), control: 73% (n = 8)
Pereles 1996	Objective measure: patients discharged with 40 days worth of medication, pill count conducted in home at 40 days. Number of medication errors as a proportion of the total doses administered	Not clearly reported After controlling for age and MMSE ‐ I: 0.045, C: 0.086; P < 0.001
Shimp 2012	Objective measure: medication possession ratios defined as sum of all days of medication supply received during year divided by total numbers of days supply needed ‐ calculated for top 8 drug classes for chronic conditions	Not reported ‐ MPRs were very high for both groups (range 0.84 to 0.96), and no clinically meaningful changes were observed over time for either group. Fewer patients reported missed doses after the intervention
Taylor 2003	Subjective measure: self‐reported number of medication doses missed. Presented as % adherence	Intervention mean 100 vs control mean 88.9 (± SD 6.3)
Volume 2001	Subjective measure: Morisky Adherence, scores 0 to 4; lower scores = better adherence	Mean SD: 0.56 ± 0.75 vs 0.47 ± 0.69; number of participants in each group unclear
Willeboordse 2017	Subjective measure: self‐reported adherence problems	Persistence of adherence problems = OR 0.83 (0.54 to 1.27) (P = 0.38) (unpublished = adherence worsened or persisted: 65 vs 54; adherence improved or remained the same: 143 vs 144)
Winland‐Brown 2000	Objective measure: pill count, average number of missed doses (unclear over what time period). Please note: group 2 vs group 3 was used for comparison of intervention vs usual care; group 1 vs group 2 was used for comparison of intervention vs intervention	Mean: group 1 = 15.1, group 2 = 1.7, control = 19.7

Outcome results presented as intervention group vs usual care group unless otherwise stated.

C: control.

CI: confidence interval.

I: intervention.

IQR: interquartile ratio.

MMSE: Mini‐Mental State Examination.

MPR: medication possession ratio.

OR: odds ratio.

SD: standard deviation.

Educational interventions

Educational interventions were identified in 14 studies; seven studies were included in meta‐analyses. Two studies ‐ Haag 2016; Marusic 2013 ‐ involving dichotomous measures of adherence and five studies ‐ George 2016; Grymonpre 2001; Messerli 2016; Muth 2016; Nascimento 2016 ‐ involving continuous measures of adherence were included in the meta‐analyses. Analysis 1.1.1 indicated that educational interventions increase the proportion of patients who are adherent (risk ratio (RR) 1.66, 95% confidence interval (CI) 1.33 to 2.06); however results were strongly influenced by Marusic 2013. Three additional studies reported dichotomous data (Table 5), which could not be included in the meta‐analyses due to incomplete data or reporting of results in a format that could not be meta‐analysed. Krska 2001 increased the number of participants who had pharmaceutical care issues (e.g. non‐adherence) resolved (intervention: 68.9% versus usual care: 30.4% resolved), and two other studies reported no differences between groups (Hanlon 1996; Willeboordse 2017).

Overall, the quality of evidence was rated as very low, meaning we are uncertain of the effects of educational interventions on adherence measured dichotomously. We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains including sequence generation and allocation concealment, (by ‐1) for inconsistency (high I² and variations in intervention, providers, settings, duration, and outcome measures), and (by ‐1) for imprecision (only two studies in the meta‐analysis; one with very wide confidence interval and low events).

Analysis 1.2.1 showed that educational interventions may have little or no impact on adherence when assessed via continuous measures (standardised mean difference (SMD) 0.16, 95% CI ‐0.12 to 0.43), but heterogeneity was substantial (I² = 74%). Sensitivity analysis performed after one study with high attrition ‐ George 2016 ‐ was removed did not substantially alter the result (SMD 0.16, 95% CI ‐0.14 to 0.47). Four further studies reported continuous measures of adherence and could not be included in the meta‐analysis (Table 5) due to incomplete data or reporting of results in a format that could not be meta‐analysed (e.g. median, interquartile ratio (IQR)). Two studies reported no differences between groups (Bond 2007; Volume 2001), and two studies had no clear results available (Blalock 2010; Shimp 2012), but one study did report that a high medication possession ratio across both intervention and usual care groups meant that no clinically meaningful differences were observable (Shimp 2012).

Overall, educational interventions may have little or no effect on medication adherence measured by continuous adherence outcomes, with quality of evidence assessed as low. We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains and (by ‐1) for inconsistency (high I² and variations in interventions, providers, settings, duration, and outcome measures).

In total, 3 of the 14 educational interventions had positive effects on adherence, and all three were delivered as one‐off interventions. In Krska 2001 and Nascimento 2016, pharmacists provided individualised medication management education and medication reviews at home; Nascimento 2016 also provided therapeutic education on diabetes care. In Marusic 2013, physicians who were specialists in clinical pharmacology provided pre‐discharge counselling (e.g. medication indications, dosages, administration, importance of compliance, possible adverse drug reactions (ADRs)) to participants 24 hours before discharge. Adherence was measured through different measures and at different time points in each study; pharmacist assessment of pharmaceutical care issues included actual or potential adherence issues at three months (Krska 2001), pill count at 30 days (Marusic 2013), and subjective use of a Portuguese/Spanish variation of the Morisky adherence measure at six months (Nascimento 2016).

Behavioural interventions

Behavioural interventions were identified in seven studies, four of which were suitable for inclusion in meta‐analyses. Four studies used a dichotomous measure of adherence, and the meta‐analysis showed that behavioural interventions increased the proportion of adherent patients (Analysis 1.1.2; RR 1.22, 95% CI 1.07 to 1.38) (Hale 2016; Moral 2015; Morales Suarez‐Vurela 2009; Truelove 2015). Sensitivity analysis after removal of one study with high attrition ‐ Truelove 2015 ‐ did not alter the result substantially (RR 1.22, 95% CI 1.02 to 1.45).

Three studies were unable to be included in the meta‐analyses, one due to non‐reporting of standard deviations ‐ Winland‐Brown 2000 ‐ and one due to reporting of the percentage of days covered rather than the percentage of participants adherent (Pandey 2017). Both reported positive effects on adherence. Winland‐Brown 2000 reported fewer missed doses assessed via pill count among participants in the intervention group (1.7 intervention group versus 19.7 usual care), and Pandey 2017 reported a higher percentage of days adherent (91% absolute adherence intervention versus 73% usual care). The remaining single study that used a continuous measure reported a large effect on adherence (mean difference (MD) 13.60, 95% CI 7.78 to 19.42) (Murray 1993).

Overall, behavioural interventions may increase the proportion of people who are adherent to medications, but we are uncertain of the effects of behavioural interventions on medication adherence measured via continuous adherence outcomes. Quality of evidence was assessed as low for dichotomous outcomes and very low for continuous outcomes. We downgraded the evidence for both outcomes (by ‐1) due to high or unclear risk of bias across multiple domains and (by ‐1) for inconsistency (high I² and variations in interventions, providers, settings, duration, and outcome measures). We also downgraded the evidence for continuous outcomes (by ‐1) for imprecision (low participant numbers).

In total, five of the seven behavioural interventions had an individual positive impact on adherence. Two studies involved DAAs: Murray 1993 involved pharmacist‐led regimen simplification to twice‐daily dosing intervals and provided medications in unit of use packaging (translucent plastic cups with lids containing all medications for that dosing time), and Winland‐Brown 2000 used an automated dispenser with audible reminders. The remaining three studies all used different interventions: Truelove 2015 involved a cardiovascular four‐ingredient poly‐pill, Pandey 2017 sent once‐daily text message adherence reminders to participants, and Moral 2015 involved physician/nurse‐led motivational interviewing and follow‐up. Adherence was measured objectively at six months via pill count in three studies (Moral 2015; Murray 1993; Winland‐Brown 2000), and it was measured subjectively via patient log‐book records at 12 months (Pandey 2017), or by self‐reported use of medication at 18 months (Truelove 2015).

Mixed educational and behavioural interventions

Mixed educational and behavioural interventions were identified in 27 studies; 19 studies were included in meta‐analyses. Twelve studies used a dichotomous measure of adherence, and meta‐analysis of data from these studies shows that mixed interventions may increase the proportion of adherent patients (Analysis 1.1.3; RR 1.22, 95% CI 1.08 to 1.37; I² = 77%) (Bernsten 2001; Cossette 2015; Khdour 2009; Lopez Cabezas 2006; Naunton 2003; Olesen 2014; Rich 1996; Saez de la Fuente 2011; Vinluan 2015; Wood 1992; Wu 2006; Young 2016). A sensitivity analysis was conducted after removal of two cluster‐RCTs that had potential unit of analysis errors (Bernsten 2001; Wood 1992), but this had little impact on the risk ratio (RR 1.25, 95% CI 1.09 to 1.44). A second sensitivity analysis performed after removal of six studies with high attrition further strengthened the above finding further (RR 1.33, 95% CI 1.20 to 1.49) (Bernsten 2001; Cossette 2015; Lopez Cabezas 2006; Olesen 2014; Vinluan 2015; Wood 1992).

Seven studies used a continuous measure of adherence, and meta‐analysis of data from these studies shows no significant impact on adherence (Analysis 1.2.3; SMD 0.47, 95% CI ‐0.08 to 1.02; I² = 95%) (Begley 1997; Chrischilles 2014; Lee 2006; Lipton 1994; Nazareth 2001; Shively 2013; Williams 2012). A sensitivity analysis after removal of three studies with high attrition did not substantially alter the findings (SMD 0.70, 95% CI ‐0.25 to 1.65) (Lipton 1994; Nazareth 2001; Williams 2012).

Of the eight studies not included in meta‐analyses, two reported a positive impact on adherence with the intervention (Al‐Rashed 2002; Pereles 1996), four reported no differences between intervention and usual care groups (Cargill 1992; Holland 2007; Lim 2004; Taylor 2003), and two did not have clearly reported results (Cohen 2011; Marek 2013). Of the two studies showing positive impact, Al‐Rashed 2002 reported a significantly higher number of medications taken correctly in the intervention group (70% versus 15.8%) and Pereles 1996 reported a significantly lower number of medication errors in the intervention group, as a proportion of total doses administered (P < 0.001).

Overall, mixed interventions may increase the proportion of people who are adherent to medications but may have little or no impact on medication adherence measured via continuous adherence outcomes. Quality of evidence was assessed as low for both outcomes ‐ downgraded (by ‐1) due to high or unclear risk of bias across multiple domains, and (by ‐1) for inconsistency (high I² and variations in interventions, outcome measures, settings, duration, etc.).

In total, 11 of the 27 mixed interventions had a positive impact on adherence. All 11 studies were conducted at the hospital‐community interface (e.g. in hospital, at discharge, post discharge, at outpatient clinics) and involved elements of education/counselling. Five studies involved pharmacist medication review (Khdour 2009; Lee 2006; Lipton 1994; Naunton 2003; Rich 1996), and three involved regimen simplification (Begley 1997; Lipton 1994; Rich 1996). Interventions varied in duration from one‐off (Al‐Rashed 2002; Naunton 2003; Saez de la Fuente 2011), to within three months (Lipton 1994; Pereles 1996; Young 2016), to 6 to 12 months (Begley 1997; Khdour 2009; Lee 2006), to two years (Wu 2006). Duration of the intervention in one study was unclear (Rich 1996). Other behavioural interventions in these studies included blister‐packed DAAs (Lee 2006, and as needed in Naunton 2003), motivational interviewing (Khdour 2009), and use of a medication reminder card (Al‐Rashed 2002).

We identified sufficient mixed intervention studies to conduct three of the planned subgroup analyses.

• Duration of intervention: short (≤ 3 months) versus long (> 3 months). When considered separately by subgroups based on intervention duration, there was no difference in adherence between those receiving interventions of a short duration and those receiving a long duration intervention when measured either as a dichotomous outcome (Analysis 1.3; RR 1.4 versus 1.11; test for subgroup differences P = 0.06; I² = 70.7%) or as a continuous outcome (Analysis 1.4; SMD 0.18 versus 0.70; test for subgroup differences P = 0.39; I² = 0%). Heterogeneity remained high, and it is not possible to state whether intervention duration is a major contributing factor to heterogeneity in effects on adherence.

• Type of outcome measure: objective versus subjective. When considered separately by subgroups based on type of outcome measure, there was no difference in adherence between those studies using an objective measure of adherence and those using a subjective measure of adherence when measured either as a dichotomous outcome (Analysis 1.5; RR 1.13 versus 1.26; test for subgroup differences P = 0.38; I² = 0%) or as a continuous outcome (Analysis 1.6; SMD 0.82 versus 0.21; test for subgroup differences P = 0.39; I² = 0%). Heterogeneity remained high, and it is not possible to state whether type of outcome measure is a major contributing factor to heterogeneity in effects on adherence.

• Health professional delivering the intervention: when considered separately by subgroups based on health professional delivering the intervention, there was no difference in adherence between those interventions delivered by pharmacists, nurses, or two or more health professionals when measured either as a dichotomous outcome (Analysis 1.7; RR 1.21 versus 1.19 versus 1.38; test for subgroup differences P = 0.83; I² = 0%) or as a continuous outcome (Analysis 1.8; SMD 1.38 versus ‐0.13 versus 0.42; test for subgroup differences P = 0.08; I² = 61.4%). Heterogeneity remained high, and it is not possible to state whether the type of health professional delivering the intervention is a major contributing factor to heterogeneity in effects on adherence.

1.3. Analysis.

Comparison 1: Interventions versus usual care, Outcome 3: Primary outcome: adherence, mixed interventions, grouped by intervention duration (dichotomous)

1.4. Analysis.

Comparison 1: Interventions versus usual care, Outcome 4: Primary outcome: adherence, mixed interventions, grouped by intervention duration (continuous)

1.5. Analysis.

Comparison 1: Interventions versus usual care, Outcome 5: Primary outcome: adherence, mixed interventions, grouped by subjective or objective outcome measures (dichotomous)

1.6. Analysis.

Comparison 1: Interventions versus usual care, Outcome 6: Primary outcome: adherence, mixed interventions, grouped by subjective or objective outcome measure (continuous)

1.7. Analysis.

Comparison 1: Interventions versus usual care, Outcome 7: Primary outcome: adherence, mixed interventions, grouped by provider (dichotomous)

1.8. Analysis.

Comparison 1: Interventions versus usual care, Outcome 8: Primary outcome: adherence, mixed interventions, grouped by provider (continuous)

Secondary outcome ‐ medication knowledge

Thirteen studies included a measure of medication knowledge (Table 6). Meta‐analysis was not possible due to large variations in outcome measures and reporting.

3. Secondary outcome ‐ medication knowledge.

Study	Measure of medication knowledge	Outcome
Al‐Rashed 2002	Pharmacist‐delivered questionnaire; percentage scores for correct answers (drug use, dose, dosage interval)	Drug use: 97.4% vs 69.5%; dosage interval: 97.4% vs 86.0%; dose: 98.5% vs 91.5%
Begley 1997	Patients asked about name, purpose, dose, dosage frequency, and side effects. Reported as percentage of correct answers. Accuracy compared to hospital discharge or GP instructions	Group A 70%, Group B 68%, Group C 66% (usual care)
Bernsten 2001	Interview‐based questionnaire calculating percentage correct (looking at 4 areas: indication, number of dosage units taken per dose, number of doses per day, and awareness of potential adverse effects). Higher scores = better knowledge	Mean ± SD change at 18 months: +3.19 ± 15.18 (n = 704) vs +3.16 ± 16.19 (n = 636)
Bond 2007	Patients were asked whether they "knew more about their medicines compared with a year ago" on 5‐point Likert scale. Those who said agree/strongly agree	Trial report: 73% vs 65%
Grymonpre 2001	Knows purpose of prescribed drugs (yes/no), expressed as number and percentage of drugs correct	304/327 (93%) vs 335/373 (90%)
Hanlon 1996	Self‐report knowledge of 'how they took each analysed medication and what the medication was for'; percentage of correct responses	89.4% (n = 86) vs 90.6% (n = 83)
Khdour 2009	COPD knowledge questionnaire (validated) ‐ effectiveness of education in helping persons with COPD. 16 T/F questions, correct response = 1, range 0 to 16, higher score = better knowledge	Median (IQR): 75.0 (32.0) vs 59.3 (33.0)
Lim 2004	Composite knowledge of dose (D), frequency (F), and indication (I), percentage correct	Not reported
Manning 2007	Assessment of knowledge of indication, dosage frequency, and special comments or cautions. 0 (for no correct responses) to 3 (all correct responses)	Mean ± SD: 1.96 ± 0.7561 vs 1.66 ± 0.6851
Messerli 2016	Knowledge of medicines and daily use ‐ phone questionnaire. 58 questions ‐ included assessing knowledge	Not reported
Nazareth 2001	Prescription medicine interview ‐ patient's knowledge of prescribed drugs. Validated self‐report semi‐structured interview (knowledge score is out of 1, with 1 being 'total/highest' knowledge). Mean (SD) out of 1	Mean ± SD: 0.69 ± 0.35 (n = 65) vs 0.68 ± 0.32 (n = 68)
Pereles 1996	"Short medication knowledge questionnaire" = Patients asked to name and describe appearance and purpose of their medication, to describe their regimen and any potential side effects or drug interactions. Percentage of correct responses in each knowledge category	Discharge: name: 69% vs 55%; appearance: 77% vs 66%; times: 80% vs 69%; purpose: 77% vs 72%; side effects: 6% vs 4% Follow‐up: name: 77% vs 68%; appearance: 85% vs 83%; time: 87% vs 78%; purpose: 84% vs 85%; side effects: 5% vs 4%
Taylor 2003	Self‐reports used to assess medication knowledge. Score determined by dividing the number of medications for which a patient reported the correct name, purpose, dose, and frequency by the total number of medications and multiplying by 100	Mean ± SD: 92.6 ± 3.4 vs 42.9 ± 12.8

Outcome results presented as intervention group vs usual care group unless otherwise stated.

COPD: chronic obstructive pulmonary disease.

GP: general practitioner.

IQR: interquartile ratio.

SD: standard deviation.

T/F: true/false.

Educational interventions

Educational interventions were identified in four studies. In Bond 2007, pharmacist‐led medication management review (including assessment of medication appropriateness, adherence, lifestyle, and social support) conducted in the community pharmacy resulted in more patients agreeing that they knew more about their medications compared to what they knew one year ago (intervention 73% versus usual care 65%). Two studies showed no significant impact on medication knowledge, potentially due to the high levels of knowledge reported in both intervention and usual care groups (knowledge of medications was around 90% in all groups in both studies) (Grymonpre 2001; Hanlon 1996). In Grymonpre 2001, home medication histories were obtained by trained staff and were reviewed by pharmacists; pharmacists then sent a letter summarising the information and providing recommendations to the patient's general practitioner. In Hanlon 1996, the intervention involved pharmacist education provided to the participant and medication review at a general medicine clinic before/after physician appointments. One study involving pharmacist medication review and counselling in the pharmacy did not report results (Messerli 2016).

Overall, educational interventions may have little or no impact on medication knowledge (4 studies; low‐quality evidence). We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains including sequence generation, allocation, attrition, and outcome reporting, and (by ‐1) for inconsistency (variations in settings, providers, duration, and outcome measures).

Behavioural interventions

We identified no behavioural interventions that included a measure of medication knowledge.

Mixed educational and behavioural interventions

Mixed educational and behavioural interventions were identified in nine studies. Five studies reported a positive impact on medication knowledge; four reported small to moderate effects (Al‐Rashed 2002; Khdour 2009; Manning 2007; Pereles 1996), and one reported a large effect (mean ± standard deviation (SD) knowledge score/100: intervention 92.6 ± 3.4 versus usual care 42.9 ± 12.8) (Taylor 2003). Two studies used one‐off pre‐discharge education: Al‐Rashed 2002 involved a 30‐minute pharmacist counselling session (focusing on indications, side effects, dose, dosage times, importance of adherence, provision of a medication card etc.), and Manning 2007 involved nurse education via a three‐dimensional (3D) medication discharge education tool, whereby participants could affix a tablet or capsule of each medication onto the tool to assist with tablet identification. Three studies involved follow‐up/monitoring: Pereles 1996 involved a three‐stage self‐administration of medications programme in hospital, Khdour 2009 involved medication review and motivational interviewing conducted four times over nine months in an outpatient clinic or via phone, and Taylor 2003 involved pharmacist education and medication review at scheduled medical clinic visits over 12 months. Three studies reported no impact on medication knowledge ‐ one involving medication review and regimen simplification conducted at home post discharge for 12 months (Begley 1997), one involving medication review and regimen simplification conducted continuously for 18 months in the community pharmacy (Bernsten 2001), and one involving hospital pharmacist medication review with community pharmacist home visit follow‐up 7 to 14 days post discharge (Nazareth 2001). One study did not report any follow‐up results on medication knowledge (Lim 2004).

Overall, mixed interventions may improve medication knowledge but to a variable degree (9 studies; low‐quality evidence). We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains including sequence generation, allocation, and outcome reporting and (by ‐1) for inconsistency (variations in settings, providers, duration, and outcome measures).

Secondary outcome ‐ consumer satisfaction

Thirteen studies included a measure of consumer satisfaction, but only 10 studies measured the outcome in both intervention and control groups (Bernsten 2001;Bond 2007;George 2016;Hanlon 1996;Lopez Cabezas 2006;Manning 2007;Nazareth 2001;Taylor 2003;Volume 2001;Willeboordse 2017). Three studies measured satisfaction in the intervention group only (Holland 2007;Lingler 2016;Naunton 2003). Meta‐analysis was not possible due to large variation in outcome measures (Table 7).

4. Secondary outcome ‐ satisfaction.

Study	Measure of satisfaction	Outcome (intervention vs usual care)
Bernsten 2001	Self‐reported rating of services provided, satisfaction with services, and general opinion of pharmaceutical care. Questionnaire administered by pharmacist. Results presented as percentage who agree/mainly agree	Rating of services as excellent: 73.8% vs 64.6%; satisfaction with services: 93.9% vs > 90%; general opinion: 77% (intervention group only)
Bond 2007	Overall score on 15 positive and negative statements of most recent pharmacy visit (total score 15 to 75, higher scores better)	Median (IQR): 46 (40 to 55) vs 43 (38 to 49)
George 2016	User satisfaction regarding use of the computer programme questionnaire (USUCPQ): an 8‐item measure based on 7‐point Likert score (max score 56, higher scores better)	Mean ± SD total satisfaction: 45.33 ± 7.81 vs 44.68 ± 6.75
Hanlon 1996	Health Care Attitude Questionnaire: 3 questions on pharmacy‐related healthcare satisfaction (directions received, explanation of SES, numbers/types of drugs) based on 5‐point Likert scale (lower scores better)	Mean ± SD total score: 5.2 ± 1.5 vs 5.4 ± 1.7
Holland 2007	Satisfaction questionnaire; usefulness of community pharmacist visits	75 (64%) considered the visits to have been extremely or very useful
Lingler 2016	Acceptability of the intervention using a set of Likert scale questions and eliciting open‐ended comments	88% of caregivers reported intervention topics useful and relevant; 92% reported that the intervention was helpful for managing the patient's treatment plan
Lopez Cabezas 2006	Catalan Health Department satisfaction survey, asking participants about the care and information received and asking them to provide a global scoring (0 to 10)	Mean ± SD 8.9 ± 1.3 vs 8.8 ± 1.5
Manning 2007	Level of satisfaction using 5‐point Likert scale (5 = highest): "How satisfied were you with the form you received from the nurse when she/he was talking to you about your medications?"	Mean ± SD 4.24 ± 0.6986 vs 4.26 ± 0.8768
Naunton 2003	Survey of intervention group only	94% very satisfied; 84% stated information they were given 'helped a great deal'
Nazareth 2001	Validated patient satisfaction questionnaire, each item scored 1 to 4, mean score per item calculated (higher = better)	Mean ± SD 3.4 ± 0.6 (n = 62) vs 3.2 ± 0.6 (n = 61)
Taylor 2003	Mean ± SD number of patients with pharmacy‐related satisfaction (details unclear)	Mean ± SD 81.9 ± 4.8 (n = 33) vs 89.0 ± 6.2 (n = 36)
Volume 2001	Satisfaction with pharmacy services using 34‐item instrument and 7‐point Likert scale (lower scores = better). General satisfaction extracted	Mean ± SD 1.53 ± 0.77 vs 1.62 ± 0.88
Willeboordse 2017	Medication satisfaction questionnaire assessed on a 7‐point Likert scale	B (95% CI): 0.11 (‐0.08 to 0.30) (P = 0.25)

Outcome results presented as intervention group vs usual care group unless otherwise stated.

CI: confidence interval.

IQR: interquartile ratio.

SD: standard deviation.

Educational interventions

Educational interventions were identified in five studies, four of which reported no impact on satisfaction (George 2016;Hanlon 1996;Volume 2001;Willeboordse 2017). Bond 2007, which involved community pharmacists providing consultations on medications, medication adherence, lifestyle, and social support, reported that participants in the intervention group had greater satisfaction compared to those in the usual care group; however, the effect size was small.

In summary, educational interventions may have little or no impact on consumer satisfaction (5 studies; low‐quality evidence). We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains including sequence generation, allocation, incomplete outcome reporting, and other sources of bias and (by ‐1) for inconsistency (variations in settings, providers, duration, and outcome measures).

Behavioural interventions

We identified no behavioural interventions that included a measure of satisfaction.

Mixed educational and behavioural interventions

Mixed educational and behavioural interventions were identified in eight studies. Three studies ‐ Holland 2007; Lingler 2016; Naunton 2003 ‐ measured participant satisfaction only in the intervention group, with satisfaction levels ranging from 64% in Holland 2007 to 94% in Naunton 2003. Five studies measured participant satisfaction in both intervention and usual care groups; between‐group differences were non‐significant in four studies (Bernsten 2001; Lopez Cabezas 2006; Manning 2007; Nazareth 2001), and one study reported slightly higher pharmacy‐related satisfaction in the group receiving usual care (mean 89.0, SD 6.2) compared with the intervention (mean 81.9, SD 4.8); however, the satisfaction measure used was poorly described (Taylor 2003).

Overall, we are uncertain of the effects of mixed interventions on consumer satisfaction (8 studies; very low‐quality evidence). We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains including sequence generation, allocation, and incomplete outcome reporting, (by ‐1) for inconsistency (variations in interventions, settings, providers, duration, and outcome measures), and (by ‐1) due to imprecision (three of eight studies reported satisfaction only in the intervention group).

Secondary outcome ‐ HRQoL

Fourteen studies included a measure of HRQoL (Table 8). Meta‐analysis was not possible due to differences in scales used and differences in reporting of results.

5. Secondary outcome ‐ HRQoL.

Study	Measure	Time point	Outcome
Bernsten 2001	SF‐36	18 months	Change: GH: +0.28 vs ‐0.66, MH: ‐0.80 vs ‐1.34, PF: ‐0.95 vs‐0.68
Bond 2007	SF‐36	12 months	Med (IQR): GH: 52 (35 to 65) vs 50 (35 to 70), MH: 80 (64 to 88) vs 80 (64 to 88), PF: 60 (35 to 80) vs 65 (35 to 85)
	EQ‐5D	12 months	Med (IQR): 0.73 (0.7 to 0.9) vs 0.73 (0.7 to 0.9)
Cohen 2011	VR‐36 (Veterans SF‐36)	6 months	Change: Med (IQR): MH: 0.48 (‐3.37 to 4.32), C: 0.78 (‐2.67 to 4.23), PF: 1.65 (‐5.21 to 1.31), C: ‐1.95 (‐5.21 to 1.31)
Hale 2016	MLHFQ	90 days	Mean ± SD: 62.2 ± 20.6 vs 28.2 ± 22.3
Hanlon 1996	SF‐36	12 months	Mean ± SD: GH: 37.4 ± 1.6 vs 35.2 ± 1.7, MH: 61.1 ± 1.8 vs 60.4 ± 1.8, PF: 44.1 ± 2.0 vs 42.2 ± 2.0
Holland 2007	EQ‐5D, VAS	6 months	Mean ± SD: EQ‐5D: 0.58 ± 0.29 vs 0.52 ± 0.34, VAS: 58.2 ± 19.6 vs 58.6 ± 19.8
	MLHFQ		Mean ± SD: 47.7 ± 26.3 vs 44.5 ± 27.9
Khdour 2009	SGRQ	12 months	Mean (confidence interval): 61.8 (57.9 to 65.6) vs 65.3 (61.0 to 69.6)
Krska 2001	SF‐36	3 months	No significant differences ‐ values not reported
Lopez Cabezas 2006	EQ‐5D (Spanish and Catalan)	12 months	Mean ± SD: 64 ± 15.4 vs 60.6 ± 17.8, subgroup > 70 years: 63.8 ± 15.3 vs 58.4 ± 15.9
Marek 2013	SF‐36	12 months	Comparison 1 ‐ Mean (confidence interval): planner (intervention) vs control (usual care) = PCS: 1.390 (0.816 to 1.963), MCS: 1.686 (0.949 to 2.423)
			Comparison 2 ‐ Mean (confidence interval): MD.2 (intervention 1) vs planner (intervention 2) = PCS: 0.095 (‐0.450 to 0.640), MCS: 0.241 (‐0.459 to 0.940)
Muth 2016	EQ‐5D	12 weeks	Mean ± SD: change: ‐0.6 ± 19.61 vs ‐1.0 ± 13.66
Taylor 2003	SF‐36	12 months	Mean SD: GH: 57.0 ± 19.6 vs 50.1 ± 15.9, MH: 73.1 ± 21.2 vs 72.3 ± 17.1, PF: 68.6 ± 24.0 vs 56.1 ± 27.5
Volume 2001	SF‐36	12 to 13 months	Mean ± SD: MCS: 56.14 ± 8.30 vs 54.55 ± 8.65, PCS: 36.87 ± 11.62 vs 38.39 ± 11.44
Willeboordse 2017	SF‐12	6 months	Regression coefficients adjusted for baseline: PCS: ‐0.06 (‐3.19 to 3.06), MCS: 0.16 (‐2.89 to 3.22)
	EQ‐5D‐3L		Regression coefficients adjusted for baseline: utility: 0.02 (‐0.02 to 0.05), VAS: 2.30 (‐0.16 to 4.76)

Outcome results presented as intervention group vs usual care group unless otherwise stated.

C: control.

EQ‐5D: EuroQoL Group Quality of Life Questionnaire based on 5 dimensions.

GH: general health.

I: intervention.

MH: mental health.

MCS: mental components summary.

MLHFQ: Minnesota Living With Heart Failure Questionnaire (21 items, coded 0 to 5; higher scores indicate adverse impact on life).

PCS: physical components summary.

PF: physical function.

SD: standard deviation.

SF‐36: Short Form‐36 Health Survey.

SGRQ: St. George's Respiratory Questionnaire (76 items, total score 100; higher = better).

VAS: visual analogue scale.

Educational interventions

Educational interventions were identified in six studies (Bond 2007;Hanlon 1996;Krska 2001;Muth 2016;Volume 2001;Willeboordse 2017); none of these had a significant impact on HRQoL.

Overall, educational interventions probably have little or no effect on HRQoL (6 studies; moderate‐quality evidence). We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains.

Behavioural interventions

Behavioural interventions were identified in only one study (Hale 2016). The intervention involved a remotely monitored electronic medication dose administration aid with alerts and follow‐up calls if medications were missed. HRQoL was measured via the MLHFQ, with results showing that the intervention group had worse HRQoL (higher MLHFQ scores) both at baseline and at 90‐day follow‐up compared to the usual care group (baseline: mean ± SD: 43.7 ± 25.9 versus 26.2 ± 23.1; 90 days: mean ± SD: 62.2 ± 20.6 versus 28.2 ± 22.3).

Overall, we are uncertain of the effects of behavioural interventions on HRQoL (1 study; very low‐quality evidence). We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains, (by ‐1) for indirectness (MLHFQ specific to heart failure populations), and (by ‐1) for imprecision (low participant numbers).

Mixed educational and behavioural interventions

Mixed educational and behavioural interventions were identified in seven studies, with six showing no significant impact on HRQoL (Bernsten 2001;Cohen 2011;Holland 2007;Khdour 2009;Lopez Cabezas 2006;Taylor 2003). Marek 2013 showed that nurse education, follow‐up, and weekly nurse‐filled DAAs resulted in improved physical and mental summary scores on Short Form (SF)‐36 at 12 months compared to usual care (mean change: physical 1.390, 95% CI 0.816 to 1.963; mental 1.686, 95% CI 0.949 to 2.423; P < 0.0001).

Overall, mixed interventions may have little or no effect on HRQoL (7 studies; low‐quality evidence). We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains and (by ‐1) for inconsistency (variations in interventions, outcome measures, settings, duration, etc.).

Secondary outcome ‐ adverse clinical health outcomes

Twenty‐eight studies included a measure of adverse clinical health outcomes (Table 9).

6. Secondary outcome ‐ adverse clinical health outcomes.

Study	Time point	ED/Hospital admissions	Mortality	Adverse drug reactions	GP visits
Al‐Rashed 2002	3 months	Patients re‐admitted to hospital: 8/43 v 28/40			Total unplanned visits: 43 (n = 43) vs 59 (n = 40)
Bernsten 2001	18 months	Self‐reported: 35.6% vs 40.4%; n values unclear
Chrischilles 2014	3 months			Self‐reported: 100/802 (12.9%) vs 33/273 (12.2%)
Cossette 2015	30 days	ED visits: 18% (n = 108) vs 20% (n = 95)
Haag 2016	30 days	ED or hospital re‐admission: 2/11 (18%) vs 1/11 (9%)
Hale 2016	90 days	No. participants: ED: 3/11 (27%) vs 6/14 (43%); hospitalisation: 1/11 (9%) vs 7/14 (50%); total no.: ED 4 vs 7, hospital 2 vs 8
Hanlon 1996	12 months			Self‐reported: 30.2% (n = 86) vs 40% (n = 83) (P = 0.19)
Holland 2007	6 months	Total number of ED admissions (not number of participants admitted): 134 (n = 148) vs 112 (n = 143)	30/148 vs 24/143
Khdour 2009	12 months	n = 71 and 72; ED: 40 vs 80, hospital: 26 vs 64; total hospital days: 164 vs 466			Unscheduled: 28 (n = 71) vs 47 (n = 72)
Lim 2004	2 months			Self‐reported and assessed by physician, total ADRs at 2 months: 13 vs 6; residual ADRs from baseline: 4/13 vs 4/8
Lipton 1994	6 months	Total days in hospital: mean ± SD 2.29 ± 5.96, n = 350 vs 2.02 ± 5.83, n = 356
Lopez‐Cabezas 2016	12 months	Patients with re‐admission: 23/70 (32.9%) vs 31/64 (48.4%)	> 70 years subgroup: 7/53 (13.2%) vs 13/50 (26.0%)
Marusic 2013	30 days	Re‐admission or ED: 20/80 (25%) vs 27/80 (33.8%)		? Self‐reported: 24/80 (30%) vs 30/80 (37.5%) (P = 0.315)
Messerli 2016	28 weeks	Self‐reported unplanned GP visit or hospitalisation: total during study: 110 vs 99, n unclear? ‐ 181 vs 191			*
Murray 1993	6 months			Self‐reported side effects, ill effects, or other problems with medication: C1: 2/12, C2: 2/10, Int: 1/9
Muth 2016	12 weeks	Days in hospital: mean ± SD (T1 + T2) ‐ T0 = ‐0.4 ± 0.73 vs ‐0.2 ± 0.69, n unclear
Naunton 2003	90 days	1 or more unplanned re‐admissions: 16/57 (28%) vs 29/64 (45%)	3/57 (5%) vs 5/64 (8%)
Nazareth 2001	6 months	Re‐admissions: 38/136 (27.9%) vs 43/151 (28.4%) Outpatient department: 39/137 vs 40/151	22/137(16.1%) vs 19/151 (12.6%)		76/107 vs 82/116
Olesen 2014	24 months	Unplanned admissions: 77/253 (30%) vs 73/264 (28%)	19/253 (7.5%) vs 14/264 (5%)
Rich 1996	90 days	Re‐admissions: 18/80 (22.5%) vs 22/76 (28.9%)
Saez de la Fuente 2011	50 days	Total re‐admissions: 5 (n = 26) vs 7 (n = 24); ED: 7 (n = 26) vs 9 (n = 24) (note percentages listed in paper do not match n values)	2 (? n = 26) vs 1 (? n = 24)
Shively 2013	6 months	Hospital: mean (SD): 0.21 (0.409) vs 0.32 (0.475) ED: 0.33 (0.478) vs 0.37 (0.489) n = 39 vs 37
Taylor 2003	12 months	Hospital: 2/33 vs 11/36; ED: 4/33 and 6/36
Vinluan 2015	90 days	Hospital admissions: 2/7 vs 2/7	0/7 vs 2/7
Willeboordse 2017	6 months			DRPs: baseline: 4.4 ± 1.9 vs 3.7 ± 1.7 % solved: 20.2 (12.2 to 28.1)
Winland‐Brown 2000	6 months	Hospitalisations G1: 4/16, G2: 3/24, C: 12/21			Physician visits: G1: 1.5/month, G2: 1/month, C: 1/month
Wu 2006	2 years	Med (IQR): n = 219 vs 223 ED visits: 0 (‐1 to 2) vs 0 (‐1 to 2) Hospital visits: 0 (‐1 to 2) vs 1 (‐1 to 2) Days in hospital: 0 (‐4 to 10) vs 3 (‐2 to 17.5)	25/219 vs 38/223
Young 2016	180 days	Hospital: 18/51 (35.3%) vs 20/49 (40.8%); ED visits: 12/51 (23.5%) vs 11/49 (22.4%)

Outcome results presented as intervention group vs usual care group unless otherwise stated.

ADR: adverse drug reaction.

C: control.

C1: control group 1.

C2: control group 2.

DRP: drug‐related problem.

ED: emergency department.

G1: group 1.

G2: group 2.

GP: general practitioner.

Int: intervention.

SD: standard deviation.

Emergency department (ED)/Hospital admissions

ED/Hospital admissions were measured in 23 studies, and 16 studies were included in the meta‐analysis (Analysis 1.9). Four studies reported hospital and ED admissions separately, but only hospital admissions were chosen to be included in the meta‐analysis to avoid duplication of participants in the analysis (Hale 2016;Khdour 2009;Taylor 2003;Young 2016).

1.9. Analysis.

Comparison 1: Interventions versus usual care, Outcome 9: Secondary outcome: ED/Hospital admissions, grouped by type of intervention (dichotomous)

Educational interventions

Educational interventions had no significant impact on admissions (RR 1.02, 95% CI 0.71 to 1.48) (Haag 2016; Marusic 2013; Messerli 2016). One additional study that could not be included in meta‐analysis reported mean number of days in hospital but reported no effect of an educational intervention (Muth 2016).

Overall, educational interventions probably have little or no effect on ED/hospital admissions (RR 1.02, 95% CI 0.71 to 1.48; moderate‐quality evidence). We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains.

Behavioural interventions

Behavioural interventions reduced the risk of admissions (RR 0.21, 95% CI 0.08 to 0.55) (Hale 2016;Winland‐Brown 2000), although overall we are uncertain about the effects of behavioural interventions on admissions because of the very low quality of evidence for this outcome. We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains and (by ‐2) for imprecision (low participant numbers and low numbers of events).

Mixed educational and behavioural interventions

Meta‐analysis of 11 studies shows that mixed interventions reduced the risk of admissions (RR 0.67, 95% CI 0.50 to 0.90); however the level of heterogeneity was high (I² = 73%) (Al‐Rashed 2002;Cossette 2015;Khdour 2009;Lopez Cabezas 2006;Naunton 2003;Nazareth 2001;Olesen 2014;Rich 1996;Taylor 2003;Vinluan 2015;Young 2016).

A further six studies were not included in the meta‐analysis (Bernsten 2001;Holland 2007;Lipton 1994;Saez de la Fuente 2011;Shively 2013;Wu 2006). Two studies had unclear participant numbers (Bernsten 2001;Saez de la Fuente 2011), one reported only total admissions and not the number of participants admitted (Holland 2007), one reported the mean (SD) number of days in hospital (Lipton 1994), one reported mean (SD) admissions (Shively 2013), and one reported median (IQR) hospital visits (Wu 2006). None of these studies reported a difference between intervention and usual care groups for ED/hospital admissions.

Overall, mixed interventions may reduce the number of ED/hospital admissions (RR 0.67, 95% CI 0.50 to 0.90; low‐quality evidence). We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains and (by ‐1) for inconsistency (variations in interventions, outcome measures, settings, duration, and effect estimates across studies).

In total, four out of 23 individual studies had results favouring the intervention ‐ one behavioural ‐ Winland‐Brown 2000 ‐ and three mixed interventions (Al‐Rashed 2002;Khdour 2009;Taylor 2003). Two studies involved pharmacist‐led education and medication review with ‐ Khdour 2009 ‐ or without ‐ Taylor 2003 ‐ motivational interviewing conducted in an outpatient clinic ‐ Khdour 2009 ‐ or a medical clinic ‐ Taylor 2003. One study involved an automated medication dispenser with audible adherence reminders in the participant's home (Winland‐Brown 2000). Another study involved pharmacist pre‐discharge counselling and provision of a medicine reminder card in hospital (Al‐Rashed 2002).

Mortality

Mortality was reported in eight studies, all involving mixed behavioural and educational interventions led by pharmacists. No studies were identified that evaluated the impact of educational or behavioural interventions alone on mortality. Meta‐analysis involving seven studies shows that we are uncertain of the impact of mixed interventions on mortality (Analysis 1.10; RR 0.93, 95% CI 0.67 to 1.30; very low‐quality evidence) (Holland 2007;Lopez Cabezas 2006;Naunton 2003;Nazareth 2001;Olesen 2014;Vinluan 2015;Wu 2006). No individual study had a significant impact on mortality; three appeared to favour the intervention, and four appeared to favour usual care. We excluded one further study the meta‐analysis due to unclear participant numbers (Saez de la Fuente 2011). We downgraded the evidence (by ‐1) due to high or unclear risk of bias across multiple domains, (by ‐1) for inconsistency (variations in interventions, outcome measures, settings, duration, etc.), and (by ‐1) for imprecision (limits of 95% confidence intervals include both potential benefit and potential harm).

1.10. Analysis.

Comparison 1: Interventions versus usual care, Outcome 10: Secondary outcome: mortality, mixed interventions

Adverse drug reactions (ADRs)

Adverse drug reactions (ADRs) were reported in six studies.

Educational interventions

Three studies providing educational interventions included a measure of ADRs; two reported no differences between groups (Hanlon 1996; Marusic 2013), and one found that the percentage of solved medication‐related problems (including ADRs) was significantly higher in the intervention group (regression coefficient 22.6, 95% CI 14.1 to 31.1; P < 0.001) (Willeboordse 2017).

Behavioural interventions

One study providing behavioural interventions was identified but reported no differences between groups in self‐reported ADRs (Murray 1993).

Mixed educational and behavioural interventions

Two studies providing mixed educational and behavioural interventions were identified. One study reported no differences between intervention and usual care groups (Chrischilles 2014), and the other found that total ADRs were higher at two months following an intervention involving education, medication review, and regimen simplification (total 13 versus 6) but that residual ADRs from baseline were lower (4/13 versus 4/8) (Lim 2004).

Physician visits

Physician visits were reported in four studies.

Mixed educational and behavioural interventions

Two studies, both involving mixed educational and behavioural interventions, reported reductions in the number of unplanned physician visits with the intervention over usual care (43 versus 59 total visits and 39% versus 65% of participants, respectively) (Al‐Rashed 2002; Khdour 2009).

Two studies ‐ one behavioural ‐ Winland‐Brown 2000 ‐ and one mixed ‐ Nazareth 2001 ‐ reported no between‐group differences for the number of physician visits.

Secondary outcome ‐ condition‐specific outcomes

Seven studies included a condition‐specific outcome measure (Table 10). Meta‐analysis was not possible due to variations in outcome measures.

7. Secondary outcome ‐ condition‐specific outcomes.

Study	Measure	Outcome
Blalock 2010	Falls (self‐reported) in 12 months (ITT analysis)	≥ 1 fall: 53/93 vs 52/93
Bond 2007	Total score (/8) for reaching targets at 12 months (aspirin, lipid, BP, smoking, alcohol, physical activity, diet, BMI)	4.6 ± 1.2 vs 4.6 ± 1.1
Cohen 2011	Percentage achieving targets at 6 months (SBP < 130, LDL < 100, HbA1c < 7%)	16% (n = 50) vs 4.1% (n = 49)
Lee 2006	Systolic and diastolic blood pressure (mmHg) and LDL‐cholesterol (mg/dL) at 6 months post phase 1	SBP: 124.4 ± 14.0 vs 133.3 ± 21.5 DBP: 67.5 ± 9.9 vs 68.6 ± 10.5 LDL: 87.5 ± 24.2 vs 88.4 ± 21.0
Nascimento 2016	Fasting blood glucose and HbA1c at 6 months	FBG: 117.3 ± 26.8 vs 142.2 ± 32.9 HbA1C: 7.7 ± 0.8 vs 7.99 ± 0.67
Taylor 2003	Number of people reaching goal level at 12 months (BP ≤ 140/90, HbA1c ≤ 7.5%, INR 2 to 3, LDL)	BP: 22 (91.7%) vs 8 (27.6%) Diabetes: 13 (100%) vs 5 (26.7%) INR: 4 (100%) vs 1 (16.7%) LDL: 14 (77.8%) vs 1 (5.9%) (Note: calculated mean across all 4 measures: 92% vs 19%)
Williams 2012	Blood pressure, HbA1c, eGFR, and creatinine levels at 12 months (9 months post intervention)	SBP: mean (CI) ‐6.9 (‐13.8 to 0.02) vs ‐3.0 (‐8.4 to 2.4) HbA1c: med (IQR): 7 (7 to 9) vs 8 (7 to 9) eGFR: med (IQR): 48 (38 to 76) vs 46 (32 to 72) Creatinine: med (IQR): 117 (82 to 144) vs 108 (89 to 171)

Outcome results presented as intervention group vs usual care group unless otherwise stated and presented as mean ± SD unless otherwise stated.

BMI: body mass index.

BP: blood pressure.

DBP: diastolic blood pressure.

eGFR: estimated glomerular filtration rate.

FBG: fasting blood glucose.

HbA1c: glycosylated haemoglobin.

INR: international normalised ratio.

IQR: interquartile ratio.

ITT: intention‐to‐treat.

LDL: low‐density lipoprotein.

SBP: systolic blood pressure.

Educational interventions

Three studies involved educational interventions: Blalock 2010 reported no difference between groups in terms of the number of participants experiencing one or more falls; Bond 2007 found no between‐group differences in the number of participants reaching health targets (total score for eight targets; e.g. physical activity, diet, weight); and Nascimento 2016 reported greater reductions in fasting blood glucose and glycosylated haemoglobin (HbA1c) levels in intervention participants compared with those receiving usual care.

Behavioural interventions

No studies that involved only behavioural interventions were identified.

Mixed educational and behavioural interventions

Four studies involved mixed interventions. Two studies involving multidisciplinary ‐ Cohen 2011 ‐ or pharmacist ‐ Taylor 2003 ‐ education in a medical clinic with follow‐up reported higher numbers of people reaching goal levels for blood pressure, HbA1c, and low‐density lipoprotein (LDL) cholesterol with the intervention over usual care (16% versus 4% and 92% versus 19%, respectively). Two additional studies measured multiple health targets including blood pressure, reporting that although results favoured the intervention, they were not significantly different from those attained with usual care (Lee 2006;Williams 2012).

Secondary outcome ‐ cost‐effectiveness

Four studies ‐ one providing educational intervention ‐ Bond 2007 ‐ and three providing mixed interventions ‐ Bernsten 2001;Lipton 1994;Lopez Cabezas 2006 ‐ included a measure of cost‐effectiveness (see Table 11).

8. Secondary outcome ‐ cost effectiveness.

Study	Measure of costs	Outcome
Bernsten 2001	Direct costs of the study, including additional time spent by pharmacists, costs associated with contacts with other health professionals, costs of hospitalisation and drugs	Average cost per patient (saving): Denmark: 1298.13 vs 1419.88 (+121.75) Germany: 2992.25 vs 3167.25 (+175.00) Northern Ireland: 735.22 vs 750.01 (+14.79) Sweden: 1266.76 vs 1250.34 (‐16.42)
Bond 2007	Total NHS‐related study costs, including costs of intervention and other treatment (e.g. medicines, hospital, other health consultations)	Median cost (IQR): 970.5 (667.0 to 1489.0) vs 835.2 (534.4 to 1396.3) Median (IQR) cost of intervention alone (pharmacist time and training): 90 (60 to 118)
Lipton 1994	Medicare Part B charges, total hospital inpatient charges	Total charges: mean ± SD 2769 ± 4789 vs 2598 ± 3722 Inpatient charges: mean ± SD 5472 ± 10904 vs 5263 ± 11478
Lopez Cabezas 2006	Hospitalisation costs, adding in intervention direct costs, delivered materials and time spent by the pharmacist	Average cost per patient: 997 vs 1575

Outcome results presented as intervention group vs usual care group unless otherwise stated.

IQR: interquartile ratio.

NHS: National Health Service.

SD: standard deviation.

Educational interventions

In one study (Bond 2007), the educational intervention involved a one‐off pharmacist medication review; total National Health Service (NHS)‐related study costs (medicines plus NHS visits plus intervention costs) were higher in the intervention group compared with the usual care group (median 970.5 versus 835.2), although the main difference was the cost of the intervention itself (median 90, IQR 60 to 118).

Mixed interventions

Two mixed interventions involving pharmacist medication review with repeated/continuous follow‐up for 18 months, either in the pharmacy ‐ Bernsten 2001 ‐ or in hospital with home follow‐up ‐ Lopez Cabezas 2006 ‐ reported that the intervention resulted in a reduction in mean/median costs per patient, although cost savings were variable. The third mixed intervention ‐ Lipton 1994 ‐ involving one‐off face‐to‐face medication review and education in hospital with telephone follow‐up post discharge for three months shows that intervention patients had higher Medicare Part B charges and total hospital inpatient charges as measured at six months compared to usual care patients.

Secondary outcome ‐ other

Four studies included other outcome measures potentially related to measures of medication‐taking ability, medication adherence, or adverse drug events (see Table 12).

9. Secondary outcome ‐ other.

Study	Measure	Outcome (Intervention vs usual care)
Chrischilles 2014	Mean (SD) number of medication management problems from a list of 8 problems, including questions on multiple prescribers, multiple pharmacies, mail order prescriptions, confusion whether medication was taken, taking medication without knowing indication, problems affording medications, feeling that medications are not working, and feeling that medications are not doing what they were intended to do	Mean ± SD 1.4 ± 1.4 vs 1.6 ± 1.5
Lingler 2016	Medication deficiency checklist: a 15‐item, investigator‐developed instrument that uses caregiver interviews to assess for the presence of errors and problems (e.g. incorrectly chewing pills or capsules, taking at the wrong time, repeating doses, patient refuses/unco‐operative)	Mean ± SD 2.19 ± 1.52 vs 2.36 ± 1.51
Moral 2015	Average number of medication errors, defined as both patient errors (e.g. omission of dose) and prescriber errors (e.g. dose too high or too low, duplicate therapy) (as reported in Perula de Torres 2014 paper)	Mean 0.429 vs 1.145
Taylor 2013	Number of participants with at least 1 medication misadventure (defined as medication errors, adverse drug events, and/or adverse drug reactions)	2.8% (n = 33) vs 3.0% (n = 36)

Outcome results presented as intervention group vs usual care group unless otherwise stated.

SD: standard deviation.

Behavioural interventions

One study, involving a behavioural intervention comprising motivational interviewing and follow‐up by physicians and nurses, found that the average number of medication errors, defined as both patient errors (e.g. omission of dose) and prescriber errors (e.g. dose too high or too low, duplicate therapy), was significantly lower in the intervention group compared to the usual care group (0.429 vs 1.145; P = 0.047) (Moral 2015).

Mixed interventions

Three studies involving mixed interventions reported no differences between intervention and usual care groups in medication management problems (Chrischilles 2014), medication errors and problems (Lingler 2016), and medication errors and adverse drug events or reactions (Taylor 2003).

COMPARISON 2. Intervention versus intervention

Six studies involved comparison between interventions as part of a three‐arm RCT design (Begley 1997;Cargill 1992;Marek 2013;Murray 1993;Olesen 2014;Winland‐Brown 2000).

Primary outcome ‐ medication‐taking ability

Two studies included measures of medication‐taking ability.

Cargill 1992 compared a mixed intervention versus an educational intervention. In this comparison, both groups received a 20‐minute nurse education session and review of medications (educational intervention); one of the groups also received follow‐up telephone calls (mixed intervention). No difference in medication‐taking behaviour between groups was reported at four to six weeks (score out of 100 read from a graph: mean 84 versus 86).

Begley 1997 compared a mixed intervention involving pharmacist home interview with counselling versus a behavioural intervention of home interview only without counselling (modified usual care). This study reported no difference in dexterity between groups at 12 months (data were not reported).

Primary outcome ‐ adherence

Six studies involved a measure of medication adherence.

Two studies compared two behavioural interventions. In Murray 1993, pill count adherence was slightly higher in the group that received regimen simplification and unit of dose medication packaging than in the group given regimen simplification alone (92.6% versus 82.6%; P = 0.02). In Winland‐Brown 2000, nurse‐filled pillbox DAAs were associated with a higher number of missed pills as measured via pill count than via an automated dispenser with audible adherence reminders (mean 15.1 versus 1.7; P < 0.001); however the time interval is unclear.

Cargill 1992 compared a mixed intervention versus an educational intervention and found no difference in pill count adherence between the group that received nurse teaching with additional telephone follow‐ups versus the group receiving a nurse teaching session without follow‐up (mean 76% versus 74%).

Two studies compared mixed interventions versus behavioural interventions. Begley 1997 found that pharmacist home interview with counselling had slightly greater impact on pill count adherence than the home interview alone (mean ± SD percentage 86 ± 19 versus 75 ± 21). Olesen 2014 measured adherence using different methods in different groups, and thus data are not comparable.

Marek 2013 compared two mixed interventions and found that pill count adherence was similar across both medication dispensing machine and simple medication box groups (98.8% versus 97.4%).

Secondary outcome ‐ medication knowledge

Begley 1997 compared a mixed intervention involving pharmacist home interview with counselling versus a behavioural intervention of home interview only without counselling (modified usual care). This study reported no difference in medication knowledge between groups at 12 months (mean 70% versus 68%), as measured by comparison of patient answers to hospital discharge and general practitioner (GP) instructions regarding medication name, purpose, dose, dosage frequency, and side effects.

Secondary outcome ‐ satisfaction

No studies were identified.

Secondary outcome ‐ HRQoL

Marek 2013 compared two mixed interventions ‐ a medication‐dispensing machine with audio and visual prompts for adherence versus nurse‐filled simple weekly medication boxes. There was no difference in improvement in participant physical or mental summary scores between the two groups as measured via SF‐36 (mean physical 0.095, 95% CI ‐0.450 to 0.640; mean mental 0.241, 95% CI ‐0.459 to 0.940).

Secondary outcome ‐ adverse clinical health outcomes effects

Three studies reported measures of adverse clinical health outcomes.

Two studies compared two behavioural interventions. In Winland‐Brown 2000, hospitalisations (4/16 (25%) versus 3/24 (12.5%) patients) and mean number of physician visits (1.5/month versus 1/month) were higher in the weekly pre‐filled pill box DAA group than in the group using an automated dispenser with audible reminders. In Murray 1993, the main intervention group (regimen simplification and unit of use DAA packages) and the modified usual care group (group C2; regimen simplification without unit of use medication DAA packages) had similar numbers of self‐reported side effects over six months of follow‐up (1/9 versus 2/10).

Olesen 2014 compared a mixed intervention versus a behavioural intervention (electronic reminder device), but study authors were contacted and reported that data on unplanned admissions and mortality were not collected for the electronic reminder device group.

Secondary outcome ‐ condition‐specific outcomes

No studies were identified.

Secondary outcome ‐ cost‐effectiveness

No studies were identified.

Discussion

Summary of main results

Our systematic review identified a range of simple to complex interventions for improving medication‐taking ability and medication adherence in older adults prescribed multiple medications. All included studies evaluated interventions versus usual care.

No studies of educational only or behavioural only interventions for improving medication‐taking ability were identified. We were unable to determine the impact of mixed interventions on medication‐taking ability due to the small number of eligible studies, variations in effects of the interventions across studies, and large variations in design and quality of those studies.

Our findings suggest that interventions with behavioural components alone and mixed educational and behavioural interventions compared with usual care may improve the proportion of people who are adherent to their prescribed medication. However, we are uncertain of the effects of educational only interventions on the proportion of people who are adherent to their prescribed medication.

When adherence is measured as a continuous variable (e.g. percentage of pills taken), our findings suggest that educational only and mixed interventions may have little or no impact on adherence, and we are uncertain of the effects of behavioural only interventions.

These results must be interpreted with a degree of caution, given the variations in intervention design, duration, follow‐up, and risk of bias of included studies, along with the overall low or very low quality rating of evidence for these outcomes.

Within mixed interventions for improving medication adherence, all of the individual studies that had a significant impact on medication adherence (11 out of 27 studies) were conducted at the hospital‐community/primary care interface (e.g. in hospital, at discharge, post discharge, at outpatient clinics). Three formal subgroup analyses performed on studies involving mixed interventions found no significant differences between subgroups based on intervention duration, type of outcome measure, or health provider delivering the intervention. Studies involving behavioural only interventions were too few to enable subgroup analyses.

Several secondary outcomes were evaluated, but heterogeneity and concerns regarding risk of bias limited our ability to draw firm conclusions. Large variations in outcome measures also limited our ability to pool results via meta‐analyses for most secondary outcomes such as medication knowledge and consumer satisfaction, and many secondary outcomes were reported in only a limited number of studies (e.g. condition‐specific outcomes ‐ 7 studies, adverse drug reactions (ADRs) ‐ 6 studies, and cost‐effectiveness of interventions ‐ 4 studies).

Overall, we found that mixed educational and behavioural interventions may improve medication knowledge but to a variable degree across studies. Pooled results suggest that mixed interventions may reduce the number of emergency department (ED)/hospital admissions compared with usual care, although studies unable to be included in the meta‐analysis suggest that the interventions may have little or no effect on these outcomes. Mixed interventions may lead to little or no change in health‐related quality of life (HRQoL), and we are uncertain about effects on mortality, consumer satisfaction, and other secondary outcomes such as ADRs, physician visits, and costs for these interventions.

Educational interventions delivered alone and compared with usual care may have little or no effect on medication knowledge and probably have little or no impact on most secondary outcomes, including HRQoL and ED/ hospital admissions. We are uncertain of the effects of behavioural interventions delivered alone on the above outcomes (HRQoL, ED/hospital admissions, knowledge) and of the effects of educational or behavioural interventions on a range of other secondary outcomes including satisfaction, ADRs, physician visits, and costs. We identified no studies evaluating the effects of educational or behavioural interventions delivered alone on mortality.

Six studies reported a comparison between two interventions as part of a three‐arm randomised controlled trial (RCT) design; however, due to the limited number of studies assessing the same types of interventions and comparisons, we were unable to draw firm conclusions for any primary or secondary outcomes.

Overall completeness and applicability of evidence

Most of the studies included in this review are relatively new, with almost half (24/50) published since 2010. This trend most likely reflects the increasing prevalence of multiple medication use in older adults and increasing efforts to improve medication adherence. In contrast, three of the five interventions evaluating medication‐taking ability were published last century.

Studies from four continents were identified. Most studies were from high‐income countries, and the greatest proportions emanated from the USA (21), the UK (8), and Canada (5). The results of this review may be more applicable to older adults residing in developed countries, mostly Western countries, with only two studies identified in non‐Western countries (one each from China and Singapore).

Although we attempted to pool interventions under three broad categories (educational only, behavioural only, or mixed), a large degree of heterogeneity remained within each category, which impacted both our confidence in, and the potential applicability of, our findings. For example, among the mixed interventions that showed positive effects on medication adherence, interventions varied from one‐off to two years in duration, were delivered by various health professionals face‐to‐face and/or via telephone, and involved one or more behavioural components (e.g. regimen simplification, motivational interviewing, adherence aids, reminder cards). Furthermore, although interventions were primarily compared with usual care, variation in definitions of 'usual care' likely influenced the size of the effect for some interventions. Interventions that were compared to usual care that involved some form of medication counselling, education, or monitoring may have been less likely to impact medication‐taking ability and medication adherence than interventions that were compared to usual care that more closely resembled a pure control (no intervention) group. However, the often poor description of usual care made this difficult to assess. Our review found only a limited number of studies comparing one intervention versus another intervention. Further research assessing this comparison in different ways may help to identify the most clinically effective and cost‐effective interventions, without the potential ethical dilemmas inherent when health‐related interventions are compared to a pure control consisting of minimal or no intervention.

Reporting of medication use was generally poor and inconsistent. This may have resulted in exclusion of potentially eligible studies for which authors did not collect and/or clearly report the number of medications participants were taking. We also noted variation in the types of medications reported across studies, with some reporting only prescription medication, some reporting only regular medication, and some reporting all medications (e.g. regular, when required, prescription, non‐prescription medications). It was also unclear at times whether the interventions targeted all medications taken by participants, and whether assessment of medication‐taking ability or medication adherence applied to all medications or only to a subset. There is a need for clearer reporting of medication use in intervention studies targeting medication‐taking ability or medication adherence.

Reporting of risk factor(s) for poor medication‐taking ability and/or medication adherence was also inconsistent or non‐existent. Common risk factors such as number of medications, frailty, and cognitive impairment were extracted when possible, but subgroup analysis based on such factors was not possible. There is a need for clearer identification and reporting of patient, therapy, condition, system, and environmental factors that influence both medication‐taking ability and medication adherence, and that may be targeted by interventions to improve medication‐taking ability and adherence. Clearer reporting may also highlight and clarify the sometimes inter‐related nature of medication‐taking ability and medication adherence, as many of the interventions described within this review likely targeted aspects of medication‐taking ability (e.g. regimen simplification) in an attempt to improve medication adherence but did not directly measure medication‐taking ability as an outcome.

A limited number of studies evaluated clinical health outcomes, including condition‐specific outcomes and adverse events. Clinical health outcomes should be measured for any intervention that may result in changes in a person's medication intake, including any changes (decrease or increase) in medication adherence. ED and hospital admissions were reported in 23 studies; however, it is often unclear how many were unplanned admissions and/or medication‐related admissions. Only six studies reported the number of participants experiencing ADRs, and four studies reported the number of primary care physician visits, which may be a surrogate for minor to moderate medication‐related problems. Condition‐specific outcomes such as blood pressure or blood glucose were reported in seven studies, meaning the clinical impact of changes in medication‐taking ability or medication adherence was omitted from most studies. Improving clinical outcomes and preventing adverse health outcomes should be the priority of any intervention aimed at improving medication use. This is particularly important among older adults prescribed multiple medications, as this population is at increased risk of adverse events. Evidence of clinical impact and reduction in adverse health outcomes is also necessary to drive translation of research into clinical practice and policy.

Studies that evaluated the cost‐effectiveness of interventions to improve medication‐taking ability or medication adherence are scarce. Future studies should include appropriate measures of cost‐effectiveness of interventions to assist decision‐makers in allocating healthcare resources efficiently.

Quality of the evidence

We evaluated the certainty of the body of evidence using the GRADE approach for the two primary outcomes ‐ medication‐taking ability and medication adherence ‐ and for three key secondary health outcomes ‐ HRQoL, ED/hospital admissions, and mortality. Overall there were serious concerns related to risk of bias and inconsistencies, resulting in low‐ or very low‐quality evidence for most outcomes, except for the effects of educational interventions on HRQoL and ED/hospital admissions, for which evidence was considered of moderate quality.

Most studies had unclear or high risk of bias across multiple domains, particularly related to random sequence generation and allocation concealment. Nearly all studies (98%) also had high risk of performance bias, but we acknowledge that blinding of participants and clinicians (providers of the intervention) is often impossible to achieve in pragmatic health services research. More than half of the included studies were also rated as having unclear or high risk of detection, attrition, and/or reporting biases. Studies were commonly given an ‘unclear’ risk of bias rating due to poorly described methods or results. Future studies should strongly consider prospective registration of the trials in registries, publication of study protocols with detailed methods and description of outcome measures, and more rigorous study methods and reporting.

Serious concerns related to inconsistencies were identified due to the heterogeneous and complex nature of the interventions (components, providers, settings, duration) and variations in outcome measures. Although interventions were broadly grouped as educational, behavioural, or mixed interventions, moderate to high heterogeneity was evident in meta‐analyses and in most cases contributed to our limited certainty in the results.

Concerns related to imprecision were also present for behavioural interventions, for which participant numbers and event rates were often low and/or confidence intervals were wide.

Potential biases in the review process

Differing terminologies for medication‐taking ability and medication adherence may have limited the number of studies found, despite our use of broad search terms and our search of grey literature and the reference lists of included studies. As mentioned previously, poor reporting of medication use may have caused us to miss potentially eligible studies.

Agreements and disagreements with other studies or reviews

Our review is the first to evaluate interventions for improving medication‐taking ability in older adults prescribed multiple medications. Reviews of instruments to assess medication‐taking ability ‐ Elliott 2009 ‐ and self‐efficacy for medication management ‐ Lamarche 2018 ‐ have been published, but no reviews of interventions utilising these instruments have been published to date.

Several reviews have investigated medication adherence, but only four reviews to date have evaluated interventions for improving medication adherence in older people taking multiple medications. Two of these reviews were conducted over a decade ago (George 2008;Williams 2008), and two were published more recently ‐ one focusing on theory‐based interventions only (Patton 2017), and the other including both cross‐sectional analyses of prevalence of medication adherence and clinical trials/systematic reviews of interventions targeting adherence (Zelko 2016). Both Patton 2017 and Zelko 2016 included far fewer intervention studies than are included in our systematic review because of their different inclusion criteria and search strategies. Our findings are consistent with the findings of these four previous reviews, all of which concluded that high‐quality evidence is scarce, and that inconsistencies in methods, interventions, and outcome measures have made it difficult to draw firm conclusions regarding the most effective interventions for improving medication adherence.

Our concerns regarding risk of bias of included studies were also consistent with a previous Cochrane systematic review investigating interventions for enhancing medication adherence (Nieuwlaat 2014), which evaluated all RCTs of interventions to improve adherence with prescribed medications (i.e. not restricted to older adults or multiple medications) and found that only 17 of 182 included studies had the lowest risk of bias for study design features and their primary clinical outcome.

Authors' conclusions

Implications for practice.

Our review highlights a significant gap in the literature regarding high‐quality evidence on the effects of interventions for improving medication‐taking ability and medication adherence in older adults prescribed multiple medications. Low‐quality evidence suggests that healthcare providers might best utilise behavioural interventions alone to improve medication adherence or mixed educational and behavioural interventions to improve medication adherence while reducing the number of ED/hospital admissions. Given that the causes of non‐adherence and medication‐taking errors vary among patients, healthcare providers should aim to tailor interventions to the individual to address their specific medication adherence barriers.

Healthcare providers and policy‐makers may want to consider our findings that interventions initiated at the hospital‐community interface may be most likely to influence medication adherence, although effects were variable. Medication errors and non‐adherence place a significant cost burden on the healthcare system (Cutler 2018), and interventions that are effective in reducing medication errors and non‐adherence are needed to reduce avoidable healthcare costs. However, implementation of complex multi‐faceted interventions may require system‐, policy‐ and/or funding‐related changes, and our review has found that currently evidence related to cost‐effectiveness is insufficient to inform these changes.

Implications for research.

Further well‐designed RCTs are needed to investigate the effects of interventions for improving medication‐taking ability and medication adherence in older adults prescribed multiple medications. Priority should be given to adequately powered trials using validated, objective measures of medication‐taking ability and medication adherence. The effects of interventions on clinical outcomes, particularly adverse medication events, and cost‐effectiveness should be evaluated. Researchers should strongly consider prospective trial registration and publication of protocols using standard reporting checklists such as the Standard Protocol Items: Recommendations for Interventional Trials (An‐Wen 2013). This will help to ensure clearer and more consistent reporting of outcome variables and participant characteristics that may impact medication‐taking ability and medication adherence.

Greater recognition of the complexity of medication‐taking and medication adherence is needed. There remains no 'gold standard' measure of medication‐taking ability or medication adherence, and the two behaviours are sometimes inter‐related and influenced by a range of patient, therapy, condition, system, and environmental factors. Given that reasons for non‐adherence and medication‐taking errors are different among individuals, 'one size fits all' interventions are unlikely to be effective; this may be why many existing studies and reviews have reported that it is difficult to consistently improve medication‐taking and adherence. Future studies should report the specific factors targeted by their interventions and should include as participants patient groups for which those factors are relevant. Mixed methods research that aims to qualitatively understand participant experiences with interventions, as well as barriers to and enablers of these interventions, may also be useful.

History

Protocol first published: Issue 10, 2016
Review first published: Issue 5, 2020

Appendices

Appendix 1. Search strategies

MEDLINE (Ovid SP) search strategy

1. exp aged/

2. ((old or older or aged or senior) adj2 (person? or people or adult? or men or women or patient* or consumer* or carer* or caregiver* or care giver*)).ti,ab,kw.

3. (late life or ag?ing or old age or seniors).ti,ab,kw.

4. (elder* or geriatr* or gerontol* or geropsych* or veteran*).mp.

5. or/1‐4

6. exp Pharmaceutical Preparations/

7. (medication* or medicine? or medicament* or pharmac* or drug? or polypharmac*).ti,ab,kw.

8. exp drug therapy/

9. exp pharmaceutical services/

10. exp therapeutic uses/

11. or/6‐10

12. 5 and 11

13. primary health care/

14. (primary adj2 (care or healthcare)).ti,ab,kw.

15. ambulatory care/

16. ambulatory.ti,ab,kw.

17. exp general practice/

18. general practitioners/

19. gp?.ti,ab,kw.

20. physicians primary care/

21. physicians family/

22. ((general or family) adj practi*).ti,ab,kw.

23. exp ambulatory care facilities/

24. home care services/

25. exp community health services/

26. patient discharge/

27. (hospital adj3 discharge).ti,ab,kw.

28. continuity of patient care/

29. aftercare/

30. (community or home* or domicil* or outreach or out‐reach or postdischarge or post‐discharge or postacute or post‐acute or discharge plan* or aftercare or after care).ti,ab,kw.

31. or/13‐30

32. 12 and 31

33. patient education as topic/

34. ((educat* or instruct* or advis* or advice* or counsel* or teach* or train* or coach* or learn*) and (patient* or client* or consumer* or user* or carer* or caregiver* or care giver*)).mp.

35. exp counseling/

36. information services/

37. drug information services/

38. (inform* adj5 (patient* or client* or consumer* or user* or carer* or caregiver* or care giver*)).ti,ab,kw.

39. reminder systems/

40. drug packaging/

41. drug prescriptions/

42. medication therapy management/

43. ((patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*) and (manag* adj5 (medication* or medicines))).ti,ab,kw.

44. pharmac* care.ti,ab,kw.

45. or/33‐44

46. medication adherence/ or patient compliance/

47. ((medication or treatment) adj (complian* or adheren* or noncomplian* or nonadheren*)).ti,ab,kw.

48. self efficacy/

49. ((patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*) and (competen* or confident or confidence or abilit* or capacit* or skill* or self‐efficacy or cope? or coping or complian* or noncomplian* or adher* or nonadher* or underadheren* or concordan* or nonconcordan* or persisten* or nonpersist*)).ti,ab,kw.

50. ((patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*) adj5 (error* or mistak* or misus* or mismanag*)).ti,ab,kw.

51. (patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*).ti,ab,kw. and medication errors/

52. self‐administration/

53. or/46‐52

54. 32 and (45 or 53)

55. randomized controlled trial.pt.

56. controlled clinical trial.pt.

57. randomized.ab.

58. placebo.ab.

59. clinical trials as topic.sh.

60. randomly.ab.

61. trial.ti.

62. or/55‐61

63. 54 and 62

Cochrane Central Register of Controlled Trials (CENTRAL) (via Ovid)

1. aged:kw

2. ((old or older or aged or senior) near/2 (person* or people or adult* or men or women or patient* or consumer* or carer* or caregiver* or care‐giver*)):ti,ab,kw

3. ("late life" or ag*ing or "old age" or seniors):ti,ab,kw

4. (elder* or geriatri* or gerontol* or geropsych* or veteran*):ti,ab,kw

5. {or 1‐4}

6. [mh "pharmaceutical preparations"]

7. [mh "drug therapy"]

8. [mh "pharmaceutical services"]

9. [mh "therapeutic uses"]

10. (medication* or medicine* or medicament* or pharmac* or drug or drugs or polypharmac*):ti,ab,kw

11. {or 6‐10}

12. 5 and 11

13. ((primary near/2 *care) or primary‐nursing):ti,ab,kw

14. ambulatory:ti,ab,kw

15. (((general or family) next (practi* or physician* or doctor*)) or gp or gps or family‐medicine):ti,ab,kw

16. [mh "ambulatory care facilities"]

17. outpatient‐department:ti,ab,kw

18. [mh "community health services"]

19. ((patient* or hospital*) near/3 discharg*):ti,ab,kw

20. (continu* near/3 care):ti,ab,kw

21. (community or home* or domicil* or outreach or out‐reach or postdischarge or post‐discharge or postacute or post‐acute or discharge‐plan* or aftercare or after‐care):ti,ab,kw

22. {or 13‐21}

23. 12 and 22

24. ((educat* or instruct* or advis* or advice* or counsel* or teach* or train* or coach* or learn*) and (patient* or client* or consumer* or user* or carer* or caregiver* or care‐giver*)):ti,ab,kw

25. counseling:kw

26. information‐services:kw

27. ((medical or drug) next information):ti,ab,kw

28. (inform* near/5 (patient* or client* or consumer* or user* or carer* or caregiver* or care‐giver*)):ti,ab,kw

29. reminder‐system*:ti,ab,kw

30. (drug next (packaging or label*)):ti,ab,kw

31. medication‐therapy‐management:ti,ab,kw

32. ((patient* or client* or consumer* or user* or subject or subjects or carer* or caregiver* or care‐giver*) and (manag* near/5 (medication* or medicine*))):ti,ab,kw

33. pharmac*‐care:ti,ab,kw

34. {or 24‐33}

35. ((medication or treatment) next (complian* or adheren* or noncomplian* or nonadheren*)):ti,ab,kw

36. (self next (efficacy or concept)):ti,ab,kw

37. ((patient* or client* or consumer* or user* or subject or subjects or carer* or caregiver* or care‐giver*) and (competen* or confident or confidence* or abilit* or capacit* or skill* or self‐efficacy or cope* or coping or complian* or noncomplian* or adher* or nonadher* or underadheren* or concordan* or nonconcordan* or persisten* or nonpersist*)):ti,ab,kw

38. ((patient* or client* or consumer* or user* or subject or subjects or carer* or caregiver* or care‐giver*) near/5 (error* or mistak* or misus* or mismanag*)):ti,ab,kw

39. (patient* or client* or consumer* or user* or subject or subjects or carer* or caregiver* or care‐giver*):ti,ab,kw and medication‐error*:kw

40. self‐administ*:ti,ab,kw

41. {or 35‐40}

42. 23 and (34 or 41) in Trials

CINAHL Plus (via EBSCOhost)

Line #	Query
S43	s42
S42	s31 and s41
S41	S32 or S33 or S34 or S35 or S36 or S37 or S38 or S39 or S40
S40	TI (singl* or doubl* or tripl* or trebl*) and TI (blind* or mask*)
S39	AB (singl* or doubl* or tripl* or trebl*) and AB (blind* or mask*)
S38	AB (random* or trial or placebo*) or TI (random* or trial or placebo*)
S37	MH Quantitative Studies
S36	MH Placebos
S35	MH Random Assignment
S34	MH Clinical Trials+
S33	PT Clinical Trial
S32	"randomi?ed controlled trial" or PT randomized controlled trial
S31	s16 and (s24 or s30)
S30	s25 or s26 or s27 or s28 or s29
S29	"self administ*"
S28	(patient* or client* or consumer* or user* or subject* or carer* or caregiver* or "care giver*") and (error* or mistak* or misus* or mismanag* or (inappropriate* N2 prescri*)
S27	((patient* or client* or consumer* or user* or subject* or carer* or caregiver* or "care giver*") and (competen* or confident or confidence or abilit* or capacit* or skill* or "self‐efficacy" or cope* or coping or complian* or noncomplian* or adher* or nonadher* or underadheren* or concordan* or nonconcordan* or persist* or nonpersist*)
S26	"self efficacy"
S25	(patient or medication or treatment) N5 (complian* or adheren* or noncomplian* or nonadheren*)
S24	s17 or s18 or s19 or s20 or s21 or s22 or s23
S23	(patient* or client* or consumer* or user* or subject* or carer* or caregiver* or "care giver*") and (manag* N5 (medication* or medicine*)
S22	reminder* or "drug packaging" or "drug label*" or "pharmac* care"
S21	inform* N5 (patient* or client* or consumer* or user* or carer* or caregiver* or "care giver*")
S20	MW information services
S19	MH counseling
S18	(educat* or instruct* or advis* or advice* or counsel* or teach* or train* or coach* or learn*) and (patient* or client* or consumer* or user* or carer* or caregiver* or "care giver*")
S17	MH patient education+
S16	s5 and s10 and s15
S15	s11 or s12 or s13 or s14
S14	MH continuity of patient care
S13	community or home* or domicil* or outreach or "out‐reach" or "post‐discharge" or "post‐acute" or "patient discharge" or "discharge plan*" or (hospital N3 discharg*) or aftercare or "after care"
S12	((general or family) N1 (practi* or physician* or doctor*)) or "family medicine" or gp or gps
S11	(primary N2 (care or healthcare or nursing)) or ambulatory or "nurse‐managed center*"
S10	s6 or s7 or s8 or s9 or s10
S9	MH "Pharmacy and Pharmacology+"
S8	medication* or medicine* or medicament* or pharmac* or drug* or polypharmac*
S7	MH drug therapy+
S6	MH "miscellaneous drugs and agents+"
S5	s1 or s2 or s3 or s4
S4	MH health services for the aged
S3	"late life" or ag#ing or "old age" or seniors or elder* or geriatr* or gerontol* or geropsych* or veteran*
S2	(old or older or aged or senior) N2 (person* or people or adult* or men or women or patient* or consumer* or carer* or caregiver* or "care giver*")
S1	MH aged+

Embase (via Ovid)

1. exp aged/

2. ((old or older or aged or senior) adj2 (person? or people or adult? or men or women or patient* or consumer* or carer* or caregiver* or care giver*)).ti,ab,kw.

3. (late life or ag?ing or old age or seniors).ti,ab,kw.

4. (elder* or geriatr* or gerontol* or geropsych* or veteran*).mp.

5. or/1‐4

6. exp drug/

7. (medication* or medicine? or medicament* or pharmac* or drug? or polypharmac*).ti,ab,kw.

8. exp drug therapy/

9. pharmacy/

10. exp pharmaceutics/

11. or/6‐10

12. 5 and 11

13. exp primary health care/

14. (primary adj2 (care or healthcare)).ti,ab,kw.

15. exp ambulatory care/

16. ambulatory.ti,ab,kw.

17. general practice/

18. general practitioner/

19. gp?.ti,ab,kw.

20. family medicine/

21. ((general or family) adj practi*).ti,ab,kw.

22. outpatient department/

23. exp home care/

24. exp community care/

25. hospital discharge/

26. (hospital adj3 discharge).ti,ab,kw.

27. aftercare/

28. (community or home* or domicil* or outreach or out‐reach or postdischarge or post‐discharge or postacute or post‐acute or discharge plan* or aftercare or after care).ti,ab,kw.

29. or/13‐28

30. 12 and 29

31. patient education/

32. ((educat* or instruct* or advis* or advice* or counsel* or teach* or train* or coach* or learn*) and (patient* or client* or consumer* or user* or carer* or caregiver* or care giver*)).mp.

33. counseling/ or patient counseling/

34. patient information/ or medical information/

35. drug information/

36. (inform* adj5 (patient* or client* or consumer* or user* or carer* or caregiver* or care giver*)).ti,ab,kw.

37. reminder system/

38. drug packaging/ or drug labeling/

39. medication therapy management/

40. ((patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*) and (manag* adj5 (medication* or medicines))).ti,ab,kw.

41. pharmaceutical care/

42. pharmac* care.ti,ab,kw.

43. or/31‐42

44. medication compliance/ or patient compliance/

45. ((medication or treatment) adj (complian* or adheren* or noncomplian* or nonadheren*)).ti,ab,kw.

46. self concept/

47. ((patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*) and (competen* or confident or confidence or abilit* or capacit* or skill* or self‐efficacy or cope? or coping or complian* or noncomplian* or adher* or nonadher* or underadheren* or concordan* or nonconcordan* or persisten* or nonpersist*)).ti,ab,kw.

48. ((patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*) adj5 (error* or mistak* or misus* or mismanag*)).ti,ab,kw.

49. (patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*).ti,ab,kw. and exp medication error/

50. drug self‐administration/

51. or/44‐50

52. 30 and (43 or 51)

53. randomized controlled trial/

54. controlled clinical trial/

55. single blind procedure/ or double blind procedure/

56. crossover procedure/

57. random*.tw.

58. placebo*.tw.

59. ((singl* or doubl*) adj (blind* or mask*)).tw.

60. (crossover or cross over or factorial* or latin square).tw.

61. (assign* or allocat* or volunteer*).tw.

62. or/53‐61

63. 52 and 62

IPA (via ProQuest)

1. ab,ti((old or older or aged or senior) n/2 (person$1 or people or adult$1 or patient* or consumer* or carer* or caregiver* or “care giver*”))

2. ab,ti(late life or ag$1ing or old age or seniors or elder* or geriatr* or gerontol* or geropsych* or veteran*)

3. 1 or 2

4. su(dosage forms or prescription drugs or drug utilization)

5. ab,ti(medication* or medicine$1 or medicament* or pharmac* or pharmacotherap* or drug$1 or polypharmac*)

6. su(combined therapy or polypharmacy)

7. su(pharmacy services)

8. or/4‐7

9. 3 and 8

10. su(primary care)

11. ab,ti((primary) n/2 (care or healthcare))

12. su(ambulatory care)

13. ab,ti(ambulatory)

14. ab,ti((general or family) n/1 (practi*))

15. ab,ti(gp$1)

16. su(physicians)

17. su(health centers)

18. su(home health care)

19. ab,ti((hospital) n/3 (discharge))

20. su(patient care; continuity)

21. su(after hours service)

22. ab,ti(community or home or domicil* or outreach or out‐reach or postdischarge or post‐discharge or postacute or post‐acute or discharge plan* or aftercare or “after care”)

23. OR/10‐22

24. 9 and 23

25. su(patient education)

26. ab,ti((educat* or instruct* or advis* or advice* or counsel* or teach* or train* or coach* or learn* or remind*) and (patient* or client* or consumer* or user* or carer* or caregiver* or “care giver*”))

27. su(counseling)

28. su(drug information)

29. ab,ti((inform*) n/5 (patient* or client* or consumer* or user* or carer* or caregiver* or “care giver*”))

30. ab,ti((remind*) and (system* or aid* or service* or package* or message* or call*))

31. su(drugs; packaging)

32. su(collaborative drug therapy management)

33. ab,ti((patient* or client* or consumer* or user* or subject$1 or carer* or caregiver* or “care giver*”) and ((manag*) n/5 (medication* or medicine*)))

34. ab,ti(pharmac* care)

35. or/25‐34

36. su(compliance)

37. su(self‐medication)

38. ab,ti((medication or treatment) n/1 (complian* or adheren* or noncomplian* or nonadheren*))

39. ab,ti((patient* or client* or consumer* or user* or subject$1 or carer* or caregiver* or “care giver*”) and (competen* or confident or confidence or abilit* or capacit* or skill* or self‐efficacy or cope$1 or coping or complian* or noncomplian* or adher* or nonadher* or underadheren* or concordan* or nonconcordan* or persisten* or nonpersist*))

40. ab,ti((patient* or client* or consumer* or user* or subject$1 or carer* or caregiver* or “care giver*”) n/5 (error* or mistak* or misus* or mismanag*))

41. ab,ti(patient* or client* or consumer* or user* or subject$1 or carer* or caregiver* or “care giver*”) and su(medication errors)

42. OR/36‐41

43. 24 and (35 or 42)

44. ab,ti(random* or controlled or control or placebo)

45. 43 and 44

PsycINFO (via Ovid)

1. aged.id.

2. ((old or older or aged or senior) adj2 (person? or people or adult? or men or women or patient* or consumer* or carer* or caregiver* or care giver*)).ti,ab,id.

3. (late life or ag?ing or old age or seniors).ti,ab,hw,id.

4. (elder* or geriatric* or gerontolog* or geropsych* or veteran*).mp.

5. ("380" or "390").ag.

6. or/1‐5

7. exp drugs/

8. exp pharmacology/

9. (medication* or medicine? or medicament* or pharmac* or drug? or polypharmac*).ti,ab,hw,id.

10. exp drug therapy/

11. or/7‐10

12. 6 and 11

13. primary health care/

14. (primary adj2 (care or healthcare)).ti,ab,id.

15. exp outpatient treatment/

16. ambulatory.ti,ab,id.

17. family medicine/

18. general practitioners/

19. gp?.ti,ab,id.

20. family physicians/

21. ((general or family) adj practi*).ti,ab,id.

22. home care/

23. exp community services/

24. long term care/

25. aftercare/

26. exp facility discharge/

27. ((patient or hospital) adj3 discharge).ti,ab,hw,id.

28. "continuum of care"/

29. (community or home* or domicil* or outreach or out‐reach or postdischarge or post‐discharge or postacute or post‐acute or discharge plan* or aftercare or after care).ti,ab,hw,id.

30. or/13‐29

31. 12 and 30

32. client education/

33. ((educat* or instruct* or advis* or advice* or counsel* or teach* or train* or coach* or learn*) and (patient* or client* or consumer* or user* or carer* or caregiver* or care giver*)).mp.

34. exp counseling/

35. information services/

36. information/

37. (inform* adj5 (patient* or client* or consumer* or user* or carer* or caregiver* or care giver*)).ti,ab,id.

38. (reminder? or reminder system*).ti,ab,id.

39. warning labels/

40. "prescribing (drugs)"/

41. ((patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*) and (manag* adj5 (medication* or medicines))).ti,ab,hw,id.

42. pharmac* care.ti,ab,id.

43. or/32‐42

44. treatment compliance/

45. ((medication or treatment) adj (complian* or adheren* or noncomplian* or nonadheren*)).ti,ab,id.

46. self efficacy/

47. ((patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*) and (competen* or confident or confidence or abilit* or capacit* or skill* or self‐efficacy or cope? or coping or complian* or noncomplian* or adher* or nonadher* or underadheren* or concordan* or nonconcordan* or persisten* or nonpersist*)).ti,ab,hw,id.

48. ((patient* or client* or consumer* or user* or subject? or carer* or caregiver* or care giver*) and (error* or mistak* or misus* or mismanag*)).ti,ab,hw,id.

49. drug self‐administration/

50. or/44‐49

51. 31 and (43 or 50)

52. random*.ti,ab,hw,id.

53. trial*.ti,ab,hw,id.

54. controlled stud*.ti,ab,hw,id.

55. placebo*.ti,ab,hw,id.

56. ((singl* or doubl* or trebl* or tripl*) and (blind* or mask*)).ti,ab,hw,id.

57. (cross over or crossover or factorial* or latin square).ti,ab,hw,id.

58. (assign* or allocat* or volunteer*).ti,ab,hw,id.

59. treatment effectiveness evaluation/

60. mental health program evaluation/

61. exp experimental design/

62. "2100".md.

63. or/52‐62

64. 51 and 63

Data and analyses

Comparison 1. Interventions versus usual care.

Outcome or subgroup title	No. of studies	No. of participants	Statistical method	Effect size
1.1 Primary outcome: adherence, grouped by types of interventions (dichotomous)	18		Risk Ratio (M‐H, Random, 95% CI)	Subtotals only
1.1.1 Educational interventions	2	182	Risk Ratio (M‐H, Random, 95% CI)	1.66 [1.33, 2.06]
1.1.2 Behavioural interventions	4	528	Risk Ratio (M‐H, Random, 95% CI)	1.22 [1.07, 1.38]
1.1.3 Mixed educational and behavioural interventions	12	3147	Risk Ratio (M‐H, Random, 95% CI)	1.22 [1.08, 1.37]
1.2 Primary outcome: adherence, grouped by types of interventions (continuous)	12		Std. Mean Difference (IV, Random, 95% CI)	Subtotals only
1.2.1 Educational interventions	5	1165	Std. Mean Difference (IV, Random, 95% CI)	0.16 [‐0.12, 0.43]
1.2.3 Mixed educational and behavioural interventions	7	1825	Std. Mean Difference (IV, Random, 95% CI)	0.47 [‐0.08, 1.02]
1.3 Primary outcome: adherence, mixed interventions, grouped by intervention duration (dichotomous)	11		Risk Ratio (M‐H, Random, 95% CI)	Subtotals only
1.3.1 Short duration (≤ 3 months)	6	486	Risk Ratio (M‐H, Random, 95% CI)	1.40 [1.13, 1.74]
1.3.2 Long duration (> 3 months)	5	2505	Risk Ratio (M‐H, Random, 95% CI)	1.11 [0.97, 1.27]
1.4 Primary outcome: adherence, mixed interventions, grouped by intervention duration (continuous)	7		Std. Mean Difference (IV, Random, 95% CI)	Subtotals only
1.4.1 Short duration (≤ 3 months)	3	398	Std. Mean Difference (IV, Random, 95% CI)	0.18 [‐0.52, 0.88]
1.4.2 Long duration (> 3 months)	4	1427	Std. Mean Difference (IV, Random, 95% CI)	0.70 [‐0.25, 1.65]
1.5 Primary outcome: adherence, mixed interventions, grouped by subjective or objective outcome measures (dichotomous)	12		Risk Ratio (M‐H, Random, 95% CI)	Subtotals only
1.5.1 Objective outcome measure	5	762	Risk Ratio (M‐H, Random, 95% CI)	1.13 [0.93, 1.38]
1.5.2 Subjective outcome measure	7	2385	Risk Ratio (M‐H, Random, 95% CI)	1.26 [1.09, 1.46]
1.6 Primary outcome: adherence, mixed interventions, grouped by subjective or objective outcome measure (continuous)	7		Std. Mean Difference (IV, Random, 95% CI)	Subtotals only
1.6.1 Objective outcome measure	3	360	Std. Mean Difference (IV, Random, 95% CI)	0.82 [‐0.49, 2.13]
1.6.2 Subjective outcome measure	4	1465	Std. Mean Difference (IV, Random, 95% CI)	0.21 [‐0.23, 0.66]
1.7 Primary outcome: adherence, mixed interventions, grouped by provider (dichotomous)	12		Risk Ratio (M‐H, Random, 95% CI)	Subtotals only
1.7.1 Provider: pharmacist	8	2672	Risk Ratio (M‐H, Random, 95% CI)	1.21 [1.04, 1.41]
1.7.2 Provider: nurse	2	297	Risk Ratio (M‐H, Random, 95% CI)	1.19 [1.02, 1.38]
1.7.3 Provider: 2 or more health professionals	2	178	Risk Ratio (M‐H, Random, 95% CI)	1.38 [0.88, 2.16]
1.8 Primary outcome: adherence, mixed interventions, grouped by provider (continuous)	6		Std. Mean Difference (IV, Random, 95% CI)	Subtotals only
1.8.1 Provider: pharmacist	2	286	Std. Mean Difference (IV, Random, 95% CI)	1.38 [0.01, 2.75]
1.8.2 Provider: nurse	2	140	Std. Mean Difference (IV, Random, 95% CI)	‐0.13 [‐0.53, 0.27]
1.8.3 Provider: 2 or more health professionals	2	324	Std. Mean Difference (IV, Random, 95% CI)	0.42 [‐0.38, 1.21]
1.9 Secondary outcome: ED/Hospital admissions, grouped by type of intervention (dichotomous)	16		Risk Ratio (M‐H, Random, 95% CI)	Subtotals only
1.9.1 Educational interventions	3	554	Risk Ratio (M‐H, Random, 95% CI)	1.02 [0.71, 1.48]
1.9.2 Behavioural interventions	2	70	Risk Ratio (M‐H, Random, 95% CI)	0.21 [0.08, 0.55]
1.9.3 Mixed educational and behavioural interventions	11	1827	Risk Ratio (M‐H, Random, 95% CI)	0.67 [0.50, 0.90]
1.10 Secondary outcome: mortality, mixed interventions	7	1776	Risk Ratio (M‐H, Random, 95% CI)	0.93 [0.67, 1.30]

Characteristics of studies

Characteristics of included studies [ordered by study ID]

Al‐Rashed 2002.

Study characteristics
Methods	Aim of study: to evaluate whether pharmaceutical counselling pre‐discharge from hospital (in combination with a medication and information discharge summary (MIDS) and a medicine reminder card) can improve a patient’s therapeutic management post discharge and reduce unnecessary visits to the doctor or hospital re‐admission; to investigate whether a pharmaceutical domiciliary visit can reinforce inpatient counselling Study design: RCT (2 inpatient wards: 1 intervention, 1 control) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: UK Setting: hospital discharge Inclusion criteria: > 65 years, prescribed 4 or more regular items, discharged to own home, abbreviated mental score > 7 (/10), first language English, assessed by pharmacist as at risk for problems with prescribed medicines when discharged home Number of participants randomised: 89 (45 intervention, 44 control) Number of participants included in analysis: 83 (43 intervention, 40 control) Age: mean (SD): 80.2 (5.7) years intervention, 81.1 (5.8) years control Gender: female: 36% (n = 16) intervention, 45% (n = 20) control Ethnicity: not specified Number of medications: regular medications at discharge mean (SD): 7.1 (1.8) intervention, 7.1 (2.3) control Frailty/Functional impairment: not specified Cognitive impairment: all participants had abbreviated mental score > 7/10 Co‐morbidities: not specified
Interventions	Group 1 ‐ Pharmaceutical counselling pre‐discharge: approximately 30 minutes pre‐discharge, counselling by clinical ward pharmacist, including indication, side effects, doses, dosage times, and importance of compliance. Counselling conducted regarding medicine reminder card Group 2 ‐ Usual care: nurse went through discharge medication at point of discharge Co‐intervention: both groups received MIDS and medicine reminder card and 14 days of medication. All patients received home visit by pharmacists at 15 to 22 days and were questioned on medication use. Any incorrect information provided to participants was corrected Provider: pharmacist (hospital) Where: hospital (inpatient ward) When and how often: intervention provided once, within 24 hours of discharge Intervention personalised: yes
Outcomes	Timing of outcome assessment: 3 months post discharge Medication adherence (objective) : percentage of total medications with which participants are compliant (compliance considered 85% to 115%), using home medicines stock and refill prescriptions Knowledge about medicines (objective): percentage of correct answers on a pharmacist‐delivered questionnaire (drug use, dose, dosage interval) Adverse clinical health outcomes (objective) : numbers of general practitioner visits and hospital re‐admissions
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: not specified Dropout: before first visit: intervention = 2 (1 died, 1 withdrew), control = 4 (2 died, 1 nursing home, 1 withdrew)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Of the 2 care of the elderly wards, 1 was randomly chosen for study group patients and the other for control group patients. Unclear how this was chosen
Allocation concealment (selection bias)	Unclear risk	Unclear how patients were allocated to wards and if this was affected by the study
Blinding of participants and personnel (performance bias) All outcomes	High risk	Participants and research staff unblinded
Blinding of outcome assessment (detection bias) All outcomes	High risk	Research pharmacist not blinded
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	Excluded/declined patients not reported; 6/89 attrition (6.7%)
Selective reporting (reporting bias)	Low risk	Outcomes listed in methods reported
Other bias	Low risk	None apparent

Begley 1997.

Study characteristics
Methods	Aim of study: to evaluate the influence of domiciliary pharmacist visits on medication management in a sample of elderly people recently discharged from hospital to their own homes Study design: RCT (3 hospitals; unit of allocation: individual) Number of arms/groups: 3
Participants	Description: patient/consumer Geographic location: UK Setting: community (post discharge) Inclusion criteria: ≥ 75 years, ≥ 3 prescribed drugs, ≥ 2 doses/d, under care of participating consultant, consented to participate, discharged to own home Number of participants randomised: 222 (A: 74, B: 75, C: 73) Number of participants included in analysis: 190 (A: 61, B: 63, C: 66) Age: median (range) = A: 84 (75 to 94), B: 81 (75 to 96), C: 82 (76 to 92) Gender: female A: 61%, B: 65%, C: 56% Ethnicity: not specified Number of medications: mean (SD) prescribed: A: 4.6 (1.8), B: 4.8 (1.6), C: 5.5 (1.9); mean (SD) OTC: A: 2.6 (0.7), B: 4.1 (1.4), C: 2.2 (1.8) Frailty/Functional impairment: not specified Cognitive impairment: abbreviated mental test mean (SD): A: 8.4 (1.5), B: 8.8 (1.1), C: 7.9 (1.3) Comorbidities: not specified
Interventions	Group 1 ‐ Domiciliary pharmacy medication management visit: interview consisted of 6 sections: patient information, drug knowledge, patient dexterity, abbreviated mental test, medication management, compliance. Following interview, intervention group (A) received structured counselling on correct use, storage, and compliance (including simplifying regimen, emphasising importance of compliance, positive reinforcement) Group 2‐ Group (B): control, with home interview but no counselling Group 3 ‐ Group (C): control with no home visit (i.e. usual care) Co‐intervention: N/A Provider: pharmacist (investigator) Where: home (post discharge) When and how often: home visits for A and B occurred at baseline, 2 weeks, 1 month, 3 months, and 12 months Intervention personalised: yes ‐ counselling tailored to needs of the patient
Outcomes	Timing of outcome assessment: 12 months Medication adherence (objective): percentage of medications with which participant is compliant using pill count. Researcher counted remaining tablets and measured volume of liquid. To improve reliability and accuracy, patients were asked to retain all used medicine containers for removal by the investigator Medication‐taking ability (objective): dexterity medication management. 5‐task dexterity test (e.g. opening child‐resistant closure) assessed at baseline and at 12 months; 1 point awarded for each successfully completed activity Knowledge about medicines (subjective): drug knowledge. Percentage of correct answers. Patients asked about name, purpose, dose, dosage frequency, and side effects. Accuracy compared to hospital discharge or GP instructions
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: not specified Dropout: 4 withdrew (refused), 28 were lost to follow‐up (7 death, 7 hospitalised, 10 nursing home, 4 moved out of area) For this review, group A vs group C was considered under Comparison 1 ‐ Intervention vs control; group A vs group B was considered under Comparison 2 ‐ Intervention vs intervention
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	High risk	Recruitment staff blinded to identity of groups; allocated patients consecutively to group A, B, or C. No random sequence generation
Allocation concealment (selection bias)	Unclear risk	Allocated sequentially by blinded recruiter
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unable to blind participants; patients knew what they were getting (respondent bias)
Blinding of outcome assessment (detection bias) All outcomes	High risk	Intervention delivered by same pharmacist taking outcome assessment
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	Lost to follow‐up; reported only completed patients; rates seem similar across groups but breakdown of reasons not available for each group
Selective reporting (reporting bias)	High risk	Some outcomes not reported at follow‐up (e.g. dexterity). Unclear whether results for adherence are patient‐reported or pill count; gives only 'difference' ‐ not raw scores for both
Other bias	Low risk	Required sample size achieved (61 per group)

Bernsten 2001.

Study characteristics
Methods	Aim of study: to investigate the impact of a co‐ordinated community pharmacy‐based pharmaceutical care programme for elderly patients on a range of health and economic outcomes Study design: cluster‐RCT with repeated measures (unit of allocation: pharmacy) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: 7 European countries (Denmark, Germany, the Netherlands, Northern Ireland, Portugal, Republic of Ireland, Sweden) Sturgess 2003 paper describes subgroup of Ireland data only Setting: community pharmacy Inclusion criteria: ≥ 65 years; ≥ 4 prescribed medications; oriented with respect to self, time, and place; community dwelling; regular visitors to a recruited pharmacy Exclusion criteria: housebound, resident in a nursing/residential home Number of participants randomised: intervention: 104 pharmacies, 1290 patients; control: 86 pharmacies, 1164 patients; Ireland subgroup: 191 patients (110 vs 81) Number of participants included in analysis: 18 months: 1340 (704 intervention, 636 control); Ireland subgroup: 110 patients (75 vs 35) Age: median (IQR): I: 74 (8); C: 74 (8); Ireland subgroup: mean ± SD 73.1 ± 5.0 vs 74.2 ± 6.3 Gender: female: 57.9% intervention, 57.3% control; Ireland subgroup: female 63.6% vs 61.0% Ethnicity: not specified Number of medications: prescribed medications mean ± SD: intervention: 7.1 ± 2.5, control: 7.0 ± 2.5, Ireland subgroup: 5.87 ± 1.86 vs 6.66 ± 1.99 Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: not specified
Interventions	Group 1 ‐ Structured community pharmaceutical care: intervention pharmacists attended ≥ 1 study day and were given a study manual. Pharmacists assessed participants to identify actual and potential DRPs (e.g. poor compliance, poor knowledge, ADRs, interactions suboptimal) using a structured approach. Pharmacists then formulated an intervention (education, implementing compliance strategies, simplification, etc.) and monitoring plan per patient Group 2: ‐ Usual care: control pharmacist provided normal services Co‐intervention: N/A Provider: pharmacist (community) Where: community pharmacy When and how often: assessment and intervention was a continuous process throughout the 18 months Intervention personalised: personalised intervention and monitoring plan
Outcomes	Timing of outcome assessment: 18 months Medication adherence (subjective): percentage self‐reported compliant. Self‐completed questionnaire using 4‐item, 4‐point Likert scale (forgetting doses, choosing not to take a dose because feeling well, choosing not to take a dose because of perceived non‐benefit, and choosing to take more of a medicine than prescribed because of feeling the need for it) ‐ based on previously validated Morisky scale. Patients compliant if never experienced any aspects of non‐compliance Medication adherence (objective): Ireland subgroup only: refill compliance. Refill compliance rates calculated from patient medication records, percentage of patients compliant Knowledge about medicines (objective): percentage correct knowledge. Interview‐based questionnaire calculating % correctness (looking at 4 areas: indication, number of dosage units taken per dose, number of doses per day, and awareness of potential adverse effects). Higher scores = better knowledge Satisfaction with intervention (subjective): self‐reported by investigator‐administered questionnaire ‐ satisfaction with services and general opinion of pharmaceutical care. % who agree/mainly agree Health‐related quality of life (subjective): SF‐36 (validated) ‐ 8 dimensions Adverse clinical health outcomes (subjective): 1 or more hospitalisations in past 18 months, self‐reported via investigator‐administered questionnaire Cost‐effectiveness (objective): health care‐related resource usage. Direct costs of the study including additional time spent by pharmacists; contacts with GPs, specialists, and nurses; and costs of hospitalisation and medications
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: European Commission (BIOMED 2)‐funded co‐ordination of RCT (+ lots of others for financial/logistic support), Ireland subgroup: Northern Pharmacies Trust, Northern Ireland and European Commission Dropout: at 18 months: 1114 (45%) patients (586 intervention, 528 control) due to unwillingness, illness, moving away, pharmacy withdrawal, and death. Ireland subgroup: withdrew: 41 (15 and 26), illness: 2 (1 and 1), pharmacy withdrew: 30 (15 and 15), patient death: 8 (4 and 4) ICC value unclear, study authors contacted for further information but no response. Thus unit of analysis error exists
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Pharmacies assigned as control or intervention; "where possible control and intervention sites were matched as closely as possible" ‐ limited details Sturgess 2003: restricted randomisation technique to match community pharmacies in similar pairs. Half participating pharmacies, then randomly assigned as intervention sites; other half as control sites. No details on randomisation technique
Allocation concealment (selection bias)	High risk	Pharmacies randomised; participants attended their normal pharmacy. Unclear whether allocation was concealed from pharmacies until after randomisation
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unable to blind; patients and pharmacies aware. Non‐blinding may have influenced service delivery by pharmacists
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Data collection interviews performed, when possible, by a member of staff other than the pharmacist (e.g. pharmacy assistant). Suspect staff would still be aware of allocation
Incomplete outcome data (attrition bias) All outcomes	High risk	Two countries did not complete 18‐month follow‐up (stopped at 6 months); 1 country conducted 18‐month follow up at 24 months. High withdrawal; those who withdrew were older and had poorer QoL Sturgess 2003: large attrition ‐ 191 at baseline, 147 at 6 months, 119 at 12 months, 110 at 18 months
Selective reporting (reporting bias)	Unclear risk	Reported as per methods. However methods did not discuss how to deal with large attrition
Other bias	Unclear risk	Target sample size was 480 per country ‐ not reached. Large variance in follow‐up Recruitment bias (selective recruitment of cluster participants): unclear whether allocation was concealed from pharmacies until after recruitment. Potential for risk of bias as patients with good relationships with pharmacists and knowledge of intervention may have preferentially joined the study

Blalock 2010.

Study characteristics
Methods	Aim of study: to assess effects of a community pharmacy‐based falls prevention programme targeting high‐risk older adults on rates of recurrent falls, recurrent injurious falls, and filling prescriptions for medications that have been associated with increased risk of falls Study design: RCT (1 year look back and 1 year follow‐up after RCT; unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: community pharmacy Inclusion criteria: those at high risk of falling (≥ 65 years, ≥ 1 fall not attributable to syncope within the 1 year preceding, ≥ 4 long‐term prescription medications, ≥ 1 CNS‐active medication) Exclusion criteria: housebound, in long‐term care facility, not able to read and write English, exhibited significant cognitive impairment Number of participants randomised: 186 (93 intervention, 93 control) Number of participants included in analysis: 93 and 93 (ITT), 73 and 113 (as treated) Age: mean (SD): I: 75.5 (7.0) vs C: 74.1 (6.8) Gender: female: 78.5% intervention vs 65.4% control Ethnicity: white: 91.4% intervention vs 86.0% control Number of medications: unclear (inclusion criteria ≥ 4 long‐term prescriptions) Frailty/Functional impairment: use of cane or walker: 37 (39.8%) vs 43 (46.2%) (P = 0.37) Cognitive impairment: not specified Comorbidities: high‐risk conditions (dizziness, diabetes, incontinence, arthritis, Parkinson, stroke): mean (SD): 1.65 ± 1.19 intervention vs 1.58 ± 1.06 control
Interventions	Group 1 ‐ Enhanced pharmacologic care. Invitation to participate in free face‐to‐face medication consultation (~ 45 minutes) with community pharmacy resident. Pharmacist reviewed medications and identified potential problems (emphasis on CNS‐active medications) using structured algorithms. If problem identified and patient interested in making a change, pharmacist contacted physician to seek prescriber approval of the recommended changes Group 2 ‐ Usual care: no medication consultation Co‐intervention: both groups received 2 brochures on prevention of falls Provider: pharmacist (community) Where: local health care centre When and how often: once Intervention personalised: yes, personalised medication review
Outcomes	Timing of outcome assessment: baseline and 12 months Medication adherence (subjective): BMQ (validated), 5‐item regimen screen that assesses how medication is used Condition‐specific outcomes (subjective): 1 or more falls. Calculated using monthly fall calendar; patients recorded each fall "a sudden, accidental change in position where you land on the ground, floor, or an object"
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: National Center for Injury Prevention and Control at the Centers for Disease Control and Prevention Dropout: 20 did not receive intervention, 27 dropped out (17 vs 10), 9 unable to contact (6 vs 3), 5 died (3 vs 2) Further information required: BMQ results (email correspondence with trial author ‐ unsuccessful)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Randomised to either intervention or control ‐ unclear how
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unable to blind; patients knew if they had the intervention
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	No mention of blinding
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	ITT, although no BMQ data, so difficult to assess if/how ITT was done
Selective reporting (reporting bias)	High risk	"BMQ was readministered at 4 monthly intervals, ending 12 months after the baseline assessment" ‐ results not listed. However BMQ listed as a data source ‐ not an outcome in methods
Other bias	Unclear risk	Initial sample size was 262; "interim power analyses were conducted when it became apparent that it would be difficult to reach target sample size" Sample size changed to 95 per group. Sample size based on falls risk

Bond 2007.

Study characteristics
Methods	Aim of study: to test the hypothesis that a comprehensive MEDMAN service would increase the proportion of patients receiving treatment according to the National Service Framework in England and Wales; would improve overall patient health status; and would be cost‐effective Study design: RCT (pharmacy/GP; unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: UK Setting: community pharmacy (+ primary care (GP)) Inclusion criteria: patients registered with GP > 17 years and with CHD (previous MI, angina, CABG, and/or angioplasty); pharmacies (only pharmacies with private consultation area were eligible to participate) Exclusion criteria: illiterate/innumerate, history of alcohol/drug misuse, terminal/serious illness, severe mental illness, unable to provide informed consent or otherwise unsuitable for the trial as determined by GP Number of participants randomised: 1493 (I: 980, C: 513) Number of participants included in analysis: questionnaires analysed: 712 vs 373, clinical records analysed: 868 vs 466 Age: mean ± SD intervention 68.7 ± 9.2 vs control 68.8 ± 9.1 Gender: F: 307 (32.6%) vs 147 (29.4%) Ethnicity: not specified Number of medications: prescribed medications median (IQR) of 738, intervention: 7 (5 to 10) Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: not specified
Interventions	Group 1 ‐ Community Pharmacy Medicines Management (MEDMAN): patients received a study registration card and a letter asking them to visit their nominated pharmacy to initiate service. Initial consultation informed by extracted medical data supplied by researchers. Further consultations provided according to pharmacist‐determined patient need. Consultations included assessments of the following: therapy, medication compliance, lifestyle (e.g. smoking, exercise, diet), and social support (e.g. difficulties collecting prescriptions and opening bottles). Recommendations were recorded on a referral form, which was sent to the GP, who returned annotated copies to pharmacists Group 2 ‐ Usual care from GP and community pharmacy Co‐intervention: N/A Provider: pharmacist (community) Where: community pharmacy When and how often: initial consultation, then as pharmacist‐determined need Intervention personalised: yes ‐ assessment of therapy, compliance, lifestyle, social ‐ and further consultations as needed
Outcomes	Timing of outcome assessment: baseline and 12 months Medication adherence (subjective): 12 statements about medicine‐taking were summated to derive self‐reported compliance score (range 12 to 60). 12‐Item scale extended scope of MARS questionnaire, introduced a time dimension, and rephrased some questions to make them more patient friendly Knowledge about medicines (subjective): patients were asked whether they "knew more about their medicines compared with a year ago" on a 5‐point Likert scale. Dichotomous; those who said agree/strongly agree Satisfaction with intervention (subjective): responses to 15 positive and negative statements regarding their most recent pharmacy visit. Overall score 15 to 75 (higher = better) Health‐related quality of life (subjective): SF‐36 and EuroQoL‐5D Condition‐specific outcomes (objective): patients reaching CHD targets. Total score for patients reaching 8 targets (aspirin, lipid, BP, smoking, alcohol, physical activity, diet, and BMI) Cost‐effectiveness (objective): health economics analysis. Total NHS‐related study cost: NHS resource use based on information extracted from GP‐held records at baseline and at follow‐up. NHS costs included costs of intervention and other treatment (e.g. medicines, hospital, other health consultations)
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: Department of Health for England and Wales, managed by National Pharmaceutical Association, Royal Pharmaceutical Society of Great Britain, Company Chemist Association, and Co‐operative Pharmacy Technical Panel, led by PSNC Dropout: before intervention: 3 died, 49 withdrew (total 52, 39 vs 13); post intervention: 38 vs 9 withdrew, 20 vs 19 died Unpublished data included: full trial report provided by trial authors
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Patients randomised 2:1 (intervention:usual care) independently of research team using a password‐protected computer programme in permuted blocks stratified by practice
Allocation concealment (selection bias)	Low risk	Patients consented before randomisation; randomisation done independent of research team
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not possible to blind participants nor staff to intervention. Pharmacies not told which control patients had nominated their pharmacy
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Audit clerks and researchers conducting statistical analyses were blinded to patient randomisation. Self‐reported data were collected by postal questionnaire
Incomplete outcome data (attrition bias) All outcomes	Low risk	81% and 79% of questionnaires analysed. Intention‐to‐treat, but patients with missing data excluded. Potential selection bias resulting from loss to follow‐up or missing data was tested and adjusted for, using the Heckman selection correction. When evidence of selection bias was found, unbiased effect of the intervention was reported. 98 and 99% of clinical record forms analysed
Selective reporting (reporting bias)	Unclear risk	Krska paper; not as per protocol
Other bias	Unclear risk	Did not reach required sample size. Sample size calculation: 1920 (1280 vs 640)

Cargill 1992.

Study characteristics
Methods	Aim of study: to provide information on identification of patients at highest risk for problems related to medication non‐compliance and problematic behaviours in the home setting and their response to teaching interventions; to optimise medication‐taking compliance of elderly patients by strengthening the home medication administration system; to reinforce the nursing role as facilitator of maximum health status Study design: RCT (unit of allocation: individual) Number of arms/groups: 3
Participants	Description: both patient/consumer and carer Geographic location: USA Setting: outpatient clinic (general medicine servicing Veterans Administration) Inclusion criteria: ≥ 60 years, metropolitan area accessible to home visits Number of participants randomised: 70 Number of participants included in analysis: 70 Age: range 62 to 97 years, mean 72 Gender: not specified Ethnicity: not specified Number of medications: prescription, non‐topical, non‐inhalant, non‐liquid; mean: 7.5 Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: not specified
Interventions	Group 2 ‐ Nurse teaching session: 20‐minute teaching session, including review of medications timed to patient's schedule and any allowed flexibility. A pill cassette was dispensed if feasible for the patient Group 3 ‐ Nurse teaching session and follow‐up phone call: 20‐minute teaching session (as above) plus additional follow‐up telephone call 1 to 2 weeks after visit in which the nurse reviewed the medication regimen verbally with the patient Group 1‐ Usual care Co‐intervention: N/A Provider: nurse Where: home ± phone call (group 3) When and how often: once (+ follow‐up at 1 to 2 weeks in group 3) Intervention personalised: personalised review of medications was timed to patient's schedule; pill cassette was dispensed if feasible
Outcomes	Timing of outcome assessment: baseline, 4 to 6 weeks Medication adherence (objective): pill count percentage compliance. Percentage of pills taken vs those prescribed to be taken using pill count Medication taking ability (objective): behaviour score/100 for congruency between supply of medications on hand and prescribed medications (/40), verbalising correct regimen (/30), maintaining each prescribed med (/20), appropriate use of OTC (/10). Points deducted for sequestering old scripts, using alternative medications inappropriately, or mixing medications together
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: not specified Dropout: N/A
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Not specified
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	No mention of blinding; assume patients and nurses knew allocation to perform intervention
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	No mention of blinding
Incomplete outcome data (attrition bias) All outcomes	Low risk	No mention of attrition
Selective reporting (reporting bias)	Unclear risk	Raw data not reported; only in graph format
Other bias	Low risk	None apparent

Chrischilles 2014.

Study characteristics
Methods	Aim of study: to examine the impact of a personal health record (PHR) on medication use safety among older adults Study design: RCT (single‐centre open‐label parallel group study with unequal randomisation (3:1); unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: patient's home (online) Inclusion criteria: age 65+, used a computer in past month to visit websites or to send/receive email, responded to questionnaire Number of participants randomised: 1163 Number of participants included in analysis: 1075 (802 vs 273) Age: mean ± SD 72.5 ± 6.0 vs 72.0 ± 6.3 Gender: female: 461 (57.5%) vs 150 (54.9%) Ethnicity: non‐Hispanic white: 782 (99%) vs 267 (98.2%) Number of medications: mean ± SD: prescription: 4.1 ± 3.2 vs 4.2 ± 3.2, OTC: 4.1 ± 2.8 vs 4.3 ± 3.1 Frailty/Functional impairment: physical health (SF‐12): 45.9 ± 10.6 vs 46.1 ± 10.3 Cognitive impairment: memory problems: 80 (10%) vs 31 (11.4%) Comorbidities: medical conditions (from list of 19): 3.6 ± 2.3 vs 3.6 ± 2.2
Interventions	Group 1 ‐ Personal Health Records (PHRs): participants sent an invitation to use study PHR for a period of 1 year and a quick‐start guide. Users could enter, view, and print their current and past medicines, allergies, health conditions, and health event tracking over time. PHR also had user‐friendly medication safety messages based on the Assessing Care of Vulnerable Elders project (ALCOVE‐3) medication use quality indicators. PHR displayed a message when a user entered a medication with an associated ALCOVE‐3 safety concern (drug‐drug interactions e.g. warfarin; dosage concerns e.g. acetaminophen; important lab monitoring e.g. loop diuretics; risk awareness e.g. NSAIDs, bleeding; drugs that should be avoided e.g. barbiturates). Three levels of increasing detail ‐ brief alert, summary level, and detailed explanation. Participants who did not log in were sent a reminder letter 3 to 4 weeks after initial invitation Group 2‐ Usual care: no access to study PHR Co‐intervention: N/A Provider: online Where: online (with baseline and follow‐up questionnaires mailed) When and how often: continuous for 1 year at patient discretion Intervention personalised: individual medication‐specific messages
Outcomes	Timing of outcome assessment: baseline and 6 months Medication adherence (subjective): modified Morisky self‐reported adherence. Answers never, rarely, sometimes, often, always (instead of original yes/no). Mailed questionnaire Adverse clinical health outcomes (subjective): experienced medication side effects in past 3 months (yes/no ‐ reported as percentage of participants experiencing side effects) Other (subjective): medication management problems: mean (SD) number of medication management problems. List of 8 problems including questions on multiple prescribers, multiple pharmacies, mail‐order prescriptions, confusion whether medication was taken, taking medication without knowing indication, problems affording medications, feeling that medications are not working, feeling that medications are not doing what they were intended to do
Notes	Trial registration: NCT02012712 Consumer involvement: PHR was developed and refined using participatory design and focus group sessions with older adults, as well as evaluation in a usability laboratory Funding source: Agency for Healthcare Research and Quality grant and National Institutes of Health grant Dropout: 23 before intervention, 65 lost to follow‐up Fidelity: 61.2% attempted to log on to PHR; 55.2% performed some activity with PHR. More than 40% entered at least 1 medication into PHR
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Randomised in a 3:1 ratio using computerised random numbers. Groups comparable
Allocation concealment (selection bias)	Low risk	Notification of study group assignment was sent by mail to all trial participants by an investigator with no clinical involvement in the trial
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded ‐ participants knew allocation
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Mailed questionnaires and online results; no outcome assessors
Incomplete outcome data (attrition bias) All outcomes	Low risk	1075 of 1163 included in analysis; ITT
Selective reporting (reporting bias)	Low risk	Reported as per methods
Other bias	High risk	61.2% attempted to log on to PHR; 55.2% performed some activity with PHR. More than 40% entered at least 1 medication. ‐ so poor fidelity of intervention. Reimbursed for completing baseline and follow‐up questionnaires

Cohen 2011.

Study characteristics
Methods	Aim of study: to assess whether Veterans Affairs Multi‐disciplinary Education and Diabetes Intervention for Cardiac Risk Reduction Extended for 6 Months could improve attainment of target goals for hypertension, hyperglycaemia, hyperlipidaemia, and tobacco use in patients with type 2 diabetes compared to primary care after 6 months of intervention Study design: RCT (1:1 randomisation; unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: medical centre (Veterans Affairs medical centre) Inclusion criteria: veterans with type 2 diabetes HbA1c > 7%, LDL‐C > 100 mg/dL; coronary artery disease LDL > 70 mg/dL, BP > 130/80 in previous 6 months Exclusion criteria: gestational diabetes, unable to attend group sessions, psychiatric instability or organic brain injury that precluded diabetes self‐care Number of participants randomised: 103 Number of participants included in analysis: 99 (50 and 49) Age: mean ± SD I: 69.8 ± 10.7, C: 67.2 ± 9.4 Gender: female: 0% (n = 0) vs 4% (n = 2) Ethnicity: not specified Number of medications: total not available (added means = 4.20 vs 4.15). Hypertension: 2.02 ± 1.09 vs 1.86 vs 1.12, diabetes: 1.38 ± 0.81 vs 1.47 ± 0.82, cholesterol: 0.80 ± 0.49 vs 0.82 vs 0.53 Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: heart failure 16% vs 10.2%, smoker 14% vs 8.2%, stroke 4% vs 4.1%, coronary heart disease 48% vs 46.9%, COPD 14% vs 20.4%, mood disorder 14% vs 14.3%
Interventions	Group 1 ‐ VA MEDIC‐E: 4 weekly group sessions followed by 5 monthly booster group sessions. Each 2‐hour session included 1 hour multi‐disciplinary diabetes‐specific healthy lifestyle education and 1 hour pharmacotherapeutic intervention performed by a clinical pharmacist (diabetes educator). Family/friends encouraged to participate. 90‐minute booster sessions were less structured Group 2 ‐ Usual care (clinic visits with primary care providers; average once every 4 months) Co‐intervention: N/A Provider: weekly multi‐disciplinary (pharmacist, dietician, pharmacist/PT, nurse) + monthly booster clinical pharmacist Where: medical centre room When and how often: 4 once‐weekly + 5 monthly boosters Intervention personalised: sessions were group based; however pharmacist sessions were more informal and allowed for open discussion about each individual's risk factor control, obstacles, solutions
Outcomes	Timing of outcome assessment: baseline and 6 months Medication adherence (objective): medication possession ratios: total days supply of medication received divided by total number of expected medication intake days Health‐related quality of life (subjective): change in VR‐36 (SF‐36 for veterans) Condition‐specific outcomes (objective): achievement of glycaemic and cardiac risk factor goals. Percentage of participants achieving SBP < 130, LDL < 100, A1c < 7%
Notes	Trial registration: NCT00409240 Consumer involvement: not specified Funding source: Sandra A. Daugherty Foundation Dropout: 4 before intervention, 3 died Further information required: total number of medications and complete data regarding medication adherence (email correspondence with trial author ‐ successful, but authors had no further data available)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Assigned in a 1:1 ratio; no details on randomisation method
Allocation concealment (selection bias)	Unclear risk	No details on allocation specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unable to blind participants/personnel; assumed intervention would impact behaviour
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	No mention of blinding
Incomplete outcome data (attrition bias) All outcomes	Low risk	103 randomised, 99 included in analysis; 4 revoked consent (3 vs 1); 3.8% attrition
Selective reporting (reporting bias)	High risk	Raw data missing for adherence. MPR for total medications quoted but total number of medications not reported
Other bias	Low risk	None noted

Cossette 2015.

Study characteristics
Methods	Aim of study: to evaluate the effectiveness of an ED‐based nursing intervention; to report the impact of an intervention on the secondary outcomes of perceived continuity of care, illness perceptions, self‐care capacities, psychological symptoms, and medication adherence Study design: RCT (unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Canada Setting: hospital discharge (emergency department) Inclusion criteria: at risk for ED return because ≥ 1 ED visit in past year, ≥ 6 medications Exclusion criteria: inability to speak French or English, cognitive problems (e.g. dementia), already receiving regular follow‐up (e.g. at a specialised clinic in hospital) Number of participants randomised: 265 (132 vs 133) Number of participants included in analysis: 203 (108 vs 95) Age: mean ± SD: 67.06 ± 10.42 vs 67.33 ± 9.11 Gender: female: 38.9% vs 48.4% Ethnicity: not specified Number of medications: medications on arrival in ED: mean (SD) 9.2 (2.79) vs 9.95 (3.47) Frailty/Functional impairment: not specified Cognitive impairment: cognitive impairment (e.g. dementia) excluded Comorbidities: not specified
Interventions	Group 1 ‐ Nursing ED intervention: 3 encounters: 1 discharge, 2 telephone follow‐ups at 2 to 4 days and 7 to 10 days post discharge. Potential patient concerns assessed by a 19‐item clinical disease management tool (worries about returning home, disease management, treatment management, ADL/iADL, emotions/cognition, informal resources, healthcare system). If patients rated as 'at risk', they received tailored nurse intervention (e.g. teaching, advice, feedback, referring to external resources). Patients could also call the nurse between planned encounters if they had questions or concerns Group 2‐ Usual care + project nurse repeated advice given by bedside nurse that patients should contact regular healthcare resources if needed (e.g. hotlines, GPs, cardiologists) Co‐intervention: N/A Provider: nurse (project nurse: bachelors degree + 5 years experience in clinical cardiac care) Where: face‐to‐face in ED and telephone follow‐up When and how often: 3 times (discharge, 2 to 4 days and 7 to 10 days) Intervention personalised: yes ‐ each person received different package care
Outcomes	Timing of outcome assessment: 30 days post discharge Medication adherence (subjective): Morisky self‐reported medication‐taking scale (validated). Patients indicated whether (1) or not (0) they forgot (item 1), omitted (item 2), were careless (item 3), or stopped their medication when feeling better (item 4). In this study, results were dichotomised as 0 (never miss Rx) vs 1 or more (1 or more missing Rx) Adverse clinical health outcomes (objective): ED revisits. Percentage of participants re‐admitted to emergency department
Notes	Trial registration: ISRCTN88422298 Consumer involvement: not specified Funding source: Fonds de la Recherche Quebec Sante, Quebec Network on Nursing Intervention Research, Montreal Heart Institute Foundation and Research Centre Dropout: 62 (24/38) lost to follow‐up
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Randomisation sequence generated by independent statistician using PROC PLAN procedure
Allocation concealment (selection bias)	Low risk	Statistician provided opaque envelopes containing assignment to project nurse who was blinded until opening envelopes
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unable to blind ‐ patient and nurse unblinded
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Research assistant who collected outcome measure data by telephone was blinded
Incomplete outcome data (attrition bias) All outcomes	High risk	Missing patients ‐ 203/265 reached at time of outcome assessment. Unbalanced losses also 24 (18%) vs 38 (29%)
Selective reporting (reporting bias)	Low risk	Reported as per methods
Other bias	Unclear risk	Trial ceased early due to unlikely achievement of primary outcome. Sample size not reached

George 2016.

Study characteristics
Methods	Aim of study: to examine the efficacy of a web‐based intervention that utilised Bandura's theory of self‐efficacy and targeted dementia family caregivers Study design: RCT (substudy of larger study; unit of allocation: individual) Number of arms/groups: 2
Participants	Description: carer Geographic location: USA Setting: community Inclusion criteria: carer: (a) women ≥ 18 years (b) assisting a community‐dwelling biological or “chosen” earlier‐generation relative by (c) accompanying/providing transportation to a medical appointment of this relative ≥ 1×/year, (d) engaging in ≥ 1 caregiving activities related to prescription drugs: ordering, retrieving, organising, or administering medication, routinely reminding the older adult to take medications, or sharing in decision‐making with care recipient and physician to begin, hold, increase, decrease, or discontinue a medication, and who (e) endorsed a score ≥ 2, “somewhat distressed”, on 2 items of the Family Caregiver. Care recipients (i.e. patients) were required to have a caregiver‐reported diagnosis of dementia Exclusion criteria: care recipients: lifetime‐reported history of (a) schizophrenia, (b) bipolar disorder, (c) suicide attempts, (d) Huntington’s disease, (e) Korsakoff’s disease, (f) multiple sclerosis, (g) HIV, (h) traumatic brain injury, or (i) drug/alcohol dependence Medication Administration Hassles Scale Number of participants randomised: 53 (28 vs 25) Number of participants included in analysis: 35 (18 vs 17) completed programme Age: mean age years ± SD: carers: 53 ± 10.7 vs 53.92 ± 9.05, patients: 83.03 ± 9.12 vs 83.00 ± 6.83 Gender: all carers female (n = 53; 100%), patients: female: 22 (78.6%) vs 19 (76%) Ethnicity: carers: Caucasian: 25 (89.3%) vs 15 (60%), African American: 2 (7.1%) vs 6 (24%), Latina: 0 (0%) vs 1 (4%), multi‐racial: 1 (3.6%) vs 3 (12%) Number of medications: total prescription medications: 7.03 ± 3.47 vs 7.76 ± 3.91 Frailty/Functional impairment: ADL score: 1.29 ± 1.61 vs 0.80 ± 1.15 Cognitive impairment: all had carer‐reported dementia (CRD): 1.46 ± 0.81 vs 1.44 ± 0.79 Comorbidities: total not specified
Interventions	Group 1 ‐ Narrative health education/Narrative online education: participants entering the experimental condition’s website also encountered a still screen shot with 4 clickable content areas. In the centre of the page, they saw a clickable section titled “introduction” ‐ which linked to a video. When participants entered any content area, they saw another screen containing 2 columns ‐ 1 with resources and a single video of an “expert” (pharmacist, nurse, psychologist, or social worker) providing brief supplementary information, the second column titled “story” including brief video episodes, each less than 4 minutes in length, showing ethnically diverse care dyads encountering various medication‐related challenges as the weeks progressed Group 2 ‐ Narrative health education/Didactic online education: still screen shot with 4 clickable content areas. When participants entered any content area, they saw another screen containing 1 column. This column was titled “resources” and contained PDF didactic handouts with information about that content area and a single video of an “expert” (pharmacist, nurse, psychologist, or social worker) providing brief supplementary information Co‐intervention: N/A Provider: online delivery Where: online delivery When and how often: continuous for 1 month Intervention personalised: no
Outcomes	Timing of outcome assessment: baseline and 1 month Medication adherence (subjective) : Morisky medication adherence: 8‐item self‐report by caregiver (caregiver answered questions about care recipient's level of adherence) = Yes/No answers, Yes = 1 indicating non‐adherent behaviour, No = 0 indicating good medication adherence. Higher scores = poorer adherence Satisfaction with intervention (subjective): user satisfaction regarding use of the computer programme questionnaire (USUCPQ): 8‐item measure that assesses user satisfaction with online health‐based interventions. This measure is based on a 7‐point Likert scale (0 = very unsatisfied, 7 = very satisfied). Explores following domains of caregiver satisfaction: (a) convenience, (b) entertainment, (c) how interesting the content was, (d) speed of the modules, (e) usefulness, (f) practicality, (g) tolerability, and (h) how much information was presented. Maximum score = 56
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: Express Scripts Research Award (July 2013) Dropout: 7 and 11 did not complete the programme Unpublished data: full manuscript of thesis. Some data, particularly related to the larger study, are not yet published
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Online random number generator used to evenly divide ID numbers into 2 groups before the study began
Allocation concealment (selection bias)	Low risk	A lab member unaffiliated with the project placed randomly assigned condition types into sealed envelopes with an ID number on the front. Once an individual was determined to be in the dementia group, the envelope with the correct participant number in the group was opened, and the individual was placed in the condition identified inside the envelope
Blinding of participants and personnel (performance bias) All outcomes	Low risk	Project co‐ordinator accessed pre‐intervention survey to determine dementia status; thus random assignment was not blind to project co‐ordinator. Of note, all intervention materials and contact points were pre‐determined, and thus there was no possibility of differing participant assignment based on project co‐ordinator knowledge of the intervention condition. Both groups viewed the same online interface, thus may have been unaware of allocation
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Caregiver self‐reported adherence but likely blinded, so unsure of the impact this would have on outcome assessment
Incomplete outcome data (attrition bias) All outcomes	High risk	High attrition: a third considered non‐completers. No difference in dropout rates between groups. Participants who dropped out were reporting poorer medication management adherence and higher level of overall medication‐related hassles. No significant differences in dropout rates emerged between didactic and narrative vignettes
Selective reporting (reporting bias)	Low risk	Results as per methods
Other bias	High risk	Thesis only ‐ not published in peer‐reviewed journal. Poor fidelity, as 33% did not log on to complete the programme

Grymonpre 2001.

Study characteristics
Methods	Aim of study: to measure the impact of a community‐based geriatric pharmaceutical care model on specific process measures Study design: RCT (unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Canada Setting: primary care clinic (interdisciplinary community health clinic) Inclusion criteria: ≥ 65 years, non‐institutionalised, ≥ 2 medications (prescribed or non‐prescribed) Number of participants randomised: 135 (69 intervention vs 66 control) Number of participants included in analysis:114 (56 vs 58) Age: mean ± SD 76.9 ± 8.4 vs 77.2 ± 8.8 Gender: female: 75% vs 83% Ethnicity: 100% Caucasian Number of medications: prescribed medications mean ± SD 5.9 ± 3.1 vs 6.5 ± 3.4 Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: not specified
Interventions	Group 1 ‐ Geriatric pharmaceutical care model: home medication history (HMH) conducted by trained staff or volunteers using standardised instrument, reviewed by pharmacist to identify and document potential and actual drug‐related issues. Pharmacist letter summarising info and recommendations provided to physician Group 2 ‐ Usual care with home medication history but no pharmacist intervention: HMH was reviewed by pharmacist for any immediate concerns, and those with "life‐threatening" drug‐related problems were required to withdraw Co‐intervention: N/A Provider: pharmacist Where: private office or at home When and how often: once (and then as required) Intervention personalised: yes ‐ depending on nature of drug‐related problems
Outcomes	Timing of outcome assessment: baseline and 6 months Medication adherence (objective): prescription refill adherence: refill adherence was based on provincial prescription claims database; medication percentage adherence by comparing 1 year before and 1 year after intervention date prescription claims database. Percentage adherence = sum of days supply in interval × 100/actual number of days in interval between first and last fills Knowledge about medicines (objective):knowledge of purpose: knows purpose of prescribed drugs (yes/no), expressed per prescribed drug
Notes	Trial registration: not specified Consumer involvement: not specified Funding source: not specified Dropout: 15 withdrew (10 vs 5), 4 died (2 vs 2), 1 NH, 1 unable to contact Fidelity: pharmacist was able to evaluate and make recommendations on 66 of the 69 test patients at baseline
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Computer‐generated randomisation list
Allocation concealment (selection bias)	Low risk	All patients were informed, in a letter, of their allocation
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unable to blind; patients were informed by letter of their allocation
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Home medication history re‐administered at 6 months by blinded, trained volunteers
Incomplete outcome data (attrition bias) All outcomes	High risk	Adherence calculated per drug ‐ although number of drugs does not match up to mean number of prescribed drugs used by patients nor to number of drugs used to assess knowledge
Selective reporting (reporting bias)	Unclear risk	Outcomes specified in methods reported. Specific data comparisons not specified in methods ‐ may have been searching for significant outcomes (e.g. % hoarded, mean hoarded)
Other bias	Low risk	Sample size based on number of drugs ‐ "100 test drugs and 100 control drugs" ‐ reached

Haag 2016.

Study characteristics
Methods	Aim of study: to assess the impact of comprehensive pharmacist‐provided telephonic MTM on care quality in an outpatient care transition programme (CTP) for high‐risk adults aged ≥ 60 years Study design: RCT (unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: outpatient clinic (primary care work group at tertiary care academic medical centre) Inclusion criteria: ≥ 60 years, independent living, enrolled in local care transition programme (CTP). Enrolled in CTP during hospitalisation if in primary care work group, resided within 20 minutes drive, and predicted high risk of health utilisation) Number of participants randomised: 25 Number of participants included in analysis: 22 Age: median (IQR): 81 (78 to 85) intervention vs 86 (79.5 to 87) control Gender: female: 4 (31%) vs 2 (17%) Ethnicity: white: 13 (100%) vs 11 (92%) Number of medications: all medications listed on home medication list (prescription, non‐prescription, and herbal); median (IQR): 17 (12 to 20) intervention vs 15.5 (13 to 18.5) control Frailty/Functional impairment: Elder Risk Assessment Index score: median (IQR) 18 (17 to 20) vs 20 (17.5 to 22.5) Cognitive impairment: dementia excluded Comorbidities: not specified
Interventions	Group 1 ‐ Medication therapy management (MTM): MTM consultation with a pharmacist by telephone 3 to 7 business days after hospital discharge. Intervention complemented existing CTP (care transition programme). Pharmacist completed comprehensive review of all prescription, non‐prescription, and herbal medications to identify, resolve, and prevent DRPs (e.g. PIM, ADEs, prescribing omissions). Recommendations sent via secure messaging function within electronic medical record to CTP provider Group 2 ‐ Usual care ‐ defined as pre‐existing CTP without pharmacist intervention Co‐intervention: pre‐existing CTP programme: home visit by nurse practitioner within 3 business days after discharge. As part of the visit, the nurse practitioner reviewed the patient's medications and made changes as deemed appropriate. Changes were implemented directly or were discussed with the patient's primary care provider, depending on clinical judgement Provider: pharmacist Where: by telephone (phone call to patient's home) When and how often: once, 3 to 7 days after discharge Intervention personalised: yes
Outcomes	Timing of outcome assessment: baseline and 5 weeks (or 30 days) Medication adherence (subjective) : adapted Morisky Medication Adherence Scale (MMAS): self‐reported by questionnaire over phone. 6 yes/no questions ‐ number of no's (no = indicating good adherence behaviour). Validated Adverse clinical health outcomes (objective): ED visits or hospital re‐admissions: re‐admissions assessed by blinded, independent pharmacists
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: Grant # UL1 TR000135 from National Center for Advancing Translational Sciences, NIH, and US DHHS Dropout: 1 withdrew, 2 died
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Study statistician used a random number generator to determine allocation sequence
Allocation concealment (selection bias)	Low risk	Randomisation completed during phone call with study co‐ordinator, who opened a sealed envelope that contained an indication of which group the patient was assigned to
Blinding of participants and personnel (performance bias) All outcomes	High risk	Trial was unblinded (participants and investigators) ‐ but was unable to blind
Blinding of outcome assessment (detection bias) All outcomes	Low risk	All outcomes were assessed while blinded to intervention or usual care group allocations
Incomplete outcome data (attrition bias) All outcomes	Low risk	3 participants lost ‐ balanced across groups
Selective reporting (reporting bias)	Low risk	All outcomes reported, including NS outcomes
Other bias	Unclear risk	2 of the 12 patients who were randomised to the usual care group had participated in MTM in the past 12 months

Hale 2016.

Study characteristics
Methods	Aim of study: to compare the MedSentry remote medication monitoring system vs usual care in older HF adult patients who recently completed an HF telemonitoring programme Study design: RCT of people who had recently completed hospital‐based heart failure telemonitoring (individual allocation) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: community dwelling (hospital telemonitoring into the home) Inclusion criteria: using 3 to 10 different medications daily, no more than 4 specified times each day; able to sort and manage own medications; had a telephone/mobile phone; live in greater Boston area; speak, read, and write English Exclusion criteria: vision or hearing impaired (i.e. unable to hear an alarm), dementia, or other conditions precluding informed consent; awaiting revascularisation, cardiac resynchronisation, or heart transplant; terminal illness Number of participants randomised: 29 (13 vs 16) Number of participants included in analysis: 25 (11 vs 14) Age: mean ± SD = 68.4 ± 11.8 vs 74.4 ± 10.4 Gender: female: 4 (36%) vs 5 (36%) Ethnicity: white: 9 (82%) vs 13 (93%) Number of medications: not specified, but all participants taking min 3 and max 10 different medications/d Frailty/Functional impairment: NYHA functional classification: Class II or higher: 10 (91%) vs 2 (16%) Cognitive impairment: dementia excluded Comorbidities: not specified
Interventions	Group 1 ‐ MedSentry Medication Management System: (1) a remotely monitored electronic device (“device”) that alerts participants when it is time to take their medications, and (2) a monitoring centre with advisors who contact participants and caregivers when medications are not taken. The device is installed in the participant’s home, and data are transmitted to the monitoring centre via the Internet. The device is approximately the size of a small microwave oven. The top of the device consists of a series of small, removable bins arranged in a 7 × 4 configuration (7 days of the week and 4 medication times per day). A lid on the top of each bin detects when a bin is opened. The bottom of each bin is clear plastic. Cameras located under the bins transmit an image of the contents to the monitoring centre. First, the device provides a visual cue (blue lights around a bin) and an audio alarm to alert a participant when it is time to take medication. If a dose is not taken within 30 minutes, an advisor at the monitoring centre calls the participant. After 3 attempts over a 45‐minute time span to contact the participant, a voice message is left and a call is placed to an optional caregiver who has agreed to be contacted and to follow up with the participant. Participants were responsible for refilling the device and communicating medication changes to the monitoring centre Group 2 ‐ Usual care Co‐intervention: N/A Provider: MedSentry device (with telephone calls if non‐adherent to device‐administered medication) Where: home When and how often: continuous ‐ 90 days Intervention personalised: alerts based on individual medication regimens ‐ otherwise no
Outcomes	Timing of outcome assessment: baseline and 90 days Medication adherence (subjective) : Morisky Medication Adherence: 8‐item questionnaire, scored from 0 to 8. 0 = high adherence, 1 to 2 = medium adherence, 3 or more = low adherence Health‐related quality of life (subjective): Minnesota Living With Heart Failure Questionnaire: 21 items that assess the impact of HF and HF treatment. Responses coded from 0 = does not apply to 5 = very much. Higher scores indicate greater impact (worse) Adverse clinical health outcomes (mixed objective/subjective): all‐cause unplanned hospitalisations and ED visits. Electronic medical records and patient questionnaires
Notes	Trial registration: NCT01814696 Consumer involvement: not specified Funding source: Presentcare, Inc. Dropout: 3 (2 vs 1) did not complete enrolment, 1 control withdrew, 1 control was excluded for randomisation error. Adherence measure also had missing participants not described (9 vs 13 baseline, 10 vs 12 follow‐up) Further information required: mean/median number of medications (email correspondence with trial author ‐ unsuccessful)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	No information provided
Allocation concealment (selection bias)	Unclear risk	Patients who agreed to participate were randomised during the screening phone call. No further details were provided
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	No details provided
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	"Missing cases for some comparisons is because of incomplete responses on the closeout questionnaire" 3 did not complete enrolment, 1 withdrew, 1 was excluded for randomisation error
Selective reporting (reporting bias)	Low risk	Appears to present results as planned
Other bias	Unclear risk	"recruitment was slow and the study was ended early before achieving the original goal of 35 participants per study arm"

Hanlon 1996.

Study characteristics
Methods	Aim of study: to evaluate the effects of sustained clinical pharmacist interventions involving elderly outpatients with polypharmacy and their physicians Study design: RCT (unit of allocation: individual) Number of arms/groups: 2
Participants	Description: both patient/consumer and carer Geographic location: USA Setting: primary care clinic (General Medicine Clinic (GMC) at Veterans Affairs Medical Center) Inclusion criteria: ≥ 65, evidence of polypharmacy (≥ 5), received primary care in GMC Exclusion criteria: living in nursing home. Patients with cognitive impairment eligible only if a caregiver was available to be involved Number of participants randomised: 208 Number of participants included in analysis: 172 (88 intervention vs 84 control) Age: mean ± SD: 69.7 ± 3.5 vs 69.9 ± 4.1 Gender: female: 1.9% vs 0% Ethnicity: % white: 79.0 vs 74.8 Number of medications: Veterans Affairs prescribed medications 7.6 ± 2.8 vs 8.2 ± 2.7 Frailty/Functional impairment: not specified Cognitive impairment: percentage of participants: 7.6% vs 12.6% Comorbidities: mean chronic medical conditions: 9.2 ± 3.7 vs 9.0 ± 3.0
Interventions	Group 1 ‐ Sustained clinical pharmacist involvement: usual and clinical pharmacist care. Pharmacist monitored drug therapy outcomes and medication list and identified DRPs before every scheduled GMC visit by reviewing medical records and meeting with patients/caregivers. Pharmacists provided written recommendations to primary physician. After physician visit, pharmacist educated patients regarding any medication changes. Pharmacist also used compliance‐enhancing strategies and written patient education materials to assist compliance. Clinical pharmacist also reviewed with patients and caregivers general principles of safe medicine use in the elderly and the importance of discussing their medications with physicians Group 2 ‐ Usual care (GMC) ‐ clinic nurse reviewing medications before visit, physician/nurse reviewing medications after visit. Clinical pharmacist neither spoke with nor gave advice to control patients or their physicians during the study period. Written drug therapy recommendations for control patients prepared before randomisation were not discussed nor given to the primary physician but were filed for review at the end of the study Co‐intervention: N/A Provider: pharmacist Where: medical centre When and how often: before/after GMC visits Intervention personalised: yes
Outcomes	Timing of outcome assessment: baseline and 12 months Medication adherence (subjective) : self‐reported compliance: proportion of medications for which patients' adherence response agreed with directions for their use on their action profile, obtained during telephone interviews Knowledge about medicines (subjective): self‐report knowledge of 'how they took each analysed medication and what the medication was for', proportion of correct responses Satisfaction with intervention (subjective): Health Care Attitude Questionnaire: 5‐point Likert scales to rate 3 questions on pharmacy‐related healthcare satisfaction: (1) directions received for taking medication, (2) explanation of SEs, (3) numbers and types of drugs they were taking Health‐related quality of life (subjective): assessed via SF‐36 by blinded interviewers Adverse clinical health outcomes (subjective): patients asked if they had or had not had any possible ADEs (side effects, unwanted reactions, or other problems with medications)
Notes	Trial registration: not specified Consumer involvement: not specified Funding source: National Institute on Aging grant and academic award; supported by Claude D. Pepper Older Americans Independence Center Dropout: lost to follow‐up 36 (17 vs 19)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Not specified
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Outcomes assessed by a separate blinded clinical pharmacist
Incomplete outcome data (attrition bias) All outcomes	High risk	Lost to follow‐up (19%). Methods state ITT but not done for adherence outcomes?
Selective reporting (reporting bias)	Low risk	Appears to be as per methods
Other bias	Unclear risk	Physicians not randomised; potential to be differentially influenced. Sample size 100 per group "to detect an effect of 0.4" or 84 per group "to detect an effect size of 0.5"

Holland 2007.

Study characteristics
Methods	Aim of study: to test whether a drug review and symptom self‐management and lifestyle advice intervention by community pharmacists could reduce hospital admissions or mortality in heart failure patients Study design: RCT (unit of allocation: individual stratified) Number of arms/groups: 2
Participants	Description: both patient/consumer and carer Geographic location: UK Setting: community pharmacy (after discharge from hospital) Inclusion criteria: > 18 years, admitted as an emergency in which HF was an important ongoing clinical condition, prescribed ≥ 2 medications on discharge Exclusion criteria: residential or nursing home, awaiting surgery for heart disease/transplant, had terminal malignancy Number of participants randomised: 339 (169 intervention vs 170 control) Number of participants included in analysis: 291 (148 vs 143) Age: mean ± SD: 77.6 ± 9.0 vs 76.4 ± 9.5 Gender: female: 54 (36.2%) vs 53 (36.7%) Ethnicity: not specified Number of medications: number of prescribed items taken daily: mean ± SD 7.9 ± 2.6 vs 7.7 ± 2.3 Frailty/Functional impairment: not specified Cognitive impairment: abbreviated mental test: 9.2 ± 1.0 vs 9.3 ± 1.0 Comorbidities: not specified
Interventions	Group 1 ‐ HeartMed (visits from community pharmacist): community pharmacist received discharge letter and arranged home visit within 2 weeks of discharge to meet with patient or carer. As appropriate, educated about heart failure, drugs, exercise, diet, smoking; provided signs and symptoms daily cards; removed discontinued drugs; fed recommendations back to GP. Intervention delivered in line with advice from British Heart Foundation's booklet "Living With Heart Failure", which was also given to the patient. A follow‐up visit occurred at 6 to 8 weeks to reinforce Group 2 ‐ Usual care Co‐intervention: N/A Provider: pharmacist (community) Where: patient's home When and how often: twice ‐ at 2 weeks and at 6 to 8 weeks post discharge Intervention personalised: yes
Outcomes	Timing of outcome assessment: baseline and 6 months Medication adherence (subjective) : Medication Adherence Report Scale (MARS) scores from 5 (very poor adherence) to 25 (perfect adherence). Questionnaires mailed to patients Satisfaction with intervention (subjective): satisfaction questionnaire at 3 months Health‐related quality of life (subjective): EQ‐5D ‐ self‐assessed quality of life: 1 (perfect health) to ‐0.59 (worst imaginable health state) Adverse clinical health outcomes (objective): mortality ‐ number of deaths Adverse clinical health outcomes (objective): emergency admissions ‐ emergency admission data from Hospital Episode Statistics Condition‐specific outcomes (subjective): Minnesota Living With Heart Failure Questionnaire: 21 questions of 0 to 5 giving total score from 0 to 105. Higher scores implying worse condition. Change of 5 points is significant
Notes	Trial registration: ISRCTN59427925 Consumer involvement: not specified Funding source: British Heart Foundation project grant; Great Yarmouth and Southern Norfolk Primary Care Trusts covered excess treatment costs. Pfizer supported pharmacist training Dropout: 46 (20 vs 26) excluded before intervention, 2 (1 vs 1) lost to follow‐up Fidelity: of 149 intervention patients ‐ 136 received first visit, 119 received second visit, 13 did not receive intervention
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Third party telephone randomisation based on a computer‐generated random allocation sequence. Stratified by New York Heart Association class and recruitment site
Allocation concealment (selection bias)	Unclear risk	Participants told allocation after baseline; concealment unclear
Blinding of participants and personnel (performance bias) All outcomes	High risk	No placebo possible, so participants were told which group they were in
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Not specified
Incomplete outcome data (attrition bias) All outcomes	High risk	High rate of failure to complete 6‐month assessments (only 101/169 intervention and 103/170)
Selective reporting (reporting bias)	Low risk	As per methods
Other bias	Unclear risk	Pharmacist training funded by Pfizer ‐ unclear what, if any, influence Pfizer had on content of training. Of 149 intervention patients ‐ 136 received first visit, 119 received second visit, 13 did not receive intervention

Khdour 2009.

Study characteristics
Methods	Aim of study: to investigate the impact of a pharmacy‐led disease and medicine management programme (with a strong focus on self‐management) in patients with COPD on clinical and humanistic outcomes Study design: RCT (1 clinic; allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Ireland Setting: outpatient clinic (COPD hospital clinic) Inclusion criteria: confirmed diagnosis of COPD by hospital consultant for ≥ 1 year, FEV1 of 30% to 80% of predicted normal value, > 45 years old Exclusion criteria: CHF, moderate to severe learning difficulties (judged by hospital consultant), attended pulmonary rehab programme in last 6 months, severe mobility problems, terminal illness Number of participants randomised: 173 (86 vs 87) Number of participants included in analysis: 143 (71 vs 72) Age: mean ± SD: 65.63 ± 10.1 intervention vs 67.3 ± 9.2 control Gender: female: 55.8% vs 56.3% Ethnicity: not specified Number of medications: combined prescription and non‐prescription: 8.3 ± 2.9 vs 8.0 ± 3.8 Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: comorbid conditions: n = 41 (47.7%) vs n = 44 (50.5%)
Interventions	Group 1 ‐ Pharmacy‐led COPD disease and medicine management programme: preliminary assessment with pharmacist to determine individual needs (data on disease knowledge, smoking, medication adherence, self‐efficacy, exercise, and diet). Intervention pharmacist then discussed drug therapy with consultant and provided education (adherence, inhaler technique, home exercises, management of COPD symptoms). Pharmacist demonstrated techniques and then observed patients carrying out the techniques (a booklet on these techniques was given to take home). Pharmacist provided advice using motivational interviewing technique (e.g. quit smoking) and provided customisable action plan for exacerbations (include advice to GPs about antibiotics). Initial intervention lasted for approximately 1 hour (slightly longer for smokers) Group 2 ‐ Usual care (medical and nursing staff only ‐ no pharmacist involvement) Co‐intervention: N/A Provider: pharmacist Where: outpatient clinic When and how often: baseline and 6 months in person, phone call at 3 and 9 months Intervention personalised: yes ‐ tailored according to preliminary assessment
Outcomes	Timing of outcome assessment: baseline and 12 months Medication adherence (subjective) : Morisky Adherence (measures adherence with 4 Yes/No response items: forgetting, carelessness, stopping when feeling better, and stopping when feeling worse); yes = 1, no = 0; high adherence (score 0 to 1) vs low adherence (score 2 to 4) Knowledge about medicines (objective): COPD knowledge questionnaire (validated) ‐ effectiveness of education in helping persons with COPD. 16 T/F questions, correct response = 1, range 0 to 16, higher score = better knowledge Health‐related quality of life (subjective): St George's Respiratory Questionnaire (SGRQ) total score = SGRQ is a 76‐item supervised self‐administered survey; scores for symptoms, activity, and impact to give global view of respiratory health. Scores 0 to 100; high = poor health Adverse clinical health outcomes (objective): ED visits, hospital admissions, and unscheduled GP visits, assessed via questionnaire and computer records for past year
Notes	Trial registration: not specified Consumer involvement: not specified Funding source: Chest Heart and Stroke (N Ireland) financial support Dropout: 13 (7 vs 6) withdrew, 8 died (3 vs 5), 9 were lost to follow‐up (5 vs 4)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Randomisation carried out via the minimisation method (see reference). Groups matched as closely as possible
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Participants and research staff unblinded
Blinding of outcome assessment (detection bias) All outcomes	High risk	Research pharmacist not blinded
Incomplete outcome data (attrition bias) All outcomes	Low risk	Loss to follow‐up described and balanced
Selective reporting (reporting bias)	Low risk	Reported results for all outcome measures listed in methods section
Other bias	Unclear risk	Sample size based on SQRG ‐ aimed for 180 patients (90 vs 90) ‐ not reached

Krska 2001.

Study characteristics
Methods	Aim of study: to evaluate the effects of pharmacist‐led medication review on outcomes such as presence of pharmaceutical care issues (PCIs), hospitalisation, medication costs, and HRQoL Study design: RCT (6 general medical clinics; individual patients randomised) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Scotland Setting: primary care clinic (general medical practices) Inclusion criteria: ≥ 65 years, ≥ 4 medications (via computerised repeat prescribing system), ≥ 2 chronic conditions (Note: a maximum of 70 patients from each practice were invited to participate) Exclusion criteria: dementia, GP considered patient unable to cope with study Number of participants randomised: 381 Number of participants included in analysis: 332 (168 and 164) Age: mean ± SD (range): 74.8 ± 6.2 (65 to 90) intervention vs 75.2 ± 6.6 (65 to 93) control Gender: female: 95 (56.5%) vs 106 (64.6%) Ethnicity: not specified Number of medications: medications actually being taken (prescription and non‐prescription): mean ± SD (range) 7.3 ± 2.7 (3 to 16) vs 7.6 ± 2.7 (3 to 17) Frailty/Functional impairment: not specified Cognitive impairment: dementia excluded Comorbidities: chronic diseases: 3.9 ± 1.4 (2 to 8) vs 3.8 ± 1.4 (2 to 9)
Interventions	Group 1 ‐ Pharmacist medication review and pharmaceutical care planning: pharmaceutical care plan drawn up via medical notes and home interview (actual and potential PCIs, actions planned, desired outputs). Copies of plan put in medical notes and given to GP. GP asked to indicate level of agreement with each PCI identified and with actions. Pharmacist then implemented agreed actions Group 2 ‐ Interviewed and PCIs identified: no pharmaceutical care plan written or implemented, just usual care (but if serious PCI identified, independent medical assessor decided whether to withdraw patient, n = 1) Co‐intervention: patients interviewed at home about medications, health services, SF‐36, medication costs Provider: pharmacist Where: GP practice/Home When and how often: 1 home visit Intervention personalised: Yes ‐ individualised care plan
Outcomes	Timing of outcome assessment: baseline and 3 months Medication adherence (subjective): potential/actual compliance ‐ pharmacist review identified pharmaceutical care issues, including potential or actual compliance issues. Results as total number of issues at baseline and number resolved at 3 months Health‐related quality of life (subjective): SF‐36 (data not reported in paper)
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: Grampians Healthcare NHS Trust Dropout: 24 and 25 (excluded after randomisation ‐ hospital, ill health, holidays), 1 withdrew
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	After stratification by number of drugs, number of CV drugs and presence of NSAIDs, patients allocated randomly to intervention or control
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	No details provided
Incomplete outcome data (attrition bias) All outcomes	Low risk	Withdrawal explained. No differences in demography or medicine use between groups
Selective reporting (reporting bias)	High risk	Not all results listed (e.g. HRQoL just says not significant)
Other bias	Low risk	None apparent

Lee 2006.

Study characteristics
Methods	Aim of study: to test the efficacy of a comprehensive pharmacy care programme to improve medication adherence and its associated effects on BP and LDL‐C Study design: RCT (multi‐phase prospective study with observational and RCT components) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: outpatient pharmacy clinics (outpatient medicine service of Army Medical Centre and Armed Forces Retirement Home (independently living military healthcare beneficiaries)) Inclusion criteria: ≥ 65 years, ≥ 4 long‐term medications daily, at increased risk for non‐adherence Exclusion criteria: not living independently (assisted living or nursing home residents excluded), had serious medical condition with unlikely 1‐year survival Number of participants randomised: 159 (83 vs 76) enrolled in RCT phase Number of participants included in analysis: 159 (83 vs 76) Age: mean SD 77 ± 10.5 vs 78 ± 6.2 Gender: female: 21 (25.3%) vs 20 (26.3%) Ethnicity: white: 51 (61.4%) vs 43 (56.6%), black: 29 (34.9%) vs 31 (40.8%) Number of medications: long‐term medications: 9.1 ± 3.2 vs 8.3 ± 2.8 Frailty/Functional impairment: not specified Cognitive impairment: taking medication for memory problems: 6 (3.8%) vs 2 (1.3%) Comorbidities: ≥ 4 health problems: 52 (62.7%) vs 38 (50%)
Interventions	Group 1 ‐ Comprehensive pharmacy care programme: clinical pharmacist meeting every 2 months; medications continued to be blister‐packed (phase 2) Group 2 ‐ Return to usual care (no adherence aid, new pill bottles with 90‐day supply and 1 refill prescription given) Co‐intervention: run‐in: (months 1 and 2) = baseline data collection (adherence, BP, LDL‐C); phase 1 (months 3 to 8): prospective observational study of comprehensive pharmacy care programme including individualised medication education, medications dispensed via adherence aid, and regular follow‐up with clinical pharmacist every 2 months Provider: pharmacist Where: pharmacy clinics at outpatient medical centre and retirement home When and how often: 2 monthly clinical pharmacist follow‐ups Intervention personalised: yes
Outcomes	Timing of outcome assessment: baseline (end of phase 1; 8 months) and conclusion (end of phase 2; 14 months) Medication adherence (objective):pill count adherence: sustained mean medication adherence Condition‐specific outcomes (objective): blood pressure: change in systolic and diastolic blood pressure ‐ mmHg Condition‐specific outcomes (objective): LDL cholesterol: change in LDL‐C ‐ mg/dL
Notes	Trial registration: NCT00393419 Consumer involvement: not specified Funding source: competitive junior investigator grant from American Society of Health‐System Pharmacists Research and Education Foundation Dropout: 13 lost to follow‐up (6 and 7), last observation carried forward
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Randomised in 1:1 ratio via a computer‐generated random number sequence. Patients randomised in blocks based on level of baseline medication adherence (above or below 55%)
Allocation concealment (selection bias)	Low risk	Allocation was concealed to both patients and study personnel and was revealed at end of phase 1
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not possible to blind participants
Blinding of outcome assessment (detection bias) All outcomes	High risk	Not possible to blind pharmacists assessing outcomes
Incomplete outcome data (attrition bias) All outcomes	Low risk	Figure 1 shows participant flow, last observation carried forward for analysis
Selective reporting (reporting bias)	Unclear risk	Results at baseline not split based on intervention or control; hard to compare intervention effect
Other bias	Low risk	None apparent

Lim 2004.

Study characteristics
Methods	Aim of study: to evaluate the impact of a pharmacist consult clinic on health‐related outcomes of elderly outpatients in a local setting Study design: RCT (randomised in blocks of 2 participants) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Singapore Setting: outpatient clinic (geriatric medicine hospital outpatient clinic) Inclusion criteria: participants who required drug therapy monitoring, evidence of polypharmacy (> 3 regular meds or > 9 doses per day), documented non‐compliance, self‐administered drugs that require psychomotor skill and co‐ordination, on nasogastric tube feeding, > 1 doctor managing care OR hospitalised within last 6 months Exclusion criteria: stable on follow‐up, cognitive impairment and no caregiver to participate, life expectancy < 6 months, medications supervised by other healthcare personnel Number of participants randomised: 136 (68 and 68) Number of participants included in analysis: 126 (64 and 62) Age: mean ± SD: 79.6 ± 7.7 vs 80.5 ± 8.1 Gender: female: 60.9% vs 69.4% Ethnicity: Chinese 73.4% vs 83.9%, Malay 6.3% vs 6.5%, Indian 12.5% vs 6.5%, Other 7.8% vs 3.2% Number of medications: regularly scheduled medicines: median (range): 6 (3 to 16) vs 7 (3 to 10) Frailty/Functional impairment: ADL independent: 50.8 % vs 40.3% Cognitive impairment: impaired cognition: 20.3% vs 21.0% Comorbidities: not specified
Interventions	Group 1 ‐ Pharmacist consult in clinic (10 to 30 minutes) ‐ evaluate patients for MRPs by reviewing medical records and medication list and by interviewing patient and caregiver. Recommendations to simplify, reduce ADEs, decrease cost, etc., discussed with primary physician, and accepted recommendations implemented. Pharmacist also counselled on medication knowledge, administration, etc. Group 2: assumed usual care Co‐intervention: N/A Provider: pharmacist Where: outpatient clinic When and how often: once at baseline Intervention personalised: yes ‐ Individualised based on medications and MRPs
Outcomes	Timing of outcome assessment: baseline and 2 months Medication adherence (subjective) : self‐reported compliance: patients asked if they 'forgot to take medication as directed'. Then categorised as compliant or not. Participants then classified as least compliant (compliant at base, not at 2 months), not compliant (not compliant at base or 2 months), compliant (compliant at 2 months) Knowledge about medicines (objective): composite % knowledge of dose (D), frequency (F), and indication (I), reported as percentage correct. Adverse clinical health outcomes (subjective): reported ADRs. Asking patients if they experience side effects or unwanted reactions with their medications. Patients asked to name medication involved; this was assessed by primary care physician to ascertain whether symptoms were indeed ADRs of the implicated medicine
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: National Healthcare Group research grant NHG‐RPR/01027 Dropout: 10 excluded before intervention (4 and 6), 9 withdrew (5 and 4), 17 lost‐to follow up (8 and 9) Further information required: raw data on adherence and medication knowledge at follow‐up (email correspondence with trial author successful, but further data not available)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Randomly assigned via computer‐generated numbers in blocks of 2
Allocation concealment (selection bias)	Unclear risk	Randomisation carried out before consent (Zelen design)
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unblinded
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Not specified
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	Figure 2 shows study profile; ITT concluded patients only
Selective reporting (reporting bias)	High risk	Raw values for outcomes not listed; 90% CI?; no sample size calculation
Other bias	Low risk	None apparent. Sample size 60/arm "to achieve a power of 80% to detect a 10% difference between the 2 groups in the knowledge outcome"

Lingler 2016.

Study characteristics
Methods	Aim of study: to develop and examine the efficacy of a tailored, problem‐solving intervention on informal caregivers' management of medications for community‐dwelling persons with memory loss Study design: RCT (unit of allocation: dyad) Number of arms/groups: 2
Participants	Description: both patient/consumer and carers (recruited as dyads) Geographic location: USA Setting: participant's home Inclusion criteria: PATIENT: self‐ or caregiver‐reported memory loss necessitating help with medication‐taking, ≥ 2 comorbid conditions requiring medication, living in community, provided informed consent. INFORMAL CAREGIVERS: family members or kin‐like friends, ≥ 18 years, participating in management of patient's medications, exhibiting ≥ 1 deficiency on any of 3 measures of ability to effectively manage the patient's medications, living within 75 miles of the University Exclusion criteria: paid caregivers, living in residential care setting Number of participants randomised: 83 pairs (42 vs 41) Number of participants included in analysis: 76 pairs (37 and 39) Age: mean ± SD: patients 79.67 ± 9.19 vs 80.15 ± 8.48, caregivers 66.00 ± 12.8 vs 67.80 ± 11.2 Gender: female = patients 28 (67%) vs 22 (54%), caregivers 29 (69%) vs 29 (71%) Ethnicity: white: patients 34 (81%) vs 37 (90%), caregivers 34 (81%) vs 37 (90%); black: patients 3 (7%) vs 3 (7%), caregivers 4 (10%) vs 3 (7%); other patients 5 (12%) vs 1 (2%), caregivers 4 (9%) vs 1 (2%) Number of medications: total medications (including OTC, supplements, etc.): 10.79 ± 5.52 vs 10.61 ± 5.89 Frailty/Functional impairment: not specified Cognitive impairment: baseline sample (n = 91) patients: MMSE = 17.62, carer blessed = 2.97 Comorbidities: number of comorbidities: patients 8.691 ± 3.57 vs 9.024 ± 4.21, carers 7.86 ± 3.69 vs 6.44 ± 3.59
Interventions	Group 1 ‐ Maximising Medication Management by Caregivers of Persons With Memory Loss: guided by intervention manual; sessions with nurse or social worker interventionist addressed 7 basic aspects of the caregiver's role in managing medications during home/telephone discussions. Caregivers provided with self‐study version of intervention manual. Initial 8‐week intervention, then 4 bi‐weekly calls over next 8 weeks (note: mean length of home visits ‐ 40.05 minutes (SD 13.22) ‐ and telephone sessions ‐ 13.42 minutes (SD 6.34)) Group 2‐ Usual care: at baseline, received pamphlet on medication safety. Received home visits for purpose of data collection only (medication errors were corrected). At completion of study, caregivers received intervention manual Co‐intervention: for safety, if any errors were noted during medication reconciliation, they were brought to the attention of both caregivers and prescribers regardless of group assignment. In addition, all participants received care as usual from their healthcare providers Provider: nurse or social worker Where: patient's home When and how often: 2 or 3 home visits 2 weeks apart, followed by 2 or 3 telephone sessions 7 to 10 days apart for 8 weeks; then 4 bi‐weekly phone calls for 8 weeks Intervention personalised: Yes ‐ guided by intervention manual but individualised based on caregivers needs/queries and patients medication
Outcomes	Timing of outcome assessment: baseline and 2 months post intervention Medication‐taking ability (objective): MedMaIDE: Medication Management Instrument for Deficiencies in the Elderly: uses interview and observation to assess ability to self‐administer medications using 3 areas: knowledge of medications, how to take medications, and how to procure medications. Each medication is reviewed during administration. Scores 0 to 13; max total deficiency score is 13 Satisfaction with intervention (subjective): set of Likert scaled questions (not specified), eliciting open‐ended comments during an exit interview at study completion Other (objective): Medication Deficiency Checklist (MDC): 15‐item, investigator‐developed instrument; uses caregiver interviews to assess for the presence of errors and problems (e.g. taking at the wrong time). Investigator‐developed tool ‐ not validated
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: programme project grant: NIH/NINR P01 NR010949 Dropout: 3 pairs withdrew (2 vs 1), 4 pairs were lost to follow‐up (3 vs 1) Fidelity: good ‐ independent rater randomly selected 10% of cases for an audit of protocol fidelity. Percentage of agreement 91.6%, quality of interaction 4.5/5 Unpublished data included successful communication with trial authors; follow‐up MedMAIDE results provided
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Random group assignments were computer generated with permuted blocks within strata to ensure balance of nurse/social worker, relationship of caregiver, and race/ethnicity
Allocation concealment (selection bias)	Unclear risk	Order of consent/allocation not specified; no details on allocation concealment provided
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unblinded ‐ necessary because it was not feasible to blind participating caregivers to group assignment
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	No blinding specified; unclear who did outcome assessment
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	Minimal loss to follow‐up; clearly detailed. Erlen paper: includes instances where data are missing, so number of participants may be different. We did not impute data for these participants
Selective reporting (reporting bias)	Unclear risk	MedMaIDE results presented only in visual format; raw results not included in results text
Other bias	Low risk	None apparent

Lipton 1994.

Study characteristics
Methods	Aim of study: to evaluate whether the intervention would (1) enhance patients' compliance with drug regimens, (2) reduce polypharmacy, (3) lower healthcare expenditures for physician visits, ED visits, and hospitalisations, and (4) reduce hospital re‐admission rates Study design: RCT (unit of allocation: individual) Number of arms/groups: 2
Participants	Description: both patient/consumer and carer Geographic location: USA Setting: hospital discharge (in hospital and post discharge via telephone or face‐to‐face in hospital or at home) Inclusion criteria: ≥ 65 years, covered by Medicare, admitted to non‐psychiatric ward, residing within 35 miles, English‐speaking (or proxy), mentally competent (or proxy), access to telephone, discharged not to nursing home or hospice, ≥ 3 medications taken for chronic conditions at hospital discharge Number of participants randomised: 719 (not clearly stated; 52% of 1383 eligible) Number of participants included in analysis: 706 (350 vs 356) Age: mean: 74.6 vs 74.4 Gender: not specified Ethnicity: not specified Number of medications: long‐term medications at second compliance assessment: 5.16 ± 2.62 vs 6.75 ± 2.92 Frailty/Functional impairment: at least 1 sensory deficit: 29% vs 32% Cognitive impairment: those not mentally competent had to have proxy Comorbidities: not specified
Interventions	Group 1 ‐ Clinical pharmacist review and face‐to‐face consultations: pharmacists review hospital records and drug regimens, then conduct face‐to‐face consultation with patient. Post‐discharge consultations at 1 week, 2 to 4 weeks, 2 months, and 3 months post discharge, via telephone or in pharmacy at hospital or in home. Medication regimen simplification by discussion with physician for prescription, or with patient for non‐prescription Group 2: usual care Co‐intervention: both groups: booklets given at discharge to record medication information (e.g. drug purpose, dosage, schedule) Provider: pharmacist (clinical hospital pharmacist) Where: in hospital + hospital, home or telephone When and how often: baseline, post‐discharge consultations at 1 week, 2 to 4 weeks, 2 months, and 3 months post discharge Intervention personalised: yes
Outcomes	Timing of outcome assessment: 6 to 8 weeks and 12 to 14 weeks post discharge Medication adherence (subjective) : structured telephone interviews with a subsample. Only data for antiarrhythmics, antihypertensives, anticoagulants, cardiac anticonvulsants, antidiabetic NSAIDs, respiratory and GI drugs collected, and only for first 3 medications mentioned by patient. Adherence asked for the first 3 such medications mentioned by patient. 4 behavioural questions (excluding purpose) ‐ calculated as total compliance score out of 100. Perfect compliance = 100. Results as (1) mean compliance scores (SD), (2) mean proportion with perfect (100%) scores Cost‐effectiveness (objective): Medicare Part B charges: total days in hospital, total hospital inpatient charges
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: John A. Hartford Foundation (NYC) Dropout: not specified
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Patients drew a folded slip of paper from a box containing equal numbers of experimental and control‐designated slips
Allocation concealment (selection bias)	Low risk	Patients drew a folded slip of paper from a box containing equal numbers of experimental and control‐designated slips
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not possible to blind
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Interviewers not study pharmacists; interviews conducted by investigators. Both interviewers were blinded to study group assignment
Incomplete outcome data (attrition bias) All outcomes	High risk	Subgroup selected for substudy on adherence; no details on how selected. States no demographic differences but demographics not listed. 274 selected for interview, but only 206 completed second assessment (25% attrition)
Selective reporting (reporting bias)	Unclear risk	Hospital re‐admission data not clear; compliance reported ‐ but additional analyses that looked at compliance (excluding purpose) not specified in methods
Other bias	High risk	Adherence measure only for first 3 medications mentioned by patient ‐ patients may have preferentially selected medications they were more familiar with (thus more adherent with)

Lopez Cabezas 2006.

Study characteristics
Methods	Aim of study: to assess the efficacy of multi‐factorial educational intervention carried out by a pharmacist in patients with heart failure Study design: RCT (2 hospitals; allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Spain Setting: hospital discharge Inclusion criteria: patients admitted for definite heart failure (Framingham criteria ‐ 2 major or 1 major + 2 minor criteria met simultaneously) Falces 2008 describes subgroup > 70 years Exclusion criteria: living out of the area of influence of the hospital, living in old people's home, moved to a social‐health centre or other centre for acute patients, suffering any type of dementia or psychiatric disease, refusing participation Number of participants randomised: 134 (70 and 64), subgroup > 70 years: 103 (53 vs 50) Number of participants included in analysis: 134 (70 and 64), except adherence 63 (40 vs 23), subgroup > 70 years: 82 (45 vs 37) Age: 75.3 ± 8.4 vs 76.1 ± 9.4, subgroup > 70 years: 79.0 ± 4.9 vs 80.1 ± 5.5 Gender: female: 41 (58.6%) vs 34 (53.1%), subgroup > 70 years: 60.4% vs 56% Ethnicity: not specified Number of medications: type not specified, 7.1 ± 3.0 vs 7.1 ± 2.5, subgroup > 70 years: 7.5 ± 3.1 intervention vs 7.0 ± 2.1 control Frailty/Functional impairment: New York Heart Association Functional Classification: I to II: 58 (84.1%) vs 54 (87.1%) Cognitive impairment: dementia excluded Comorbidities: total not reported
Interventions	Group 1 ‐ Active information programme: active information programme (run by a pharmacist from the research team) consisted of a personal interview at the time of discharge and subsequent telephone reinforcement. Intervention included information about the disease, diet education, and information about the medications. Simple language was used, adapted to the cultural level of patients, with support of audiovisual and written didactic materials. Monthly during first 6 months of follow‐up, and subsequently every 2 months, patients were called to reinforce the intervention and to solve doubts or problems that may have arisen Group 2 ‐ Usual care Co‐intervention: N/A Provider: pharmacist Where: in person at discharge; telephone to home When and how often: discharge, monthly follow‐up for 6 months, then 2‐monthly follow‐up for 6 months Intervention personalised: yes
Outcomes	Timing of outcome assessment: 12 months Medication adherence (objective) : pill count/tablet accountability: % of reliable patients (95% to 100% compliance) Satisfaction with intervention (subjective): Catalan Health Department satisfaction survey, asking patients about care and information received and asking them to provide a global score from 0 to 10 Health‐related quality of life (subjective): EuroQol, validated in Spanish and in Catalan Adverse clinical health outcomes (objective): hospital re‐admissions, percentage of patients with re‐admission, subgroup > 70 years: mortality Adverse clinical health outcomes (objective): number of deaths Cost‐effectiveness (objective): financial evaluation: hospitalisation costs calculated for both groups, with intervention direct costs, delivered materials, and time spent by the pharmacist added in
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: Health Research Fund and European Regional Development Fund Dropout: 12 months of data for adherence only available for 40 and 23 patients, subgroup > 70 years: 20 died (7 vs 13) Language translation: yes ‐ Falces 2008 was translated to English
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Generation of the randomisation sequence was the responsibility of the clinical epidemiology unit. Randomisation lists were generated by software and in blocks of 4
Allocation concealment (selection bias)	Unclear risk	Allocation controlled by admissions department; recruitment carried out by cardiology department
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded. Neither the physician nor the nurse responsible for the patient knew the allocation until the educational intervention on the day of discharge
Blinding of outcome assessment (detection bias) All outcomes	High risk	Compliance assessed by pharmacist. Pharmacist responsible for active info programme knew allocation; this could have generated contamination problems
Incomplete outcome data (attrition bias) All outcomes	High risk	No mention of reason for attrition; only 47% completed 12‐month compliance Falces paper: compliance data available for only 49 patients (59%). Methods stated that those who did not attend follow‐up were to be considered non‐compliant, but results were not presented this way. P value figure not listed
Selective reporting (reporting bias)	High risk	Reported only 'reliable patients' ‐ but compliance had 3 levels: reliable, partially reliable, not reliable. Financial evaluation not a planned outcome Falces paper: no reasons given for chosen variables in hazard ratio calculation
Other bias	Unclear risk	Sample size calculation: 67/group not reached; 3 years from final data to publication

Manning 2007.

Study characteristics
Methods	Aim of study: to determine whether the 3D tool is better than the Medication Discharge Worksheet in terms of patient satisfaction, understanding, and safety Study design: RCT (exploratory RCT; 4 medical units; individual allocation) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: hospital discharge Inclusion criteria: > 20 years, ≥ 3 discharge medications, returning to self‐care at home (or to care of a relative) Exclusion criteria: discharge to nursing home, hospital, or assisted living facility; unable to speak or read English; unable to hear over the telephone to participate in follow‐up; pregnant Number of participants randomised: 337 Number of participants included in analysis: 138 (78 and 60) Age: mean ± SD 68.1 ± 5.65 intervention vs 67.6 ± 13.06 control (total range 24 to 100) Gender: unclear: % or mean (SD): Table 1: 0.51 ± 0.50 vs 0.38 ± 0.49 Ethnicity: not specified Number of medications: not specified (discharge medications): 10.0 ± 4.42 vs 8.7 ± 3.93 (total range 4 to 31) Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: not specified
Interventions	Group 1 ‐ 3D (durable display at discharge) medication discharge education tool: 3D tool including purpose, time to take medications, comments and cautions, and space for durable display (patients encouraged to affix tablet/capsule of each medication onto the 3D tool in column labelled "Display"). Plus a section for "home medications you should no longer take". Participants randomised to 3D upon returning home and after filling any new prescriptions were encouraged to affix (with clear adhesive tape) a tablet or capsule of each medication onto the 3D adjacent to the medication name and under the column labelled "Display" Group 2 ‐ Usual care ‐ medication discharge worksheet (MDW) Co‐intervention: before hospital dismissal, the primary nurse conducted her/his usual patient education session including usage of either MDW or 3D (per randomisation) Provider: 3D medication sheets (generated by study recruiter, reviewed by principal investigator or pharmacist co‐investigator. Nurse provided patient education) Where: hospital discharge When and how often: once Intervention personalised: yes
Outcomes	Timing of outcome assessment: 7 to 14 days after discharge Medication taking ability (subjective) : self‐reported safety in taking medications: "since discharge, how many mistakes have you made taking your medications (score 0‐4)?" Knowledge about medicines (objective): assessment of knowledge of indication, dosage frequency, and special comments or cautions: 0 (for no correct responses) to 3 (all correct responses) Satisfaction with intervention (subjective): how satisfied were you with the form you received from the nurse when she/he was talking to you about your medications? 5‐point Likert scale: 1 (low) to 5 (high)
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: Mayo Clinic Rochester MIDAS Grant; Mayo Foundation for Education and Research, small grants programme Dropout: 38 (did not remember form ‐ so were not interviewed), 126 lost to follow‐up (93 could not be reached, 12 excluded post discharge, 4 could not hear during call, 5 incorrect phone number, 2 did not receive MDW, 5 too ill, 4 refused, 1 no English) Fidelity: compliance with affixing medications to 3D is uncertain
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Computer‐generated random number algorithm
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not possible to blind
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Research assistant conducting follow‐up call was blinded to both study hypotheses and participant randomisation
Incomplete outcome data (attrition bias) All outcomes	High risk	Loss to follow‐up high. 176/337 randomised were contacted by telephone, 38 did not remember the tool so were excluded from analysis, only 41% of randomised patients (138/337) were included in analysis. No statistically significant differences in patient loss at each level
Selective reporting (reporting bias)	Low risk	Hypotheses and outcomes listed as per methods
Other bias	Unclear risk	"Patient compliance with affixing medications to 3D is uncertain" ‐ "analysed on intention‐to‐influence basis with knowledge that any non‐compliance might diminish the apparent 3D benefit"

Marek 2013.

Study characteristics
Methods	Aim of study: the purpose of this study was to evaluate health status outcomes of frail older adults receiving a home‐based nurse support programme that emphasised self‐management of medications using both care co‐ordination and technology Study design: RCT (3 home healthcare agencies, individual allocation) Number of arms/groups: 3
Participants	Description: patient/consumer Geographic location: USA Setting: discharge from home health care Inclusion criteria: ≥ 60, Medicare primary payer, impaired ability to manage medications and/or impaired cognitive functioning, working telephone and electricity Exclusion criteria: terminal diagnosis or hospice care that would make attrition likely, use of other device for medications (e.g. pager) Number of participants randomised: 456 Number of participants included in analysis: 414 (152, 137, 125); completed 12‐month follow‐up: 301 (98, 102, 101) Age: mean ± SD: MD.2: 79.6 ± 7.92 vs Planner: 79.6 ± 7.64 vs Control: 78.2 ± 7.25 Gender: n (%) female: 104 (68.4) vs 93 (67.9) vs 77 (61.6) Ethnicity: n (%): white: 124 (81.6) vs 114 (83.2) vs 113 (90.4); black: 28 (18.4) vs 22 (16.1) vs 12 (9.6); Hispanic: 2 (1.3) vs 6 (4.4) vs 3 (2.4) Number of medications: all medications: mean ± SD: 11.01 ± 4.466; range 2 to 27 (as listed in Lancaster 2014) Frailty/Functional impairment: physical performance test: 14.6 ± 5.06 vs 14.2 ± 5.16 vs 15.8 ± 6.14 Cognitive impairment: MMSE: 25.5 ± 3.33 vs 25.0 ± 3.65 vs 26.3 ± 3.17 Comorbidities: total comorbidities not listed
Interventions	Both groups 1 and 2: received nurse care co‐ordination ‐ education, tools for participants to manage their chronic conditions, enhanced communication with health professionals, monitoring signs and symptoms of disease. Nurse visited at least every 2 weeks + additional visits if change in medication or if hospitalised Group 1MD.2: medication‐dispensing machine (releases preloaded medication in plastic reusable cups; at pre‐programmed intervals, user presses large red button and a plastic cup containing medications in a chute. Audible and visual prompt for 45 minutes; if medication not taken, then notification to identified responder, e.g. family member, nurse) Group 2Medplanner: Medplanner (simple weekly medication box). Nurses filled Medplanners and recorded number of medications remaining in the Medplanners before refilling. Group 3Usual care Co‐intervention: each participant received a pharmacy screen on admission (pharmacist and advanced practice nurse), which was sent to prescribing provider(s). Main purpose was to ensure medications were not harmful Provider: nurse care co‐ordinators + medication device Where: in home When and how often: 12 months: contact minimum every 2 weeks as per intervention Intervention personalised: individualised
Outcomes	Timing of outcome assessment: monthly for 12 months Medication adherence (objective) : percentage correct doses/month: average percentage of correct doses per month in 2 intervention groups. Machine recorded medication doses or nurse counted medications left in planner Health‐related quality of life (subjective): HRQoL: quarterly improvement in SF‐36
Notes	Trial registration: NCT01321853 Consumer involvement: not specified Funding source: National Institute of Nursing Research & University of Wisconsin‐Milwaukee Self‐Management Science Center Dropout: excluded before baseline (22, 17, 3), did not receive intervention (22, 11, 0), lost to follow‐up (32, 24, 24)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Randomised by computer programme developed by a study statistician
Allocation concealment (selection bias)	Low risk	Randomised before staff contacted potential patients
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not possible to blind providers or patients. Higher attrition rate from MD.2
Blinding of outcome assessment (detection bias) All outcomes	High risk	Not possible to blind providers and data collection. Research data collectors, however, did not deliver the intervention, and interrater reliability among data collectors was monitored closely
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	Analysed based on intention‐to‐treat. Only 72.7% completed 12‐month follow‐up
Selective reporting (reporting bias)	Unclear risk	Adherence results not reported clearly; no MD.2 vs control for HRQoL
Other bias	Unclear risk	Sample size 100 per group reached (but close) ‐ noted actually completed numbers 98 vs 102 vs 101

Marusic 2013.

Study characteristics
Methods	Aim of study: to evaluate the effect of hospital pharmacotherapeutic counselling on rates and causes of 30‐day post‐discharge hospital re‐admissions and ED visits Study design: RCT (individual allocation) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Croatia Setting: hospital discharge Inclusion criteria: ≥ 65 years, hospital discharge to community with prescription for ≥ 2 medications for treatment of chronic disease Exclusion criteria: cognitive or perceptual problems, diagnosis of terminal illness with life expectancy < 1 month, discharge to long‐term care facility, inability to be followed up Number of participants randomised: 160 Number of participants included in analysis: 160 (80 and 80) Age: mean ± SD (range): 74.0 ± 6.7 (65 to 88) vs 73.9 ± 5.5 (65 to 87) Gender: female n (%): 43 (53.8%) vs 47 (58.8%) Ethnicity: not specified Number of medications: prescribed medication mean ± SD (range): 6.6 ± 2.4 (2 to 13) vs 6.2 ± 2.6 (2 to 13) Frailty/Functional impairment: not specified Cognitive impairment: cognition problems excluded Comorbidities: number of discharge diagnoses: 4.4 ± 1.6 (1 to 8) vs 3.9 ± 1.5 (2 to 8)
Interventions	Group 1 ‐ Pharmacotherapeutic discharge counselling: pre‐discharge counselling (30 minutes) by qualified physician, specialist in clinical pharmacology, provided within 24 hours before discharge. Counselling included indications, dosage and admin times, importance of compliance, possible consequences of non‐compliance, possible ADRs Group 2 ‐ Usual care (including discharge letter to be handed to GP) Co‐intervention: N/A Provider: physician (specialist in clinical pharmacology) Where: hospital When and how often: once within 24 hours of discharge Intervention personalised: yes
Outcomes	Timing of outcome assessment: 30 days Medication adherence (objective) : pill count ‐ patients asked to bring all remaining medications and empty packaging to follow‐up visit. Compliance = total number of doses taken by the patient since discharge/total number of doses to be taken since discharge × 100. Reported as percentage of participants who are compliant (80% to 110%). If participants could not attend hospital, then visit was arranged at home Adverse clinical health outcomes (objective): hospital re‐admission/ED visit: number of patients with re‐admission or ED visit Adverse clinical health outcomes (objective): number of patients with ADRs: the probability that an ADR was drug related was estimated using the Naranjo ADR probability scale. ADRs that were fatal or life threatening or required hospital admission were considered serious ADRs
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: no external funding Dropout: nil mentioned
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Manual shuffle of 80 intervention and 80 control cards in envelopes
Allocation concealment (selection bias)	Unclear risk	Sealed, unmarked envelope contained card with 'intervention' or 'control'. Unclear if opaque envelopes
Blinding of participants and personnel (performance bias) All outcomes	High risk	Patients and physicians were not blinded
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Outcomes assessed by research assistant blinded to treatment assignment
Incomplete outcome data (attrition bias) All outcomes	Low risk	No attrition
Selective reporting (reporting bias)	Low risk	Reported as per methods
Other bias	Low risk	Sample size 80/group

Messerli 2016.

Study characteristics
Methods	Aim of study: to investigate the impact of the polymedication check (PMC) on patients on polypharmacy Study design: RCT (individual allocation) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Switzerland Setting: community pharmacy Inclusion criteria: > 18 years, ≥ 4 prescribed drugs over ≥ 3 months Exclusion criteria: living in retirement home, prior PMC, receiving weekly dosing aids filled by the pharmacy or another person, cognitive impairment, move or death, insufficient knowledge of written and spoken German or French Number of participants randomised: 450 (218, 232) Number of participants included in analysis: 372 completed; 450 in analysis Age: mean ± SD 67.2 ± 11.52 vs 67.1 ± 11.56 Gender: female: 118 (54.1%) vs 125 (53.9%) Ethnicity: not specified. Number of medications: long‐term oral medications (excluding on‐demand and self‐medication): 6.8 ± 2.92 (range 1 to 19) Frailty/Functional impairment: Disabilities of the Arm, Shoulder and Hand (DASH‐4) score: 4.9 ± 2.01 vs 4.9 ± 1.83 Cognitive impairment: cognitive impairment excluded Comorbidities: not specified
Interventions	Group 1 ‐ Polymedication check (PMC): face‐to‐face counselling with pharmacist. Pharmacist screened all meds, checked for knowledge gaps and pharmaceutical care issues (e.g. handling, adherence). Pharmacist documented all resulting interventions (e.g. GP consultations, implementation of weekly dose reminder systems). Education and medication plan could also be provided when necessary. PMC occurred at T0 and T28 (28 weeks = study end) Group 2 ‐ Usual care: no intervention or T0 documentation. Did receive PMC at 28 weeks (study end) Co‐intervention: N/A Provider: pharmacist (appropriately trained) Where: community pharmacy (separate area, i.e. consulting room) When and how often: T0 (intervention) and T28 (both) Intervention personalised: yes ‐ personalised because medication specific
Outcomes	Timing of outcome assessment: baseline (200 days before T0) and 28 weeks (T0 = T28 = 196 days) Medication adherence (objective) : medication possession ratio (MPR) ‐ calculated by dividing the days supply of a medication dispensed by the number of days in the time interval of interest Knowledge about medicines (objective): knowledge of medicines and daily use ‐ phone questionnaire; 58 questions ‐ included assessing knowledge Adverse clinical health outcomes (subjective): GP/Hospital visits: self‐reported patient's unplanned visits at the general practitioner or hospital
Notes	Trial registration: NCT01739816 Consumer involvement: unclear ‐ the PMC (polymedication check) is standardised so potential consumers can be involved in the original development of the Swiss PMC Funding source: investigator initiated project; funded in part by Swiss Pharmacists Association, pharmaSuisse Dropout: 18 withdrew, 60 were lost to follow‐up
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Patients were assigned by 2 × 4 block randomisation to intervention or control group. Initially, each study pharmacist received 2 blocks containing 8 dossiers (4 intervention and 4 control), each packed in sealed and unlabelled envelopes. Unclear if envelopes opaque
Allocation concealment (selection bias)	Unclear risk	Once the first patient had consented, the study pharmacist opened 1 envelope out of the first block to reveal which arm of the study the patient had been randomised to. Once all 8 envelopes of block No. 1 had been assigned, the next block was used. Upon request, further blocks were available. Pharmacist would know allocation of some (e.g. if already opened 4 intervention, then would know remaining were control)
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unable to blind; Hawthorne effect
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Patients filled out questionnaire, sealed in envelope, and returned to pharmacy. Interviewers blinded to intervention and without knowledge of the content of the PMC or the patient questionnaire at T0
Incomplete outcome data (attrition bias) All outcomes	High risk	Table 2 summarises reasons for dropout: 34 lost because pharmacist revoked study participation because underestimated time commitment. Missing patients from both T0 and T28 analyses unexplained
Selective reporting (reporting bias)	High risk	MPR for antiplatelets and PPI listed, not mentioned in methods; no results presented for medication knowledge
Other bias	Unclear risk	Sample size calculation: 780 at T0 and 252 at T28 (not reached for adherence). Also study pharmacists received compensation for delivery of each complete patient data set, and patients paid for time spent on telephones

Moral 2015.

Study characteristics
Methods	Aim of study: to determine whether a face‐to‐face communicative strategy based on motivational interviewing (MI), used by health practitioners (family physicians and nurses) in a primary care setting, and aimed at patients over 65 years old with a chronic disease who are being treated by polypharmacy and who have poor medication adherence can achieve better results than the usual approach based on an informative model of providing education and advice Study design: cluster‐RCT (2 arms, 16 health centres, stratified by professional) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Spain Setting: primary care clinic (health centre) Inclusion criteria: > 65, chronic disease, polypharmacy (≥ 5 medicines or ≥ 12 daily doses for a period ≥ 6 months), high probability for non‐adherence (Haynes‐Sackett yes, inconsistent answers to at least 1 of the 4 Morisky‐Green Qs) Exclusion criteria: serious psychiatric and neurological diseases, difficulties coping with basic daily activities (Barthel Index < 60), those who had cognitive impairment (Pfeiffer's test), those admitted to hospital at least twice in last year, patients under carer's supervision Number of participants randomised: 32 (16 and 16) health professionals, 70 vs 84 patients Number of participants included in analysis: 66 vs 81 (but included in analysis 70 vs 84) Age: 75.6 ± 5.9 vs 76.1 ± 5.8 Gender: female: 49 (70%) vs 57 (67.9%) Ethnicity: not specified Number of medications: medication consumption: 8.7 ± 2.5 vs 9.0 ± 3.1 Frailty/Functional impairment: not specified; < 60 Barthel Index ADLs excluded Cognitive impairment: cognitive impairment excluded Comorbidities: mean ± SD: chronic disease: 4.9 ± 2.1 vs 5.1 ± 2.6
Interventions	Group 1 ‐ Motivational interviewing (MI): intervention health professionals attended an additional 20‐hour workshop taught by family doctor who is expert in the field. Intervention professionals focused on motivational interviewing. Strategies of EMot are based on a collaborative, evocative style and respect for autonomy of the patient. The practice of EMot is based on 4 basic principles grouped under the acronym RULE: R (resist) resist the redirect reflex, U (understand) understand and explore the motivations of the patient himself, L (listen) listen empathically, and E (empower) empower the patient, favouring hope and optimism Group 2 ‐ Usual care: control patients received routine clinical attention based on transmission of info and persuasive advice Co‐intervention: before intervention, healthcare providers in both groups attended a 15‐hour workshop on patient safety and medication adherence. Intervention: (1) initial assessment of medication status, (2) detection of critical incidents and possible medication errors, (3) providing information, (4) developing customised action plan, (5) proposal for implementation Provider: physician or nurse (trained health professionals ‐ 16 physicians and 11 nurses) Where: patient's home or health centre When and how often: V0 baseline in healthcare setting (15 m), V1 at 15 to 20 days at home (45 to 60 m), V2 at 3 months in healthcare setting (15 m), V3 at 6 months at home (45 to 60 m) Intervention personalised: yes
Outcomes	Timing of outcome assessment: baseline and 6 months Medication adherence (objective):pill count: number of tablets presumably consumed/Number of tablets that should be consumed × 100. Adherent if average adherence > 80% and < 110% Other (objective) : average medication errors according to group. Errors including subtherapeutic dose, omission of administration, deteriorated drug, duplicate therapy, higher doses and other (reported in Perula de Torres 2014 paper)
Notes	Trial registration: NCT01291966 Consumer involvement: not specified Funding source: supported by Spanish Society of Family and Community Medicine and Andalusian Society of Family and Community Medicine research grant, and the Ministry of Health of the Government of Andalusia, Spain Dropout: 5 (3 vs 2) health professionals did not recruit any participants, 2 patients withdrew, 4 were lost to follow‐up (Perula de Torres paper says 5 lost to follow‐up) Language translation: yes ‐ Perula de Torres 2014 paper translated to English Exact ICC value not reported. Paper states that "ICC in cRCT in primary care generally less than 0.05". Thus 0.05 was used to recalculate sample sizes, 57 intervention vs 67 control
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	"We performed blinded randomization to one of the two study arms (C4‐Study Design Pack; Glaxo S.A.)" 32 professionals assigned randomly and stratified by type of professional
Allocation concealment (selection bias)	Unclear risk	Allocation based on clusters and stratified by profession (nurse or physician). Unclear if/how allocation was concealed
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not possible to mask the intervention, either to patients or to providers
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Unclear if assessors blinded. Final results were evaluated by a methodology expert of the investigation, who remained at all times blind to the status of patients
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	Unclear who is in final results; states ITT
Selective reporting (reporting bias)	Unclear risk	Unclear how they assessed medication adherence at baseline (i.e. how did they do pill count). Medication adherence mean only at baseline
Other bias	Unclear risk	Sample size calculation: 78 per group not reached Recruitment bias (selective recruitment of cluster participants): high risk. Participants recruited by consecutive sampling. "Time between the training program and patient recruitment and intervention was about two weeks"; thus health professionals were aware of randomisation during participant recruitment stage

Morales Suarez‐Vurela 2009.

Study characteristics
Methods	Aim of study: to assess the utility of the pillbox, individualized dispensing system, and practical dosing, to improve therapeutic compliance in polymedicated patients with diminution of mobility capacity Study design: RCT (open‐label; unit of allocation: individual) Number of arms/groups: 2
Participants	Description: both patient/consumer and carer Geographic location: Spain Setting: community (home) Inclusion criteria: ineffective management of medications due to > 70 years and > 3 prescribed medications and limited mobility Exclusion criteria: cognitive impairment (Pfeiffer test < 3 if person can read and write and < 4 if person cannot read or write), mentally incapacitated patients, hospitalised patients at start of study Number of participants randomised: 182 (89 vs 93) Number of participants included in analysis: 182 (89 vs 93) Age: mean (CI)= 77.08 (76.224 to 77.936), vs 77.39 (76.646 to 78.134); range (min to max) = 61 to 93 vs 20 to 70 Gender: female: 64 (71.9%) vs 64 (68.8%) Ethnicity: not specified Number of medications: (type unclear) mean (CI) 8.35 (7323 to 9377) vs 7.83 (7403 to 8257); range (min to max) 3 to 60 vs 3 to 18. Number of medications/day = 9.22 (8.701 to 9.739) vs 10.60 (9.946 to 11.254), range (min to max) 0 to 23 vs 3 to 22 Frailty/Functional impairment: not reported Cognitive impairment: cognitive impairment excluded Comorbidities: no total comorbidity score
Interventions	Group 1 ‐ Practidose Pillbox: a reusable pillbox ‐ plastic container with 7 compartments (7 days of the week). Name of patient written on the outside of the container and also included treatment control sheet (medication list/chart). Contains only solid dose forms ‐ this fact is rectified by introducing a cardboard pictogram of a jar of syrup, spoon, etc., in the corresponding space, at the time of administration, which reminds the patient that he/she should also take this medication. It is not clear who filled the pillbox as the intervention is not well described Group 2 ‐ Not specified ‐ presumably usual care without pillbox Co‐intervention: N/A Provider: nurse (district link nurse) and pillbox Where: unclear When and how often: in person baseline and 2 months, phone call at 14 days Intervention personalised: no (aside from individual medications in the box)
Outcomes	Timing of outcome assessment: baseline and 2 months Medication adherence (subjective) : Morisky‐Green Medication Compliance: nurse‐administered survey. Unclear how results are reported ‐ appears to be reported as % patients who are compliant, but it is not defined)
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: not specified Dropout: nil Language translation: yes ‐ translated to English Further information required: more detail on randomisation, allocation, recruitment, and adherence measure (email correspondence ‐ unsuccessful)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	"The selection of patients was made by assignment randomized by blocks" It appears these were blocks of 10 (5 intervention and 5 control for each nurse), but it is unclear how they were generated
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	All patients aware of allocation, unblinded
Blinding of outcome assessment (detection bias) All outcomes	High risk	Unblinded ‐ appears nurses administered intervention and follow‐up on their own patients
Incomplete outcome data (attrition bias) All outcomes	Low risk	No attrition specified
Selective reporting (reporting bias)	High risk	Multi‐variate analyses not reported in table ‐ unclear what was done. Morisky‐Green individual questions not reported ‐ unclear how adherence summarised (suspect answer no to all questions)
Other bias	Low risk	Sample size of 83 in each group

Murray 1993.

Study characteristics
Methods	Aim of study: to determine the effect of unit‐of‐use packaging on medication compliance among elderly outpatients treated with complex medication regimens Study design: RCT (unit of allocation: individual) Number of arms/groups: 3
Participants	Description: patient/consumer Geographic location: USA Setting: primary care clinic (geriatric outreach centres located in urban public housing units for the elderly and disabled (people living independently)) Inclusion criteria: ≥ 60 years, ≥ 3 medications Exclusion criteria: medication pharmacologic and pharmacokinetic properties considered unfeasible for twice‐daily regimen, nursing home Number of participants randomised: 36 Number of participants included in analysis: 31 (control 1: 12, control 2: 10, intervention: 9) Age: mean (range) = C1: 71.3 (64 to 81), C2: 72.5 (60 to 87), I: 72.9 (63 to 81) Gender: female: C1: 9 (75%), C2: 8 (80%), I: 6 (67%) Ethnicity: black (not white): C1: 8 (75%), C2: 9 (90%), I: 6 (67%) Number of medications: type not specified: mean ± SD: C1: 4.8 ± 2.2, C2: 3.8 ± 1.1, I: 5.1 ± 2.1 Frailty/Functional impairment: Medical Outcomes Study General Health Survey: physical function mean ± SD = C1: 52.8 ± 34.0, C2: 43.3 ± 29.6, I: 37.9 ± 31.7 Cognitive impairment: mean ± SD MMSE: C1: 27.2 ± 2.2, C2: 28.5 ± 1.0, I: 27.7 ± 1.8 Comorbidities: not specified
Interventions	Group 1 (intervention) ‐ Unit‐of‐use medication packaging and regimen simplification: medications in unit‐of‐use packages with twice‐daily dosing intervals (morning and evening). Medications in translucent plastic cups with translucent plastic snap‐on lids. Yellow label for AM, blue label for PM Group 2 (control 1) ‐ Usual care: medications in conventional packaging and no change to dosing interval Group 3 (control 2) ‐ Regimen simplification: medications in conventional packaging but dosing intervals made twice daily (morning and night) using 2 clear plastic zip‐lock bags. Co‐intervention: all medications packaged individually by study pharmacist and dispensed monthly (33 days supply) Provider: pharmacist Where: ambulatory clinic/home When and how often: monthly (medications resupplied monthly) Intervention personalised: no
Outcomes	Timing of outcome assessment: 6 months (assessed monthly) Medication adherence (objective) : pill count: percentage compliant (note over‐adherence expressed as under‐adherence, e.g. 90% not 110%). Scale 0 to 100 Adverse clinical health outcomes (subjective): asked: "Have you had any side effects, ill effects, or any other problems caused by medications you have taken? (yes/no)"
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: Health Foundation of Greater Indianapolis Dropout: 4 withdrew, 1 was lost to follow‐up
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Not specified
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	No blinding of pharmacist who delivered the intervention and collected outcome data
Blinding of outcome assessment (detection bias) All outcomes	High risk	No blinding of pharmacist who delivered the intervention and collected outcome data
Incomplete outcome data (attrition bias) All outcomes	High risk	5 people missing (16%): 3 from intervention group (25%), 1 NH, 3 returned to prior regimen, 1 disliked unit‐of‐use packaging
Selective reporting (reporting bias)	High risk	Compliance measured in 4 ways; subjective not reported at follow‐up; results in abstract not matching main paper
Other bias	Unclear risk	No power calculation. Small sample size in each group. Groups not particularly well matched (e.g. mean number of drugs). Pill counts occurred in the pharmacy ‐ patients may not have returned all meds, and this be more of an issue with unit‐of‐use packaging (a bag for empty containers was provided, but it is possible that containers were discarded and % containers returned was not reported)

Muth 2016.

Study characteristics
Methods	Aim of study: to test the feasibility of an intervention and cluster‐RCT study design for an intervention designed to improve medication appropriateness and adherence in elderly patients with multi‐morbidity Study design: cluster‐RCT (20 GP practices; unit of allocation: practice) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Germany Setting: primary care clinic (GP practices) Inclusion criteria: GPs: provision of primary care within German statutory health insurance system, healthcare assistant could access Internet. Patients: ≥ 65 years, ≥ 3 chronic conditions, ≥ 5 long‐term prescriptions, ≥ 1 practice visit in past quarter, ability to fill in questionnaire and participate in telephone interviews Exclusion criteria: Patients: MMSE < 26, life expectancy ≤ 6 months, alcohol and drug abuse (based on GP assessment) Number of participants randomised: 100 Number of participants included in analysis: 100 ITT (94 as per abstract) Age: mean ± SD 75.8 ± 6.7 vs 75.2 ± 5.88 Gender: female: 28 (56%) vs 24 (48%) Ethnicity: not specified Number of medications: long‐term prescriptions: 9.5 ± 2.67 vs 8.7 ± 2.66 Frailty/Functional impairment: falls: 7 (14%) vs 6 (12%), 94% intervention and 92% control were "fending for themselves", which presumably means they were independently functioning Cognitive impairment: excluded MMSE < 26, MMSE data not reported Comorbidities: mean ± SD Schafer et al, count of chronic diseases: 8.4 ± 2.52 vs 7.0 ± 2.62; Charlson score: 4.5 ± 2.64 vs 4.5 ± 2.46
Interventions	Group 1 ‐ Prioritising Multimedication in Multimorbidity in general practices (PRIMUMpilot): intervention group received a brown bag review and a checklist‐based pre‐consultation interview with patient and healthcare assistant to detect potential medication issues and non‐adherence; then a computer‐assisted medication review was carried out by GP along with GP‐patient consultation Group 2 ‐ Usual care (not described) Co‐intervention: both groups of GPs received practice guidelines for older patients Provider: GP with assistance from healthcare assistants Where: GP clinic When and how often: once at baseline Intervention personalised: yes ‐ tailored to individual medications
Outcomes	Timing of outcome assessment: baseline (0 weeks) and 12 weeks Medication adherence (subjective) : Morisky adherence: validated questionnaire; 4 items resulting in sum scores of 0 to 4 with low scores indicating good adherence Medication adherence (subjective) : Medication Adherence Rating Scale (MARS): validated questionnaire; 5 items resulting in sum score 5 to 25, with high scores indicating good adherence Medication adherence (subjective) : discrepancy between medicines patients reported actually taking (at patient interview) and medicines prescribed (reported by GP). Three domains: drug score, dose score, and regimen score. Scores outside of 0.8 to 1.2 considered deviant. Unsure if validated Health‐related quality of life (subjective): EQ‐5D Adverse clinical health outcomes (subjective): number of days in hospital
Notes	Trial registration: ISRCTN99691973 Consumer involvement: not specified Funding source: German Federal Ministry of Education and Research, Grant no. 01GK0702 Dropout: 1 hospitalised, 7 lost to follow‐up (5 and 2) ICC for adherence reported as 0.000; thus no need to recalculate results
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Allocation sequence generated by an external researcher using the random number generator of Microsoft Excel
Allocation concealment (selection bias)	Low risk	Treatment allocation was concealed to practices and patients until data collection at baseline had been completed
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded ‐ participants could not be blinded
Blinding of outcome assessment (detection bias) All outcomes	High risk	Not blinded ‐ adherence assessment was not blinded
Incomplete outcome data (attrition bias) All outcomes	High risk	Significant quantity of missing data for adherence measures; reasons not adequately explained
Selective reporting (reporting bias)	Low risk	All outcomes reported as per methods
Other bias	Low risk	Aim for 100 patients (50:50), 10 GPs, 5 patients per cluster Recruitment bias (selective recruitment of cluster participants): low risk; treatment allocation was concealed to practices and patients until data collection at baseline (and thus recruitment) had been completed

Nascimento 2016.

Study characteristics
Methods	Aim of study: to evaluate improvement in diabetes self‐care (including adherence) after an individualised pharmacotherapy management service (home medication review and therapeutic education) in elderly patients Study design: RCT (unit of allocation: individual) Number of arms/groups: 2
Participants	Description: both patient/consumer and carer Geographic location: Portugal Setting: diabetes care clinic and patient's home Inclusion criteria: T2DM, ≥ 65 years, HbA1c ≥ 7.5% Exclusion criteria: (unclear) cancer, cognitive impairment or other condition that could "hinder communication" unless they could submit a caregiver Number of participants randomised: 90 Number of participants included in analysis: 87 (44 and 43) Age: mean ± SD: 74.2 ± 5.4 vs 72.3 ± 4.5 Gender: female: 43.2% vs 41.9% Ethnicity: not specified Number of medications: type not specified: 6.86 ± 3.32 vs 5.84 ± 2.76 Frailty/Functional impairment: not specified Cognitive impairment: cognitive impairment ‐ needed carer Comorbidities: no total score given
Interventions	Group 1 ‐ Pharmacotherapy management service for T2DM elderly patients: individualized pharmacotherapy management service at home, including analysis of necessity, safety, and effectiveness of medications taken. Also received individualised therapeutic education on diabetes care especially pharmacotherapy. Unclear whether med review and education were limited to diabetes medications only or included all medications Group 2 ‐ Usual care: standard medical care consultation (no details) Co‐intervention: N/A Provider: not specified ‐? Pharmacist Where: home When and how often: once at baseline (no details) Intervention personalised: yes ‐ individual medication review
Outcomes	Timing of outcome assessment: baseline and 6 months Medication adherence (subjective) : Medida de Adesao aos Traamentos (ref 68), a validated Portuguese/Spanish measure based on Morisky Green Test: average level of adherence to drug therapy ‐ 7 questions, on 0 to 6 scale, with 6 being highest adherence Condition specific outcomes (objective): fasting blood glucose in mg/dL and glycosylated haemoglobin (HbA1c)
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: funded in part by DGS Dropout: 3 lost to follow‐up Unpublished data: mean medications: control = 5.84 ± 2.76, intervention = 6.86 ± 3.32; adherence assessed for all medications, not just diabetes medications; adherence measured using a Spanish tool that is based on Morisky
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Method of randomisation not explicitly reported, but the way it is described raises suspicion that it could have been alternating allocation, hence not random ("were randomised into a control and an intervention group, for a consecutive sampling")
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Clinical data accessed by an Independent clinical laboratory ‐ unsure if blinded
Incomplete outcome data (attrition bias) All outcomes	Low risk	90 randomised, 87 completed. No reasons given, but attrition small
Selective reporting (reporting bias)	Unclear risk	Methods unclear; method of assessing adherence mentioned at end, near conclusion
Other bias	Unclear risk	Method is very brief, making assessment of rigour and bias very difficult. Adherence assessment and analysis methods are unclear

Naunton 2003.

Study characteristics
Methods	Aim of study: to evaluate pharmacist‐conducted post‐discharge follow‐up at home of high‐risk elderly patients on various outcomes (including adherence) Study design: RCT (unit of allocation: individual) Number of arms/groups: 2
Participants	Description: both patient/consumer and carer Geographic location: Australia Setting: home (post discharge) Inclusion criteria: ≥ 60 years, ≥ 2 chronic medical conditions requiring medication (≥ 1 of HF, IHD, COPD, or DM), ≥ 4 prescribed regular medications Exclusion criteria: lived in domiciliary care facility or beyond greater Hobart area, were to be visited at home by a community nurse within 5 days of discharge, had terminal malignancy, were unable to provide informed consent Number of participants randomised: 136 Number of participants included in analysis: 121 (57 and 64) (unclear as number of participants alive at 90 days: 54 vs 59) Age: median (range): 74 (65 to 90) vs 77 (60 to 91) Gender: female: 56% vs 69% Ethnicity: not specified Number of medications: regular medications on discharge: median (range): 8 (3 to 15) vs 8 (3 to 16) Frailty/Functional impairment: nursing assistance at home: 28% vs 21% Cognitive impairment: not specified Comorbidities: chronic medical conditions: median (range) = 5 (2 to 9) vs 5 (2 to 13)
Interventions	Group 1 ‐ Pharmacist post‐discharge home visit: 5 days after discharge, patients visited at home by study pharmacists. Objective of visit was to educate, answer any queries, optimise medication management (e.g. Dosette or Webster, if necessary), improve compliance, detect DRPs, and improve liaison with community‐based health services. Brief letter composed in the patient's home was given to the patient to present to the doctor. Study pharmacist also called GP and community pharmacy to inform of study Group 2 ‐ Usual care (no specific post‐discharge follow‐up for this group) Co‐intervention: 89% in both groups were seen by hospital pharmacist before discharge Provider: pharmacist Where: home When and how often: once, 5 days after discharge Intervention personalised: yes ‐ based on adherence assessment at home visit; specific strategies were offered such as compliance aids, carer assistance, community nursing, etc.
Outcomes	Timing of outcome assessment: 90 days post discharge Medication adherence (subjective) : self‐reported missing doses: compliance defined as 'never miss medication'. Non‐compliance ‐ therefore any self‐reported missed doses (from 'rarely' to 'once a day'). Self‐reported 'never' forget to take their medication. 1 question ‐ "How often would you say you miss taking your pills?", with 7 response options from never to once a day. Presented as dichotomous variable adherent or not adherent. ? Not validated Satisfaction with intervention (subjective): satisfaction survey ‐ intervention group only Adverse clinical health outcomes (objective): deaths: % patients who died within 90 days of discharge. Retrospective medical record review and contact with family and/or GP Adverse clinical health outcomes (objective): unplanned hospital re‐admissions: % patients with 1 or more unplanned re‐admissions within 90 days of discharge (patients asked and retrospective medical records checked)
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: Abbott Australasia Pharmacy Research Grant, through SHPA Dropout: 2 withdrew (1 I, 1 C); 13 were lost to follow‐up (3 C died, 3 I and 2 C were uncontactable, 2 I and 1 C were admitted to nursing home, 2 I was admitted to intensive nursing care)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Randomised by study pharmacist using a computer‐generated list of random numbers
Allocation concealment (selection bias)	Low risk	Randomisation occurred after discharge from hospital and collection of baseline data
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded
Blinding of outcome assessment (detection bias) All outcomes	High risk	Not blinded post randomisation
Incomplete outcome data (attrition bias) All outcomes	Low risk	Good breakdown of excluded patients
Selective reporting (reporting bias)	Low risk	As described in methods
Other bias	Low risk	None apparent

Nazareth 2001.

Study characteristics
Methods	Aim of study: to evaluate the effectiveness of a co‐ordinated hospital and community pharmacy discharge care plan for elderly patients (75+) on ≥ 4 medications discharged from hospital Study design: RCT (4 hospitals; individual block randomisation) Number of arms/groups: 2
Participants	Description: both patient/consumer and carer Geographic location: UK Setting: hospital discharge (hospital and patient's home) Inclusion criteria: 75+ years, ≥ 4 medications, discharged home from elderly care wards (3 acute general and 1 long‐stay hospital) to a catchment area of the 4 participating hospitals Exclusion criteria: could not speak English, too ill (no definition) Number of participants randomised: 362 (181 and 181) Number of participants included in analysis: 6 months: 306 (149 vs 157), interviewed: 132 vs 135 Age: mean ± SD: 84 ± 5.2 vs 84 ± 5.4 Gender: female: 62% vs 66% Ethnicity: 97% white; not reported for individual groups but not significantly different Number of medications: oral prescribed medications at discharge: mean 6, SD 2 overall (not reported for individual groups, but not significantly different) Frailty/Functional impairment: not specified Cognitive impairment: MMSE ≤ 15 (n = 39) excluded from interview process Comorbidities: mean 3 chronic medical conditions (not reported for individual groups, but not significantly different)
Interventions	Group 1 ‐ Co‐ordinated hospital and community pharmacy discharge: hospital pharmacist pre‐discharge intervention: assessment of medication, rationalisation of drug treatment, assessment of patients' ability to manage their medication, provision of information on current drugs, and liaison with carers and community professionals (pharmacy, GP, etc., where appropriate). Written discharge plan given to patient, community pharmacist, and GP. Community pharmacist intervention: home visit at days 7 to 14 to check for discrepancies between what patient is taking vs that prescribed on discharge, assessment of patient knowledge ad adherence, patient counselling, removal of excess medications, and additional visits prn Group 2 ‐ Usual care: standard procedures. Discharge letter to GP. Pharmacists did not provide review of discharge medications nor community follow‐up (Unclear what services the hospital pharmacy did provide ‐ presumably some discharge counselling) Co‐intervention: N/A Provider: pharmacist (hospital and community) Where: discharge and home When and how often: pre‐discharge in hospital and at home 7 to 14 days after discharge Intervention personalised: yes (mostly standardised, but intervention tailored to address individual patient's medication management problems)
Outcomes	Timing of outcome assessment: baseline and 6 months Medication adherence (subjective) : self‐reported adherence: obtained through prescription medicine interview; adherence to prescribed drugs in the previous week; validated self‐report semi‐structured interview (adherence score is out of 1, with 1 being 'total/highest' adherence); mean (SD) out of 1 Knowledge about medicines (subjective): self‐reported medication knowledge: prescription medicine interview ‐ patient's knowledge of prescribed drugs; validated self‐report semi‐structured interview (knowledge score is out of 1, with 1 being 'total/highest' knowledge); mean (SD) out of 1 Satisfaction with intervention (subjective): validated patient satisfaction questionnaire ‐ each item scored 1 to 4; mean score per item calculated Adverse clinical health outcomes (objective): service usage: hospital re‐admission, death, outpatient department attendance, GP attendance. Data from hospital and GP surveys
Notes	Trial registration: ISRCTN66700837 Consumer involvement: not specified Funding source: National Health Service Research and Development programme on the primary/secondary care interface Dropout: 32 vs 24 died Fidelity: discharge plans were 'misplaced' for 36/181 patients, and 52/181 patients did not receive the home visit
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	After consent, independently randomised by health authority's central community pharmacy office using computer‐generated random numbers. Block randomisation, stratified by trial centre
Allocation concealment (selection bias)	Low risk	Randomisation done by an independent group after consent obtained
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Research assistant remained blinded to allocation or patient
Incomplete outcome data (attrition bias) All outcomes	High risk	High loss to follow‐up ‐ only 44% answered; 6‐month adherence
Selective reporting (reporting bias)	Low risk	As per methods
Other bias	High risk	Poor fidelity of the intervention: discharge plans were 'misplaced' for 36/181 patients, and 52/181 patients did not receive the home visit Sample size: "195 patients were required in each group" ‐ not reached

Olesen 2014.

Study characteristics
Methods	Aim of study: this paper: to investigate the impact of pharmaceutical care on medication adherence, hospitalisation, and mortality of home‐living elderly (65+) patients prescribed polypharmacy. Overall study aim also included a third arm designed to assess the impact of an electronic reminder device on adherence Study design: RCT (2‐arm results from 3‐arm RCT; individual allocation) Number of arms/groups: 3 (2 discussed)
Participants	Description: patient/consumer Geographic location: Denmark Setting: patient's home (community) Inclusion criteria: ≥ 65 years, ≥ 5 current prescription drugs taken without assistance Exclusion criteria: residence in a nursing home, terminal illness, cognitive disorders such as dementia, medication supervised by healthcare providers, immigration to Denmark after January 2005, and severe motor impairment. Patients hospitalised longer than 7 days during the study were excluded before the final adherence evaluation Number of participants randomised: 630 (315, 315) Number of participants included in analysis: 517 (253, 264) Age: median (IQR, range): 74 (70 to 80, 65 to 94) vs 74 (70 to 80, 65 to 91) Gender: female: 133 (53%) vs 134 (51%) Ethnicity: not specified (recent immigrants excluded) Number of medications: oral prescription medications: median (IQR, range): 7 (5 to 8, 1 to 16) vs 7 (5 to 8, 3 to 18) Note: only meds taken throughout the 12‐month study period were included in the adherence assessment Frailty/Functional impairment: not specified Cognitive impairment: cognitive impairment such as dementia excluded Comorbidities: not specified
Interventions	Group 1 ‐ Pharmaceutical care: pharmacist home visit to deliver patient education, motivation, and regimen simplification. There was also a medication review to identify DRPs, but this was a minor component. Pharmacist examined medicines list with regard to possible side effects, interactions, and administration, then tried to make the regimen less complex, informed patients meanwhile about the drugs, listened to questions concerning the drugs, handed over information leaflets, and motivated adherence. Phone call at 3, 6, and 9 months to inquire about patient's condition and changes in the medicine, to uncover problems, and to answer questions Group 2 ‐ Reminder device: patient was given an e‐reminder device the size of a mobile phone that beeps when medications are due, and patient presses a button to indicate medications are taken Group 3 ‐ Usual care: no intervention (not described) Co‐intervention: all groups had regular nurse home visits to collect data for medication counts Provider: pharmacist Where: home and telephone When and how often: home at baseline, phone call at 3, 6, and 9 months Intervention personalised: yes ‐ personalised based on medication, but broad intervention the same
Outcomes	Timing of outcome assessment: 12 months (adherence), 24 months (health outcomes) Medication adherence (objective) : pill count of oral prescription drugs. Nurse visited patients at baseline, 6 months, and 12 months to photograph pills, which were counted later by a 'counter pen' (combination of a marker and a digital camera). Adherence rate (%) per drug calculated as mean adherence rate during 1 year. < 80% pills taken as prescribed = non‐adherence (> 100% pills taken was regarded as 100%, i.e. adherent) Adverse clinical health outcomes (objective): unplanned hospital admissions to medical departments obtained from Danish e‐Health Portal Adverse clinical health outcomes (objective): mortality data obtained from hospital e‐journal (electronic hospital record that automatically records information on all deceased patients)
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: supported by the Danish Ministry of Health and the Association of Danish Pharmacies Dropout: excluded before intervention 31 and 31 (hospitalised or medications administered), withdrew 15 and 5 (lack of interest), lost to follow‐up 16 and 15 (outside region, no adherence count, died) Fidelity: poor ‐ adherence measured for only 48% of medications. No data provided regarding whether pharmacists delivered the intervention exactly as intended, nor whether all phone follow‐ups occurred Further information required:hospitalisation, mortality, and adherence data for electronic reminder group (email correspondence ‐ successful, but did not collect hospitalisation or mortality data; adherence was measured by a different method ‐ see Harbig 2012)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	945 envelopes prepared, with each containing a study inclusion code. Patients selected an envelope at first home visit ‐ inadequate details provided re randomisation method
Allocation concealment (selection bias)	Unclear risk	At first home visit by a project nurse, patients were asked to select 1 envelope. Unclear if opaque envelopes, or order, or if nurse had knowledge
Blinding of participants and personnel (performance bias) All outcomes	High risk	Impossible to conceal the identity of patients in the pharmaceutical care group
Blinding of outcome assessment (detection bias) All outcomes	High risk	Does not specify any blinding ‐ project nurse photographed pills to be counted later by a counter pen
Incomplete outcome data (attrition bias) All outcomes	High risk	Able to assess adherence for only 48% of medications; insufficient detail as to why hospitalised patients were excluded
Selective reporting (reporting bias)	High risk	Three‐arm study but only 2 arms described. Outcomes mostly per methods, although additional adherence calculations were conducted that were not specified in methods (e.g. within‐group comparisons). Harbig paper describes third arm adherence by a different method
Other bias	Low risk	None noted ‐ adherence was very high in the control group, leaving little room for improvement

Pandey 2017.

Study characteristics
Methods	Aim of study: to assess the impact of text message reminders on adherence to medications and exercise in patients recently discharged from the hospital after a myocardial infarction (MI) Study design: RCT (pilot single centre; individual allocation) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Canada Setting: hospital discharge to community Inclusion criteria: ≥ 18, discharged from hospital after MI in preceding 2 weeks and enrolled in a structured cardiac rehabilitation programme. Patients receiving treatment with medications from all 4 of the following classes: antiplatelets, BB, ACEI/A2RA, and statins Exclusion criteria: patients taking medications in dosing regimens > once daily, no mobile phone, unable to read and write in English or provide informed consent, those incarcerated Number of participants randomised: 34 Number of participants included in analysis: 33 (17 and 16) Age: 64.6 ± 11.5 vs 62.1 ± 11.0; subgroup > 65: 7 (41%) vs 8 (50%) Gender: 11 (65%) vs 2 (12%); not reported for subgroup Ethnicity: not specified Number of medications: cardiac (post‐MI) prescription medication: 10.1 ± 4.5 vs 8.0 ± 5.2; not reported for older subgroup Frailty/Functional impairment: not specified Cognitive impairment: dementia: 3 (18%) vs 2 (13%) Comorbidities: no total comorbidity score
Interventions	Group 1 ‐ Text message reminder: once‐daily text message at the time patient preferred to take medications. Text messages simply indicated that patient should remember to take medications and contained no identifiable information such as medication names or classes (e.g. "Please remember to take your morning medications now") Group 2 ‐ Usual care (no text message) Co‐intervention: all participants received outpatient cardiac rehab programme for 3 months and follow‐up assessment at 12 months Provider: automated (set up by cardiac rehab nurses, then automated to send daily) Where: via text message When and how often: daily for 12 months Intervention personalised: not really ‐ standard wording: "Please remember to take your morning medications now"; time of day was modified for patient
Outcomes	Timing of outcome assessment: 12 months Medication adherence (subjective) : self‐reported adherence: participants asked to use a logbook to record name and timing of medications taken on a daily basis. Logbooks were collected monthly. Absolute medication adherence was calculated as percentage of total prescribed doses that were actually taken each month. 12‐month adherence calculated as the mean of each of the 12 monthly measurements. Adherence outcome is % of days covered
Notes	Trial registration: NCT02783287 Consumer involvement: not specified Funding source: unclear; Brigham and Women's Hospital and University of Waterloo listed under sponsors and collaborators Dropout: 1 control withdrew
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Randomised by a web‐based random number generator in a 1:1 ratio
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Patients and their healthcare providers were aware of the arm to which they had been randomised
Blinding of outcome assessment (detection bias) All outcomes	High risk	Open‐label trial; no mention of blinding
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	Only 1 withdrew ‐ but may be relevant given low patient numbers, especially in older people subgroup
Selective reporting (reporting bias)	Low risk	As described in methods
Other bias	Unclear risk	Persistence with the 4 post‐MI medications not reported. Typically this is well below 100%, plus some medications may be stopped due to ADRs, etc. It is unlikely that no medications were stopped for any patients over 12 months. It is unclear how this was accounted for in the study

Pereles 1996.

Study characteristics
Methods	Aim of study: to determine the effect of an inpatient self‐medication programme (SMP) on the ability to self‐medicate, patient medication knowledge, compliance, and patient morale Study design: RCT (2 inpatient geriatric units, individual allocation) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Canada Setting: hospital (before discharge from inpatient geriatric units) Inclusion criteria: discharge home (community living), patient responsible for administration of own medication, MMSE ≥ 20, ability to give informed consent, medically stable condition Number of participants randomised: 107 (51 and 56) Number of participants included in analysis: unclear (107 for baseline, 74 for follow‐up) Age: mean SD 80 ± 7 vs 80 ± 7 Gender: female: 37 (73%) vs 48 (86%) Ethnicity: not specified Number of medications: medications/d: inpatient: 4.8 ± 3 vs 4.7 ± 2; discharge: 4.7 ± 3 vs 5.1 ± 4 Frailty/Functional impairment: not specified Cognitive impairment: MMSE < 20 excluded, MMSE 26 ± 3 Comorbidities: not specified
Interventions	Group 1 ‐ Inpatient self‐medication programme: three‐stage programme in which patient is given increasing responsibility for administration of his/her medications. (1) Patient is counselled by pharmacist and patient requests medications from nurses at appropriate times; (2) patient is given 24‐hour supply of medications to self‐administer. Advances to next stage if no errors after 3 to 5 days; (3) patient is given several days supply of medication. Average duration of program = 21.6 days (SD 19) Group 2 ‐ Usual care ‐ medications administered by nursing staff Co‐intervention: 72 hours before discharge, both groups received pharmacist assessment of knowledge and functional ability to manage medicines and pre‐discharge medication education from a pharmacist; both groups had a 20‐minute counselling session with a pharmacist Provider: pharmacist and nurse Where: inpatient geriatric unit (subacute, average LOS = 40 days) When and how often: before discharge, continuously for an average of 21.6 days Intervention personalised: yes ‐ to some extent, e.g. 41% intervention patients discharged with a Dosette (and 34% control patients)
Outcomes	Timing of outcome assessment: discharge and 40 days post discharge Medication adherence (objective) : pill count: patients discharged with 40 days worth of medication, pill count conducted in home at 40 days. Proportion of medication errors (? assumed missed doses but not explained) of total doses administered Medication‐taking ability (objective) : assessed differently for each group: intervention = 2 or fewer errors on stage 2 of SMP considered able to self‐medicate at discharge. Control = Pharmacist assessment at time of discharge counselling with input from other team members. YES/NO ‐ self‐medicating at discharge (note: there could be reasons other than failing the SMP that might explain why patients were not self‐medicating at discharge, such as patient preference) Knowledge about medicines (objective): "short medication knowledge questionnaire" = Patients asked to name and describe appearance and purpose of their medication, to describe their regimen and any potential side effects or drug interactions. % correct responses in each knowledge category
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: not specified Dropout: 1 refusal, 32 lost to follow‐up (19 C, 14 I) (5 deaths, 2 lost to follow‐up, 21 RACF, 4 other) Fidelity: 33 did not complete study protocol
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Not specified
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded (unable to blind)
Blinding of outcome assessment (detection bias) All outcomes	High risk	Medication ability not blinded (groups assessed differently); unclear whether adherence was blinded
Incomplete outcome data (attrition bias) All outcomes	High risk	33 did not complete the study; they were older, had lower MMSE, and had longer hospital stays
Selective reporting (reporting bias)	Low risk	Reported as per methods
Other bias	Unclear risk	Power analysis "suggested 48 patients in each group would be required"; loss to follow‐up meant required sample size was not maintained. 33 did not complete study protocol ‐ poor fidelity

Rich 1996.

Study characteristics
Methods	Aim of study: to evaluate the effect of a multi‐disciplinary treatment strategy on compliance rates for patients hospitalised with congestive heart failure Study design: RCT (substudy of larger RCT (Rich 1995); unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: hospital, discharge and post discharge in the home Inclusion criteria: aged 70+, admitted to hospital with CHF, at least 1 risk factor for early re‐admission Exclusion criteria: severe dementia (inability to assist with self‐care) or other serious psychiatric illness, limited life expectancy (3 months), discharge to RACF living outside catchment area Number of participants randomised: unclear Number of participants included in analysis: 156 (80 and 76) Age: mean ± SD 80.5 ± 5.7 vs 78.4 ± 6.1 Gender: female: 74% vs 59% Ethnicity: Caucasian: 40% vs 29% Number of medications: medications at discharge: 5.2 ± 2.4 vs 5.2 ± 2.5 Frailty/Functional impairment: ADL: 5.7 ± 1.1 vs 5.7 ± 0.8 Cognitive impairment: severe dementia excluded Comorbidities: no total comorbidity score
Interventions	Group 1 ‐ Multi‐disciplinary intervention for elderly people with CHF: education from study nurse about CHF and its management using a 15‐page teaching guide prepared by the study team. Patients seen daily by a study nurse throughout the remainder of their hospital stay; the importance of compliance with both medications and diet was emphasised repeatedly. Also visited by dietician and social service representative (who assisted in arranging appropriate post‐discharge care). Shortly before discharge, geriatric cardiologist reviewed medications and made recommendations to primary physician regarding simplification and consolidation. Following discharge, all patients seen by hospital's home care department and contacted regularly by study nurse Group 2 ‐ Usual care: conventional medical care + standard hospital services, including dietary teaching and pre‐discharge medication instructions Co‐intervention: N/A Provider: nurse (+ input from dietician and geriatric cardiologist) Where: hospital and home When and how often: during hospital, reinforced daily. Duration post discharge unclear Intervention personalised: yes
Outcomes	Timing of outcome assessment: 30 ± 2 days after discharge Medication adherence (objective) : pill count: performed for all current medications, presented dichotomously as compliant (≥ 80%) or non‐compliant Adverse clinical health outcomes (objective): hospital re‐admissions: number of people re‐admitted to hospital within 30 days of discharge
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: National Heart, Lung and Blood Institute grant Dropout: unclear
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Allocated based on terminal digit of a computer‐generated sequence of random numbers (i.e. even or odd)
Allocation concealment (selection bias)	Low risk	Neither patients nor investigators were aware of treatment assignment until after randomisation
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Pill count by experienced clinical pharmacist or trained pharmacy assistant blinded to treatment assignment
Incomplete outcome data (attrition bias) All outcomes	Low risk	No loss to follow‐up reported; ITT
Selective reporting (reporting bias)	Low risk	Reported as per methods, except for additional measure of adherence (> 80%)
Other bias	Unclear risk	Unclear whether adherence assessment was for all medications or only for cardiac medications, which were the focus of this study

Saez de la Fuente 2011.

Study characteristics
Methods	Aim of study: to evaluate the utility of a pharmacotherapeutic information programme at hospital discharge in polymedicated patients and the profile of modifications in treatment of the patient at 30 to 50 days of hospital discharge Study design: RCT (unit of allocation: individual) Number of arms/groups: 2
Participants	Description: both patient/consumer and carer Geographic location: Spain Setting: hospital discharge Inclusion criteria: using prescription medications for 3 or more months, ≥ 4 active ingredients at discharge Exclusion criteria: transfer to geriatric residence, dementia and/or psychiatric illness, incapacitated in the absence of a caregiver responsible for medication at the time of the interview, Barthel Index < 20 Number of participants randomised: 59 (29 and 30) Number of participants included in analysis: 50 (26 and 24) (but methods says ITT) Age: median (range): 73 (28 to 93) vs 75 (14 to 96) Gender: female n (%): 10 (34.5%) vs 11 (36.7%) Ethnicity: not specified Number of medications: median (IQR): active ingredients/patient at discharge: 8.3 (7.4 to 9.3) vs 7.6 (6.5 to 8.7); pharmaceutical forms/patient: 7.9 (7.1 to 8.8) vs 7.1 (6.0 to 8.1) Frailty/Functional impairment: Barthel Index: median (IQR) 100 (85 to 100) vs 100 (65 to 100) Cognitive impairment: dementia/psychiatric illness: 8 (26.7%) vs 8 (26.7%) Comorbidities: not specified
Interventions	Group 1 ‐ Pharmacotherapeutic discharge information programme: verbal and written information about treatment at hospital discharge ‐ unclear who provided information, suspect pharmacist (as pharmacist conducted interview). Format and content unclear Group 2 ‐ Usual care ‐ no discharge information provided Co‐intervention: N/A Provider: unclear ‐? Pharmacist Where: discharge from hospital When and how often: once, pre‐discharge Intervention personalised: yes (info provided presumably tailored to individual medication regimen)
Outcomes	Timing of outcome assessment: discharge and 30 to 50 days (mean 42.1, SD 9.6 days) Medication adherence (subjective): Morisky‐Green Medication Compliance: 4 questions: (1) Do you ever forget to take the medications, yes or no? (2) Take the medicines at the indicated time, yes or no? (3) When you feel better, do you stop taking the medication, yes or no? (4) If you sometimes feel worse when taking your medication, do you stop taking the medication, yes or no? ==> To consider good adherence, the response of all questions must be adequate (no, yes, no, no) Adverse clinical health outcomes (objective): deaths: number of deaths during follow‐up Adverse clinical health outcomes (subjective): ED and hospital admissions: telephone questionnaire ‐ number of ED or hospital re‐admissions during follow‐up
Notes	Trial registration: not specified Consumer involvement: not specified Funding source: not specified Dropout: 9 lost to follow up (3 died, 5 in hospital, 1 moved) Note: caregiver at discharge: 15 (57.7%) vs 17 (70.8%) Language translation: yes ‐ translated to English
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	At the time of discharge, patients were distributed randomly in 2 groups by a block method with a 1: 1 ratio between groups
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Patients not blinded; unclear about personnel
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Pharmacist was interviewer. At the time of the telephone interview, the interviewer was unaware of treatment of the patient, as well as the previous result of adherence to discharge
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	Minimal dropout; unclear why those in hospital were not counted as re‐admissions
Selective reporting (reporting bias)	Low risk	Appears per protocol
Other bias	Low risk	None apparent

Shimp 2012.

Study characteristics
Methods	Aim of study: to evaluate a patient‐centred employer‐based medication therapy management (MTM) programme Study design: RCT (unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: community (University) Inclusion criteria: University of Michigan beneficiaries (employees, retirees, and their dependents), taking ≥ 7 prescription medications. Patients with a University of Michigan primary care provider were preferentially invited Number of participants randomised: 133 (intervention); "a similar number who consented but were not invited formed control" Number of participants included in analysis: 128 (intervention) Age: mean age: 70 years (intervention) Gender: 55% female (intervention) Ethnicity: not specified Number of medications: prescription medications: 9.2 ± 3.2 (intervention) Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: 3 ± 1.4 medical conditions (intervention)
Interventions	Group 1 ‐ Focus on Medicines (FOM) Medication Therapy Management (MTM): 2 face‐to‐face meetings with University of Michigan clinical pharmacists. First visit was comprehensive review of all medications. Patients with DM, HT, dyslipidaemia, asthma, arthritis, chronic pain, and OP were asked disease‐specific questions. Patient questions were answered. Second visit patient and pharmacist discussed recommendations and a medication action plan (MAP). This detailed DRPs, recommended actions, and person responsible Group 2 ‐ No intervention Co‐intervention: N/A Provider: pharmacist Where: unclear ‐ University or home ? When and how often: twice, unsure of timing Intervention personalised: yes ‐ patient‐centred medication action plan
Outcomes	Timing of outcome assessment: baseline (1 year pre‐study) and final (1 year post study) Medication adherence (objective) : medication possession ratio: MPR defined as sum of all days of medication supply received during 1 year pre‐study and 1 year post‐study periods, divided by the total number of days supply needed during 365 days. MPR calculated for top 8 drug classes for chronic conditions
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: University of Michigan Dropout: 5 withdrew Further information required: raw data on MRPs (author correspondence successful, but no further data were available; study authors said "results showed no significant change")
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	High risk	Not specified; those who agreed to participate compared with similar number of individuals meeting selection criteria but not invited to participate (control group)
Allocation concealment (selection bias)	High risk	Not specified ‐ patients randomly selected by study team ?
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded
Blinding of outcome assessment (detection bias) All outcomes	High risk	Not blinded
Incomplete outcome data (attrition bias) All outcomes	High risk	No details on attrition of control group, etc. Would assume some people would change jobs
Selective reporting (reporting bias)	High risk	Adherence outcomes ‐ both BMQ and Treatment Satisfaction Questionnaire for Medication ‐ not included despite being a main outcome and listed in methods
Other bias	Unclear risk	Funded by University of Michigan; preference given to people with primary practitioner who worked at University of Michigan

Shively 2013.

Study characteristics
Methods	Aim of study: to determine the efficacy of a patient activation (Heart PACT) intervention compared with usual care on activation, self‐care management, hospitalisations, and emergency department visits in patients at high risk of re‐admission/hospitalisation for HF Study design: RCT (repeated measure design; unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: Veterans Affairs Healthcare System (single site) Inclusion criteria: document clinical HF stage C, incident hospitalisation or ED visit for HF treatment within previous 12 months, ≥ 18 years, live in San Diego County, read and speak English, telephone access, has a primary care provider Exclusion criteria: inability to provide written consent, acute medical problems within previous month, considered by investigators to be medically unstable, enrolled in speciality HF programme or telehealth or had long‐term follow‐up by cardiology after hospital admission, severe medical problems, life expectancy < 1 year, acute substance abuse, psychiatric problems, homelessness Number of participants randomised: 84 (43 vs 41) Number of participants included in analysis: 6 months: 68 (34 vs 34) Age: grouped: mean ± SD 66.1 ± 10.76, range 42 to 89 (intervention: 63.4 ± 9.10, control: 68.9 ± 11.73) Gender: 1 female (1.2%) (0 vs 1) Ethnicity: white: 76.7% vs 78.0% (other races not extracted) Number of medications: trial author reported all > 4 medications (unpublished) Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: 71% reported ≥ 3 comorbidities
Interventions	Group 1 ‐ Patient activation (Heart PACT): 6‐month activation/Heart PACT programme developed to enhance self‐management. Intervention used activation theory and was tailored to each participant's activation level. At each meeting/telephone call, goals and progress toward attaining these were discussed (Figure 2). Also received a self‐management tool kit (BP cuff, weight scale, pedometer, HF self‐management DVD, and educational booklet) Group 2‐ Usual care ‐ general medical care and any HF‐specific clinical care from primary care provider. Received self‐management toolkit after final assessment (6 months) Co‐intervention: 2‐hour baseline outcome assessment Provider: nurse (advanced practice nurse) Where: telephone and F2F. Unclear location ‐ assume at clinic When and how often: 6 sessions over 6 months Intervention personalised: yes ‐ personalised based on activation level
Outcomes	Timing of outcome assessment: baseline and 6 months Medication adherence (subjective) : self‐reported medication adherence: medication adherence (as part of MOS‐specific adherence scale). "Took medications as prescribed (on time without skipping dose) in the past 4 weeks". Responses from 0 to 5, transformed to a 0 to 100 scale Adverse clinical health outcomes (subjective): self‐reported hospitalisations: patients asked to report any hospitalisations, ED visits, and other unscheduled visits including reason for visit and treatment. Results reported as mean (SD)
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service, project 04‐252 Dropout: no details provided Unpublished data: trial author reported that participants were on > 4 medications; most had minimum of 12 medications and 3 comorbid conditions
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Stratified block randomisation approach, based on baseline activation, was used to ensure patients were equally distributed. No other details regarding randomisation were provided
Allocation concealment (selection bias)	Unclear risk	Randomly assigned after baseline assessment ‐ unclear who was allocated or if concealed
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Not clear if outcome assessors were blinded
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	Missing completely at random (MCAR) analysis completed but not reported. Attrition rate 19%
Selective reporting (reporting bias)	Low risk	As per methods
Other bias	Unclear risk	Participants received $10 at baseline and at 3 months, $20 at 6 months

Taylor 2003.

Study characteristics
Methods	Aim of study: to determine the effect of pharmaceutical care on prevention, detection, and resolution of drug‐related problems in high‐risk patients in a rural community Study design: RCT (3 clinics; unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: primary care clinic (family medicine clinics ‐ rural) Inclusion criteria: adults (18+) at high risk for medication‐related adverse events (presence of 3 or more risk factors: ≥ 5 medications, ≥ 12 doses/d, ≥ 4 medication changes in previous year, ≥ 3 concurrent diseases, history of non‐compliance, presence of drugs requiring therapeutic monitoring) attending a participating clinic Exclusion criteria: significant cognitive impairment, history of missed office visits, scheduling conflicts, life expectancy < 1 year Number of participants randomised: 81 Number of participants included in analysis: 69 (33 and 36) Age: 64.4 ± 13.7 vs 66.7 ± 12.3 (P = 0.467) Gender: female: 63.6% vs 72.2% Ethnicity: white: 60.6% vs 61.1% Number of medications: type not specified, 6.3 ± 2.2 vs 5.7 ± 1.7 Frailty/Functional impairment: not specified Cognitive impairment: significant cognitive impairment excluded Comorbidities: ≥ 3 concurrent diseases ‐ inclusion criterion
Interventions	Group 1 ‐ Outpatient pharmaceutical care: standard medical care + pharmaceutical care. Pharmaceutical care (~ 20 minutes) occurred with a pharmacist, before seeing physician at regularly scheduled office visits. Pharmacists evaluated indication, effectiveness, dosage, correctness and practicality of directions, drug‐drug interactions, drug‐disease interactions, therapeutic duplication, duration of treatment, untreated indications, and expense. Pharmacist reviewed medical record, conducted a chart review, and examined medication history to determine compliance with and complications of medications and provided comprehensive individualised patient education that included a brief review of the disease, important lifestyle modifications, and basic drug information. Therapeutic recommendations were communicated to physicians through discussions and progress notes Group 2 ‐ Usual care: standard medical care (assume no pharmaceutical care during clinic visits) Co‐intervention: both groups received baseline and follow‐up interviews with pharmacist. Information collected included compliance, presence of medication misadventures, and medication knowledge Provider: pharmacist Where: medical clinic When and how often: continuous for 1 year at scheduled clinic visits Intervention personalised: yes
Outcomes	Timing of outcome assessment: baseline and 12 months Medication adherence (subjective) : self‐reported compliance: percentage of patients with medication compliance scores of 80% to 100%. Calculated by asking the patient the number of medication doses missed during the past week or month and dividing the estimated number of doses taken by the total number of doses prescribed Knowledge about medicines (objective): self‐reports used to assess medication knowledge during each pharmacist‐patient encounter. A knowledge score was determined by dividing the number of medications for which a patient reported the correct name, purpose, dose, and frequency by the total number of medications and multiplying by 100 Satisfaction with intervention (subjective): patient satisfaction with pharmacy‐related services, survey Health‐related quality of life (subjective): SF‐36 health survey Adverse clinical health outcomes (objective): ED and hospital visits: numbers of emergency department visits and hospitalisations for each patient during preceding year ‐ medical record audit Condition‐specific outcomes (objective): clinical markers of disease: number of people reaching goal level of BP ≤ 140/90, DM:HbA1c ≤ 7.5%, INR 2 to 3, and lipids LDL concentrations Other (subjective): patients with at least 1 medication misadventure
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: ASHP Research and Education Foundation Dropout: 3 intervention refused, 6 lost to follow‐up (3 and 3), 3 died (2 and 1)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Patients were randomly assigned to a control group or an intervention group; no details on randomisation sequence
Allocation concealment (selection bias)	Unclear risk	Not specified; order of consent/allocation unclear
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded due to nature of intervention
Blinding of outcome assessment (detection bias) All outcomes	High risk	No mention of blinding; may have impacted reporting of outcomes
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	12 (14.8%) lost to follow‐up; no mention if characteristics similar
Selective reporting (reporting bias)	Low risk	Reported as per methods
Other bias	Low risk	None apparent

Truelove 2015.

Study characteristics
Methods	Aim of study: to determine whether fixed‐dose combinations of generic drugs ('polypills') would promote use of optimal preventative drugs Study design: RCT Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Australia Setting: primary care clinic (general practices or aboriginal medical services) Inclusion criteria: established CVD (MI, stroke, or PVD = secondary prevention group) or 5‐year CVD risk ≥ 15% using Framingham‐based calculation (=primary prevention group), enrolling doctor had to be satisfied that each medication was clearly indicated and no contraindication Exclusion criteria: contraindication to any component of polypill, responsible clinician feels change to current therapy will place patient at risk Number of participants randomised: 623 (311 and 312) Number of participants included in analysis: 609 (304 and 305), subgroup of more than 8 meds: 202 Age: more than 8 meds subgroup = 66.4 years ± 11.4 years Gender: 41.6% female Ethnicity: not specified Number of medications: > 8 prescription medications subgroup Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: not specified
Interventions	Group 1 ‐ Polypill: all previous CV medications stopped and started on a polypill (Version 1 aspirin 75 mg, simvastatin 40 mg, lisinopril 10 mg, atenolol 50 mg; Version 2 aspirin 75 mg, simvastatin 40 mg, lisinopril 10 mg, HCT 12.5 mg) Group 2 ‐ Same medications but no polypill (i.e. usual care) Co‐intervention: N/A N/A ‐ Doctors given complete treatment autonomy after randomisation. Both polypill and usual medications dispensed from designated pharmacies with same out‐of‐pocket costs Provider: GP prescribed Where: general practice or aboriginal medical centre When and how often: continuous unless stopped by GP or patient Intervention personalised: not really ‐ 2 versions of polypill. Otherwise no personalisation
Outcomes	Timing of outcome assessment: baseline, 1 month, then at 6 monthly intervals for 18 months Medication adherence (subjective) : self‐reported use of combination treatment (≥ 2 BP‐lowering medications: an antiplatelet and a statin). Patient must have reported taking each component medication on at least 4 of the 7 preceding days. This captures combined effect of changes by healthcare provider and patient adherence
Notes	Trial registration: ACTRN126080005833347 Consumer involvement: not specified Funding source: NHMRC of Australia Fidelity: 62.4% still taking polypill at end of study (suggesting there had been many GP/patient changes during study) Dropout: 6 refused (3 and 3), 2 died (1 and 1), 6 missing/unable to contact (3 and 3)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Central, computer‐based randomisation service. Stratified by study centre, indication, and prescription of all appropriate therapies at baseline (yes vs no)
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unable to blind; designed as an open trial
Blinding of outcome assessment (detection bias) All outcomes	High risk	Blinded endpoints but adherence was self‐reported, so unable to blind this outcome
Incomplete outcome data (attrition bias) All outcomes	High risk	97.7% and 97.8% completed, but only 62.4% taking polypill at end of study
Selective reporting (reporting bias)	Low risk	As per methods
Other bias	Unclear risk	Trial study sample size calculation 1000; only 623 recruited due to insufficient resources. Only 62.4% taking polypill at end may indicate poor fidelity

Vinluan 2015.

Study characteristics
Methods	Aim of study: to evaluate the effect of pharmacist discharge counselling on patient adherence to heart failure (HF) therapy among an elderly US population and to assess hospital re‐admission rates Study design: RCT Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: hospital discharge Inclusion criteria: ≥ 65 years admitted with a new diagnosis of HF or already had diagnosis and were re‐admitted with HF exacerbation, prescribed ≥ 5 medications at discharge Exclusion criteria: living in long‐term care facility, hearing or cognitive impairment, could not communicate in English, did not manage own medications, lacked a telephone, unable to give informed consent Number of participants randomised: 16 (7 and 9) Number of participants included in analysis: adherence: 2 and 2, hospitalisation: 7 and 9 Age: 74 ± 5.9 vs 71 ± 6.9 Gender: female 86% vs 78% Ethnicity: not specified Number of medications: long‐term/regular medications: 8.1 ± 2.9 vs 8.3 ± 2.2 Frailty/Functional impairment: not specified Cognitive impairment: cognitive impairment excluded Comorbidities: total number not specified
Interventions	Group 1 ‐ Pharmaceutical discharge HF counselling: individual inpatient counselling by a pharmacist and telephone call follow‐up with review of current medications and HF counselling after discharge at days 3, 30, 60, and 90 Group 2 ‐ Usual care: regular care by nurses (including discharge counselling using generated d/c med list and HF handout) Co‐intervention: pharmacist performed a comprehensive review of inpatient HF medication regimen for all patients to ensure appropriate therapy was initiated; reviewed drug interactions, drug‐disease interactions, and duplicate therapy Provider: pharmacist Where: hospital and telephone When and how often: hospital at baseline, telephone days 3, 30, 60, and 90 Intervention personalised: yes
Outcomes	Timing of outcome assessment: 90 days post discharge Medication adherence (objective) : prescription refill history from community pharmacy, percentage of participants adherent Adverse clinical health outcomes (subjective): rehospitalisation: patient asked number of hospital admissions within 90 days after hospital discharge. Number of deaths also collected (source ?)
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: nil funding Dropout: details not specified, but for adherence 14 dropouts (7 and 7)
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Simple randomisation was performed using envelopes created by an outside affiliate with an assigned number inside
Allocation concealment (selection bias)	Low risk	Sealed envelopes opened in front of only patient and pharmacist once patient agreed to participate
Blinding of participants and personnel (performance bias) All outcomes	High risk	Unable to blind; unclear if this would impact outcomes
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Self‐reported patient outcomes; unclear if blinded or not for pharmacist and refill history
Incomplete outcome data (attrition bias) All outcomes	High risk	Massive attrition ‐ unable to reach by phone. Also said 7 and 7 lost to follow‐up but still reported 2 and 2 (should be 0 and 2) ?
Selective reporting (reporting bias)	High risk	Stated rehospitalisation data obtained from patients during phone calls. However, researchers have data for all participants. Also unclear how death data were obtained
Other bias	Low risk	None apparent

Volume 2001.

Study characteristics
Methods	Aim of study: to describe changes in patients' adherence to therapy regimens, patients' expectations of the care they receive from their pharmacist, patients' satisfaction with pharmacy services, and patients' HRQoL after provision of pharmaceutical care Study design: cluster‐RCT (16 pharmacies; cluster unit of allocation: pharmacy) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Canada Setting: community pharmacy Inclusion criteria: coverage of medications under Alberta Health & Wellness senior drug benefit plan (age ≥ 65 years), ≥ 3 medications according to dispensing records, able to complete telephone interviews, residing in Alberta for 12 of 15 study months, agree to get prescriptions from study pharmacy (Kassam 2001) Exclusion criteria: communication and language barriers, terminal disease, unable to provide informed consent Number of participants randomised: 16 pharmacies (8 vs 8), 363 patients (159 vs 204) Number of participants included in analysis: 292 completed Age: 73.89 ± 6.09 vs 73.18 ± 6.11 Gender: female: 63.5% vs 69.6% Ethnicity: not specified Number of medications: prescription: 4.67 ± 2.82 vs 3.90 ± 2.49. Non‐prescription: 0.63 ± 0.92 vs 0.73 ± 1.17 Frailty/Functional impairment: not specified Cognitive impairment: not specified Comorbidities: not specified
Interventions	Group 1 ‐ Pharmaceutical care research and education project (PREP): comprehensive pharmaceutical care. Treatment pharmacists (enrolled in an intensive education programme) used the Pharmacist's Management of Drug‐Related Problems (PMDRP) instrument to summarise information collected during patient interview and used SOAP (subjective, objective, assessment, and plan) record to document actions and follow‐ups Group 2 ‐ Usual care: control pharmacists not told which patients had or had not agreed to participate Co‐intervention: N/A Provider: pharmacists (community) Where: community pharmacies When and how often: 1 interview with frequent follow‐up Intervention personalised: yes ‐ based on interview and required pharmaceutical care
Outcomes	Timing of outcome assessment: baseline and 12 to 13 months Medication adherence (subjective) : Morisky self‐reported adherence: adherence to medication regimens assessed using a 4‐item self‐report Morisky (validated) measure. Summing numerical values for each answer provides a summary adherence score ranging from 0 to 4, with lower scores indicating better adherence Satisfaction with intervention (subjective): patient satisfaction with pharmacy services using 34‐item instrument based on work by MacKeidan and Larson and Johnson et al; 7‐point Likert scale used, with 1 indicating highest satisfaction. Only general satisfaction extracted Health‐related quality of life (subjective): SF‐36 health survey, validated
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: Alberta Ministry of Health, Alberta Pharmaceutical Association, University of Alberta Central Research Fund, Merck Frosst Canada, Hoechst Marion Roussel, Alberta Health‐Health Services Research Innovation Fund; drug references for pharmacists were provided by Bristol‐Myers Squibb Dropout: unclear: 5 treatment and 7 control pharmacies supplied patient data; 3 treatment and 1 control never recruited patients ICC not reported, numbers of participants in intervention and control groups at follow‐up unclear. Trial authors contacted for more information but no response. Thus unit of analysis error exists
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	High risk	Pharmacies paired based on Statistics Canada median income for first 3 digits of pharmacy's postal code. Study statistician did not know the identity of pharmacies and randomly assigned pharmacies to treatment or control within the pair. One pair were very closely located, thus assigned to same treatment/control to minimise contamination. Unclear why groups still balanced (8 and 8)
Allocation concealment (selection bias)	Unclear risk	Statistician did not know identity of pharmacies but took steps to minimise contamination and match characteristics
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not possible to blind patients to intervention; control pharmacists not told which patients had or had not agreed to participate
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Telephone survey by Population Research Lab at the University ‐ unclear whether blinded
Incomplete outcome data (attrition bias) All outcomes	High risk	Only patients with data at all 3 time points were included in the analysis; T1 = 363, T2 = 292
Selective reporting (reporting bias)	Low risk	Appears to be presented as per methods
Other bias	Unclear risk	"We intended that each pharmacy would identify enough to produce sample of 50 participants" ‐ not reached, sample size based on HRQoL Recruitment bias (selective recruitment of cluster participants): high risk, patient recruitment occurred after allocation of clusters, resulting in potential for recruitment bias; "it is possible that pharmacists selected patients whom they believed would benefit from the intervention or who had a more positive attitude toward pharmaceutical care"

Willeboordse 2017.

Study characteristics
Methods	Aim of study: to investigate effectiveness of clinical medication reviews (CMRs) for quality of life and geriatric problems in comparison with usual care in older patients with geriatric problems in general practice Study design: cluster‐RCT (22 general practices; cluster unit of allocation: GP practice) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: the Netherlands Setting: primary care clinic (general practice clinics) Inclusion criteria: PRACTICE: inclusion = all GP practices members of Academic Network of GPs. Practice not performing CMRs on a regular basis and would not start doing if randomised to control. PARTICIPANTS: inclusion = ≥ 65, newly presented with a geriatric problem in general practice, and used ≥ 1 prescribed drug long term (≥ 3 months). Geriatric problems identified by screening electronic records and by completing screening questionnaire. Geriatric problems included mobility, dizziness, fear of falling, urinary incontinence, and cognitive impairment. Patients were included if they scored ≥ 5 on VAS scales (range 1 to 10) for geriatric problems or reported ≥ 1 fall in preceding 6 months Exclusion criteria: PARTICIPANTS: recorded dementia diagnosis, GP excluded patients who had recent CMR or deemed unable to participate Number of participants randomised: 518 (275 and 243) Number of participants included in analysis: T0 = 270 vs 239, T2 = 215 vs 211 (unpublished adherence results for 208 vs 198) Age: 77.8 ± 7.7 vs 77.8 ± 8.0 Gender: female: 177 (64.4%) vs 159 (65.4%) Ethnicity: born Dutch or other European: 91.7% vs 93.6% Number of medications: number of drugs reported by patient: 6.1 ± 3.1 vs 5.6 ± 3.2 Frailty/Functional impairment: mobility problems (≥ 5 VAS) = 57.9% vs 62.6% Cognitive impairment: cognitive problems (≥ 5 VAS) = 25.5 vs 26.9%, diagnosed dementia excluded Comorbidities: chronic diseases: 2.77 ± 1.76 vs 3.23 ± 2.19
Interventions	Group 1 ‐ Optimised clinical medication reviews (Opti‐Med): (1) preparation: info from EMRs, pharmacy, and screening questionnaire collected including drug use, medication history, potential DRPs, medical problems, recent lab results, and non‐lab measurements; (2) clinical medication review: expert team of GPs/nursing home physicians and community pharmacists performed review using adapted systematic tool to reduce inappropriate prescribing (STRIP) method; (3) pharmacotherapeutic treatment plan (PTP): PTP sent to patient's GP; (4) implementation of PTP: patients invited for consultation with GP in which PTP was discussed and was determined together with the patient Group 2 ‐ Usual care: expert team also performed CMR analyses, but GPs and patients did not receive the results Co‐intervention: N/A Provider: independent expert team (doctor and pharmacist) and patient's GP Where: primary care clinic When and how often: once ‐ baseline Intervention personalised: yes
Outcomes	Timing of outcome assessment: baseline and 6 months Medication adherence (subjective): self‐reported adherenceproblems assessed in the screening and follow‐up questionnaire Satisfaction with intervention (subjective): Medication Satisfaction Questionnaire: assessed on a 7‐point Likert scale. A 1‐point change in MSQ score was considered clinically meaningful Health‐related quality of life (subjective): SF‐12 and EQ‐5D‐3L Adverse clinical health outcomes (objective): drug‐related problems: number of DRPs per patient ‐ using the DOCUMENT checklist. Assessed by expert team at baseline and by 1 researcher at follow‐up
Notes	Trial registration: NTR4264 Consumer involvement: not specified Funding source: Dutch Organisation for Health Research and Development Dropout: 9 excluded before intervention (5 and 4), 51 withdrew (33 and 18), 42 were lost to follow‐up (27 and 15) Fidelity: 274 of 275 received CMR; 247 discussed with patient Unpublished data: adherence worsened or persisted: 65 vs 54; adherence improved or remained the same: 143 vs 144 ICC value: 0.08. Effective sample sizes were not calculated, as this study was not included in any meta‐analyses due to alternate reporting methods
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Randomisation of practices performed by statistician blinded to characteristics of practices using a computer‐generated list of random numbers
Allocation concealment (selection bias)	High risk	Randomisation done at practice level before patients recruited ‐ could have influenced recruitment of patients
Blinding of participants and personnel (performance bias) All outcomes	High risk	No blinding, but blinding to treatment allocation not possible due to nature of the intervention
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Subjective outcomes unblinded; unclear if researcher blinded
Incomplete outcome data (attrition bias) All outcomes	High risk	Higher dropout and loss to follow‐up in intervention group: 51 withdrew (33 and 18), 42 were lost to follow‐up (27 and 15)
Selective reporting (reporting bias)	Unclear risk	Raw data not reported
Other bias	Unclear risk	Sample size 500 patients, not maintained during follow‐up. Based on EQ‐5D. 274 of 275 received CMR, 247 discussed with patient Recruitment bias (selective recruitment of cluster participants): high risk, randomisation carried out before patients were recruited, thus potential for selective recruitment based on practice knowledge of being in intervention or control group

Williams 2012.

Study characteristics
Methods	Aim of study: to test the feasibility and impact of a multi‐factorial Medication Self‐Management Intervention (MESMI) to improve blood pressure control and medication adherence in adults with coexisting diabetes and CKD disease Study design: RCT (single hospital; unit of allocation: individual) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: Australia Setting: outpatient clinic Inclusion criteria: ≥ 18 years, comprehended English, mentally competent (AMT), type 1 or 2 diabetes, CKD (modified diet in renal disease; eGFR > 15 or diabetic kidney disease), systolic hypertension ≥ 130 mmHg Exclusion criteria: > 50 km from city centre Number of participants randomised: 80 (39 vs 41) Number of participants included in analysis: 75 (36 vs 39), adherence 74 (35 vs 39) as per trial author correspondence Age: 68 ± 8.3 vs 66 ± 10.8 Gender: female: 17 (42.6%) vs 26 (63.4%) Ethnicity: Australia born: 14 (35.9%) vs 15 (36.6%) Number of medications: prescribed medications (excluding insulin and OTC) 7.6 ± 2.6 vs 7.2 ± 3.3 Frailty/Functional impairment: not specified Cognitive impairment: AMT: 10 (10 to 11) vs 11 (11 to 10), cognitive impairment excluded Comorbidities: other long term illnesses: 7.7 ± 2.5 vs 8.2 ± 2.5
Interventions	Group 1 ‐ Medication Self‐Management Intervention (MESMI): multi‐factorial intervention consisting of self‐monitoring of BP, individualised medication review, 20‐minute DVD, and fortnightly motivational interviewing follow‐up telephone contact for 12 weeks to support BP control and optimal medication self‐management. Patients taught how to take BP correctly and recorded BP daily for 3 months. Medication review involved drawing up a medication chart (generic name, indication, dose, targets). DVD had 3 sections: how BP affects body, benefits and safety of prescribed medications, tips to help take medications as prescribed. Motivational interviewing: open‐ended questions used to prompt discussion about the participant's well‐being, BP, and medications Group 2 ‐ Usual care: standard outpatient care Co‐intervention: N/A Provider: nurse (renal specialist, doctoral qualification, and motivational training) Where: home and telephone When and how often: home intervention, then 12 weeks of support and follow‐up phone calls Intervention personalised: yes
Outcomes	Timing of outcome assessment: 9 months post intervention (12 months post enrolment) Medication adherence (objective) : pill count: percentage medication adherence to all long‐term prescribed medications measured by pill counts. Insulin and OTC (vitamins) not included in pill count Condition‐specific outcomes (objective): change in BP (checked by research assistant), HbA1c, eGFR, creatine
Notes	Trial registration: ACTRN12607000044426 Consumer involvement: not specified Funding source: Australian Research Council grant (LP0774989), Sigma Theta Tau International Small grant, Nurses Memorial Centre Australian legion of Ex‐servicemen and ‐women scholarship, Mona Menzies Nurses Board of Victoria Grant Dropout: 1 withdrew, 3 died, 1 was lost to follow‐up Fidelity: accuracy of pill count confounded by participants unable to recall when they started their new prescription. Only 30 participants saved their medication boxes to enable a full pill count to be performed Unpublished data: trial authors contacted regarding number of people included in adherence follow‐up; total people included in calculation was 35 vs 39
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Randomised by off‐site statistician; stratified block randomisation
Allocation concealment (selection bias)	Low risk	Following recruitment, participants were allocated code numbers before enrolment and randomisation by an off‐site statistician
Blinding of participants and personnel (performance bias) All outcomes	High risk	Participants could not be blinded and were asked not to disclose group allocation to research assistant
Blinding of outcome assessment (detection bias) All outcomes	Low risk	Research assistant blinded to group assignment
Incomplete outcome data (attrition bias) All outcomes	High risk	Pill count not possible for most (only 30 saved all pill boxes, enabling complete count)
Selective reporting (reporting bias)	High risk	Sample size calculated as 108 participants ‐ did not reach target sample size and modified inclusion criteria to try to increase recruitment
Other bias	Unclear risk	Accuracy of pill count confounded by participants unable to recall when they started their new prescription. Only 30 participants saved their medication boxes to enable a full pill count to be performed. Sample size calculated as 108 participants ‐ did not reach target sample size

Winland‐Brown 2000.

Study characteristics
Methods	Aim of study: to investigate the effects of 3 medication management approaches on medication adherence. To examine the relationship between medication adherence and utilisation of healthcare resources, including numbers of physician office visits, hospitalisations, and home health visits Study design: RCT (unit of allocation: individual) Number of arms/groups: 3
Participants	Description: patient/consumer Geographic location: USA Setting: independent living facility Inclusion criteria: capable of following simple directions, had a medication mismanagement episode, had hospitalisation for medication non‐adherence or an illness in which therapeutic accuracy was necessary for its management Exclusion criteria: not specified Number of participants randomised: 61 (16, 24, 21) Number of participants included in analysis: 61 (16, 24, 21) Age: mean: 87 years, range 70 to 100 Gender: 35 F, 26 M Ethnicity: primarily Jewish Number of medications: type not specified, range 3 to 15 Frailty/Functional impairment: not specified Cognitive impairment: 17.5% had dementia Comorbidities: total number not specified
Interventions	Group 1 ‐ Pre‐poured pillbox: medication management pack, no voice activation Group 2 ‐ Automated voice‐activated dispenser: voice‐activated message that audibly reminded and automatically dispensed individual doses of medication to the participant Group 3 ‐ Usual care: self‐administration of own medications Co‐intervention: nurses visited patients each week to refill medication packs and address any questions or concerns (unclear whether control group also visited) Provider: nurse filled medication packs Where: independent living facility (patient homes) When and how often: weekly for 6 months Intervention personalised: no
Outcomes	Timing of outcome assessment: baseline (for healthcare utilisation) and 6 months Medication adherence (objective) : pill count: average number of missed doses via pill count Adverse clinical health outcomes (objective): healthcare utilisation: medical records examined for numbers of physician visits, hospital admissions, and home visits, and transition to a higher level of care Condition‐specific outcomes (objective): biochemical markers of adherence: measured by the impact on medical diagnosis. Hypertensive group defined as adherent if sustained normotensive, cardiac adherent by INR 2.0 to 3.0, antipsychotic adherent by stable blood levels and mood stabilisation, diabetes by stable blood glucose and periodic HbA1c < 9%
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: not specified Dropout: nil specified Further information required: biomedical markers of adherence as per protocol (trial author correspondence ‐ successful, no further results available) Please note: group 2 vs group 3 was used for comparison of intervention vs usual care, group 1 vs group 2 was used for comparison of intervention vs intervention
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	High risk	Patients "were randomly assigned to 1 of 2 medication management programs" (details unclear) and "clients of similar age, gender, and cognition were assigned to a control group" (not randomised)
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not possible to blind participants
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	No mention of blinding; unclear whether nurses who refilled pack each week also conducted adherence assessment
Incomplete outcome data (attrition bias) All outcomes	Low risk	No attrition mentioned
Selective reporting (reporting bias)	High risk	Missing data on impact on medical diagnoses
Other bias	Unclear risk	Groups unbalanced; G2 all had been prolonged hospitalisation compared to 7/16 in G1 and none in usual care group. Also, half of G2 participants had 2 hours home health services/d compared to none in the G1 and usual care groups

Wood 1992.

Study characteristics
Methods	Aim of study: to determine the effects of an inpatient self‐administration of medication programme on compliance post discharge among elderly patients Study design: cluster‐RCT (2 wards intervention, 2 wards control, 1 intervention and 1 control per hospital) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: UK Setting: hospital inpatient (pre‐discharge) from rehabilitation wards Inclusion criteria: rehabilitating with the ultimate aim of discharge to own home to live alone Exclusion criteria: nil mentioned Number of participants randomised: 33 (18 and 15) Number of participants included in analysis: 22 (11 and 11) Age: 85.4 ± 6.0 vs 84.8 ± 5.8 Gender: M:F = 1:8 (88.8% F) vs 1:6.5 (86.7%) Ethnicity: not specified Number of medications: number of dose‐taking events per day: 8.1 ± 5.0 vs 6.17 ± 5.0 Frailty/Functional impairment: not specified Cognitive impairment: abbreviated mental test score: 9.1 vs 9.4 Comorbidities: not specified
Interventions	Group 1 ‐ Inpatient self‐administration: 3 distinct phases ‐ phase 1: medicine containers labelled as for discharge, drugs handed to patient at appropriate times, and full supervision of medication selection and ingestion. After 7 days, or earlier if appropriate, patient moved to phase 2; phase 2: patient required to request medication at appropriate times. After 7 error‐free days, patient moves on; phase 3: patient becomes totally responsible for his/her own medication. Medicines stored in locked cupboard. Compliance checked by tablet count Group 2 ‐ Usualcare: discharge medicines issued by nursing staff immediately before discharge Co‐intervention: N/A Provider: care team ‐ including pharmacist and nurse Where: hospital inpatient (pre‐discharge) When and how often: up to 3 weeks, inpatient Intervention personalised: yes ‐ moved through phases only if able to self‐administer medications
Outcomes	Timing of outcome assessment: 2 weeks and 3 months post discharge Medication adherence (objective) : pill count: average percentage of non‐compliance calculated by pill count. No errors made, few errors (1% to 15% non‐compliance), and many errors (> 15%)
Notes	Trial registration: N/A Consumer involvement: not specified Funding source: not specified Dropout: 8 lost to follow‐up (4 and 4) plus 3 intervention could not be analysed ICC value unclear; unsuccessful contact with study authors likely due to age of study. Thus unit of analysis error exists
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Wards allocated ‐ randomisation method not stated
Allocation concealment (selection bias)	Unclear risk	Not specified
Blinding of participants and personnel (performance bias) All outcomes	High risk	Not blinded. Blinding was not possible for the type of intervention provided unless the researcher was not involved in providing the intervention; unclear if this had any impact on the outcome
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Not specified whether home visit staff were blinded
Incomplete outcome data (attrition bias) All outcomes	High risk	4 lost to follow‐up from both groups, 3 intervention patients excluded because they had received new medications but transferred them to original containers = potentially unbalanced analysis
Selective reporting (reporting bias)	Unclear risk	Additional data in results that are not specified in methods (e.g. errors sufficient to be detrimental to health)
Other bias	Low risk	Recruitment bias (selective recruitment of cluster participants): low risk, recruitment occurred after allocation but all patients on the ward were included in the study (no exclusions), thus limited risk of recruitment bias

Wu 2006.

Study characteristics
Methods	Aim of study: to investigate the effects of compliance and periodic telephone counselling by a pharmacist on mortality in patients receiving polypharmacy Study design: RCT (unit of allocation: individual) Number of arms/groups: 2
Participants	Description: both patient/consumer and carer Geographic location: China Setting: specialist medical clinic at a hospital Inclusion criteria: non‐compliant (pharmacist assessed medical clinic records), ≥ 5 drugs on ≥ 2 consecutive visits to the clinic Exclusion criteria: non‐Cantonese dialects or a different language, had conditions that prevented effective communication (deaf, mute, dementia, psychological disorders), living in nursing homes with supervised treatment Number of participants randomised: 442 (219 and 223) Number of participants included in analysis: 442 (219 and 223) (but 43 died by follow‐up) Age: 71.2 ± 9.4 vs 70.5 ± 11.1 Gender: female 51% vs 52% Ethnicity: not specified ‐ all spoke Cantonese Number of medications: drugs for chronic illnesses: 6.0 ± 1.3 vs 5.9 ± 1.2 Frailty/Functional impairment: not specified Cognitive impairment: dementia excluded Comorbidities: not specified
Interventions	Group 1 ‐ Telephone counselling by a pharmacist: patients received a 10‐ to 15‐minute telephone call from pharmacist at midpoint between clinic visits (6 to 8 calls over 2 years). Pharmacist asked about patient's treatment regimens, clarified any misconceptions, explained side effects, reminded of next clinic appointment, reinforced importance of compliance Group 2 ‐ Usual care: no telephone intervention Co‐intervention: all patients received 10‐ to 15‐minute educational talk by pharmacist during screening. Pharmacist determined compliance using structured questionnaire Provider: pharmacist Where: telephone to home When and how often: 6 to 8 telephone calls for 2 years Intervention personalised: yes
Outcomes	Timing of outcome assessment: screening or enrolment and 2 years Medication adherence (subjective) : patient asked if he or she had missed any doses; changed regimens in terms of dose, frequency, and timing; or had drugs left over. Compliant 80% to 120%. This information was checked against dispensing information Adverse clinical health outcomes (objective): all‐cause mortality Adverse clinical health outcomes (objective): hospitalisations: rate of admission to hospital, number of emergency department visits, and hospital stay 2 years before and after screening
Notes	Trial registration: SRCTN48076318 Consumer involvement: not specified Funding source: Hong Kong Government Health Care and Promotion Fund and MSD international grant Dropout: 25 and 38 died
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Pharmacist blinded to randomisation codes, which were computer‐generated by statistician and sealed in envelopes labelled with consecutive numbers
Allocation concealment (selection bias)	Low risk	Envelopes opened by clinic nurse in an ascending manner, and patients allocated
Blinding of participants and personnel (performance bias) All outcomes	High risk	Blinding was not possible because the intervention was complex and caregivers were involved
Blinding of outcome assessment (detection bias) All outcomes	High risk	Blinding not possible; could have had blinded research review of outcomes
Incomplete outcome data (attrition bias) All outcomes	Unclear risk	ITT; no loss to follow‐up, but 60 defaulters before randomisation, 31 of whom died
Selective reporting (reporting bias)	Low risk	Baseline reports as compliant/non‐compliant, follow‐up reports who remains compliant/non‐compliant (number can be computed); otherwise as per methods
Other bias	Unclear risk	Sample size 1067 to account for non‐compliance and achieve significant reduction in mortality ‐ not reached

Young 2016.

Study characteristics
Methods	Aim of study: to evaluate the effects of patient activation intervention on self‐management (SM) adherence, hospital re‐admission, and ED visit rates at 30 days, 3 months, and 6 months Study design: RCT (block randomisation of 4 to 6) Number of arms/groups: 2
Participants	Description: patient/consumer Geographic location: USA Setting: 2 rural critical access hospitals Inclusion criteria: ≥ 21 years, HF as one of discharge diagnoses, New York Heart Association class II to IV or class I symptoms and ≥ 1 HF‐related hospitalisation/ED visit in past year, discharged to home, passed mini‐cognitive screen, understood English, had access to a phone Exclusion criteria: scheduled procedures/surgeries, depressive symptoms (score ≥ 3 on Patient Health Questionnaire, liver cirrhosis, renal failure, end‐stage and/or terminal illness that affected ability to perform SM behaviours Number of participants randomised: 105 (54 and 51) Number of participants included in analysis: 100 (51 vs 49) Age: 68.7 ± 11.8 vs 71.8 ± 12.6 Gender: female: 52.9% vs 75.5% Ethnicity: Caucasian: 94.1% vs 95.9% Number of medications: medications per day (type unknown) 16.4 ± 10.0 vs 15.9 ± 7.4 Frailty/Functional impairment: not specified Cognitive impairment: had to pass mini‐cognitive assessment to be included Comorbidities: total comorbidities 7.8 ± 2.5 vs 8.0 ± 2.7
Interventions	Group 1 ‐ Patient AcTivated Care at Home Model (PATCH): usual care + 12 weeks of PATCH intervention. Intervention comprised 2 phases in which the in‐hospital discharge education session was followed by 12 weeks of post‐discharge educational sessions delivered by telephone. Patients received SM toolkit (calendar for weight and salt, scales, electronic pill organiser reminder alarm). Each intervention session lasted 45 to 50 minutes. Booster sessions for patients struggling at home Group 2 ‐ Usual care (standard discharge teaching for HF and scheduled follow‐up doctor appointments) Co‐intervention: N/A Provider: unclear ‐ nurse ? Where: phase 1: in hospital; phase 2: post discharge via telephone When and how often: post‐discharge phone calls twice a week for first 2 weeks, then weekly 3 to 6 weeks, then every second week 7 to 12) Intervention personalised: yes ‐ tailored based on activation level, pre‐set goals, and specific SM needs; booster sessions given to those struggling with SM
Outcomes	Timing of outcome assessment: hospital discharge and 6 months (180 days) Medication adherence (subjective) : self‐reported adherence: number of days when any medication doses were missed in past 7 days, grouped as 0 or ≥ 1 days (dichotomous) Adverse clinical health outcomes (objective): all‐cause re‐admissions and ED visits ‐ self‐report and primary care provider report
Notes	Trial registration: NCT01964053 Consumer involvement: not specified Funding source: National Institutes Nursing Research of the National Institutes of Health Dropout: 3 intervention withdrew before intervention, 2 control withdrew/were lost to follow‐up
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Project statistician used an on‐line pseudo‐random number generator to create an allocation schedule; random ordering of block sizes 4 and 6 was used to maintain even accrual throughout the study
Allocation concealment (selection bias)	Low risk	Group assignments placed in sealed envelope and opened sequentially as patients were enrolled
Blinding of participants and personnel (performance bias) All outcomes	High risk	Blinding of subject and intervention is impossible
Blinding of outcome assessment (detection bias) All outcomes	Unclear risk	Data collector was blinded to treatment assignment. Unclear whether this blinding was completely possible as patients were aware of their treatment group and may have told assessor
Incomplete outcome data (attrition bias) All outcomes	Low risk	Minimal attrition; sample calculations allowed for 15% but it was much less
Selective reporting (reporting bias)	Low risk	As per methods
Other bias	Low risk	None apparent; sample size 96

A2RA: angiotensin 2 receptor antagonist.

ACEI: angiotensin‐converting enzyme inhibitor.

ADL: activity of daily living.

ADR: adverse drug reaction.

BB: beta‐blocker.

BMI: body mass index.

BMQ: Beliefs About Medicines Questionnaire.

BP: blood pressure.

C: control.

CABG: coronary artery bypass graft.

CHD: coronary heart disease.

CHF: coronary heart failure.

CI: confidence interval.

CKD: chronic kidney disease.

CMR: clinical medication review.

CNS: central nervous system.

COPD: chronic obstructive pulmonary disease.

CRD: carer‐reported dementia.

CTP: care transition programme.

CV: cardiovascular.

CVD: cardiovascular disease.

DASH: Disabilities of the Arm, Shoulder and Hand.

DM: diabetes mellitus.

DRP: drug‐related problem.

ED: emergency department.

eGFR: estimated glomerular filtration rate.

EMR: electronic medical record.

EQ‐5D: EuroQoL Group Quality of Life Questionnaire based on 5 dimensions.

EuroQoL‐5D: EuroQoL Group Quality of Life Questionnaire based on 5 dimensions.

FEV1: forced expiratory volume in one second.

GMC: general medicine clinic.

GP: general practitioner.

HbA1c: glycosylated haemoglobin.

HF: heart failure.

HMH: home medication history.

HRQoL: health‐related quality of life.

I: intervention.

iADL: instrumental activity of daily living.

ICC: intracluster correlation coefficient.

IHD: ischaemic heart disease.

INR: international normalised ratio.

IQR: interquartile ratio.

ITT: intention‐to‐treat.

LDL‐C: low‐density lipoprotein cholesterol.

LOS: length of stay.

MAP: medication action plan.

MARS: Medication Adherence Rating Scale.

MD.2: medication dispenser machine

MDW: medication discharge worksheet.

MI: motivational interview; myocardial infarction.

MIDS: medication and information discharge summary.

MMAS: Morisky Medication Adherence Scale.

MOS: Medication Outcomes Study

MPR: medication possession ratio.

N/A: not applicable.

NH: nursing home

NHS: National Health Service.

NSAID: non‐steroidal anti‐inflammatory drug.

OTC: over‐the‐counter.

PCI: pharmaceutical care issue.

PHR: personal health record.

PIM: potentially inappropriate medication

PMC: polymedication check.

PPI: proton pump inhibitor.

PTP: pharmacotherapeutic treatment plan.

PVD: peripheral vascular disease

QoL: quality of life.

RACF: residential aged care facility

RCT: randomised controlled trial.

SBP: systolic blood pressure.

SD: standard deviation.

SE: standard error.

SF‐36: Short Form‐36 Health Survey.

SGRQ: St. George's Respiratory Questionnaire.

T2DM: type 2 diabetes mellitus.

VAS: visual analogue scale.

Characteristics of excluded studies [ordered by study ID]

Study	Reason for exclusion
ACTRN12616001411437	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
ACTRN12617001352392	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (intervention focused on hypertension medications only)
Adams 2015	EXCLUDE Medications = unable to determine if > 4 medications (trial authors did not collect numbers of medications)
Ahmad 2011	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Al‐Asseri 2001	EXCLUDE Participant mean age ≤ 65 years
Al‐Khadra 2014	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Allen 1986	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Allen 2011	EXCLUDE Participant mean age ≤ 65 years
Altavela 2008	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Alvarez 2001	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Ansari 2017	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Ansari 2017a	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Antoniades 2012	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Antonicelli 2008	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Artinian 2003	EXCLUDE Medications = unable to determine if > 4 medications (no response from trial author)
Ascione 1984	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (intervention and outcome only at CV medications, average 2)
Bailey 2012	EXCLUDE Participant mean age ≤ 65 years
Barker 2012	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Basger 2015	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Basheti 2016	EXCLUDE Participant mean age ≤ 65 years
Bennett 2003	EXCLUDE Participant mean age ≤ 65 years
Bhattacharya, 2016	EXCLUDE Outcome = follow‐up too short (3 weeks)
Biese 2011	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (conference paper for 2014 paper)
Biese 2014	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Biese 2017	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Bilotta 2011	EXCLUDE study design not RCT, cluster‐RCT, nor quasi‐RCT
Birtwhistle 2004	EXCLUDE Participant mean age ≤ 65 years
Biswas 2018	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (numbers of medications data not collected)
Blenkinsopp 2000	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (antihypertensives only)
Bogner 2012	EXCLUDE Participant mean age ≤ 65 years
Bolas 2004	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Bolton 2004	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Bonetti 2018	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Boult 2013	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Branda 2013	EXCLUDE Participant mean age ≤ 65 years
Braun 2009	EXCLUDE Participant mean age ≤ 65 years
Broadbent 2018	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (assessed respiratory medications only)
Bronson 1986	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Bryant 2011	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Bryson 2008	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Burrelle 1986	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Caetano 2018	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (diabetes medications only)
Calvert 2012	EXCLUDE Participant mean age ≤ 65 years
Cedilnik 2016	EXCLUDE Intervention = not directed at consumer nor carer (directed at GP)
Chan 2012	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Chan 2015	EXCLUDE Participant mean age ≤ 65 years
Chau 2012	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Chen 2016	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Choudhry 2008	EXCLUDE Participant mean age ≤ 65 years
Chow 2015	EXCLUDE Participant mean age ≤ 65 years
Clarkesmith 2013	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Clemson 2004	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Clifford 2006	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Coleman 1999	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Coombes 2018	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (looking only at adherence to medications for secondary prevention of stroke ‐ between 1 and 3 medications/person)
Costa 2008	EXCLUDE Participant mean age ≤ 65 years
Cotterell 1992	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Coull 2004	EXCLUDE Medications = unable to determine if > 4 medications (no contact with trial authors)
Criswell 2010	EXCLUDE Participant mean age ≤ 65 years
Crotty 2005	EXCLUDE Setting = participants not living in community nor discharged from hospital to community
Crowley 2015	EXCLUDE Participant mean age ≤ 65 years
Ctri 2017	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Cummings 2019	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
D'Agostino 2006	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Damush 2011	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Damush 2016	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Day 1992	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Day 1998	EXCLUDE Participant mean age ≤ 65 years
De Azevedo 2017	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
de Lusignan 2001	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Denneboom 2007	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Denneboom 2008	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Dickson 2011	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Dorje 2018	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Doucette 2009	EXCLUDE Participant mean age ≤ 65 years
Doughty 2002	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Doyon 2009	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Drenth‐van 2013	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Drks 2014	EXCLUDE Intervention = not directed at consumer nor carer
Drks 2015	EXCLUDE Intervention = not directed at consumer nor carer
Dunn 1995	EXCLUDE Participant mean age ≤ 65 years
Duong 1996	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Eggink 2010	EXCLUDE Outcome = follow‐up too short (adherence 23 days)
Eikelenboom 2016	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Elliott 2008	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (new medicines only)
Elliott 2012	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Ellis 2000	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Enguidanos 2012	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Epstein 1990	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Esposito 1995	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (assumed given low MCI scores)
Evans 2010	EXCLUDE Participant mean age ≤ 65 years
Fabacher 1994	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Fan 2012	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Farmer 2012	EXCLUDE Participant mean age ≤ 65 years
Fernandes 2012	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (intervention targeting hypertension only)
Fernando 2012	EXCLUDE Participant mean age ≤ 65 years
Fernley 1983	EXCLUDE Outcome = follow‐up too short (adherence 7 to 10 days)
Ferrat 2018	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Figar 2006	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Fikri‐Benbrahim 2013	EXCLUDE Participant mean age ≤ 65 years
Fikri‐Benbrahim 2014	EXCLUDE Participant mean age ≤ 65 years
Fincher 2009	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Finley 2003	EXCLUDE Participant mean age ≤ 65 years
Fischer 2014	EXCLUDE Participant mean age ≤ 65 years
Fortney 2007	EXCLUDE Participant mean age ≤ 65 years
Fortney 2011	EXCLUDE Participant mean age ≤ 65 years
Fortney 2015	EXCLUDE Participant mean age ≤ 65 years
Frennet 2011	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Frey 2001	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Friedman 1996	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Fugazzaro 2016	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT (non‐randomised as per 2018 paper)
Fulmer 1999	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (capped maximum 4 medications per person, hence average < 4)
Gabriel 1977	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Gamboa 2019	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Garcao 2002	EXCLUDE Participant mean age ≤ 65 years
Garcia 2017	EXCLUDE Participant mean age ≤ 65 years
Garza 2016	EXCLUDE Participant mean age ≤ 65 years
Gellis 2014	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Gialamas 2009	EXCLUDE Medications = unable to determine if > 4 medications (trial authors did not collect numbers of medications)
Gould 2011	EXCLUDE Participant mean age ≤ 65 years
Grant 2003	EXCLUDE Participant mean age ≤ 65 years
Green 2008	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (adherence to antihypertensives only)
Grice 2014	EXCLUDE Setting = participants not living in community nor discharged from hospital to community
Gujral 2014	EXCLUDE Participant mean age ≤ 65 years
Gums 2015	EXCLUDE Participant mean age ≤ 65 years
Gwadry‐Sridhar 2005	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Han 2010	EXCLUDE Participant mean age ≤ 65 years
Hansen 2009	EXCLUDE Participant mean age ≤ 65 years
Haramiova 2017	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (protocol only, blood pressure‐lowering medication only)
Harari 2008	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Hawe 1990	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Hayes 1998	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Hedegaard 2015	EXCLUDE Participant mean age ≤ 65 years
Heisler 2010	EXCLUDE Participant mean age ≤ 65 years
Heisler 2011	EXCLUDE Outcome = not medication adherence nor medication‐taking ability (conference abstract for 2012 paper)
Heisler 2012	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Heisler 2014	EXCLUDE Participant mean age ≤ 65 years
Hesselink 2004	EXCLUDE Participant mean age ≤ 65 years
Ho 2014	EXCLUDE Participant mean age ≤ 65 years
Hohmann 2014	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Holdford 2013	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Horton 2017	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Hsieh 2008	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (TB meds only)
Huang 2018	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Hugtenburg 2012	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Hunter 1996	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Hyrkas 2014	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Insel 2016	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (adherence to 1 medicine only)
IRCT20110728007143N	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
IRCT201306297531N	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
IRCT2014050617596N	EXCLUDE Participants mean age ≤ 65 years, or more than 20% aged 65 years
IRCT2015090513092N	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
IRCT2016082129448N	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
IRCT2016090629728N	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
IRCT2016120731290N	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
IRCT20171125037616N	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (adherence not assessed for all medications)
IRCT20171213037859N	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
IRCT20180513039646N	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
ISRCTN03155973	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
ISRCTN12752680	EXCLUDE Outcome = not medication adherence nor medication‐taking ability. Note: secondary outcomes were changed 17/07/17; adherence was previously listed but was no longer included in the study protocol
ISRCTN18285541	EXCLUDE Medications ‐ unable to determine if eligible as study never completed. "Investigators decided to close the clinical trial because the rate of inclusion of patients was being so slow that it was impossible to reach the necessary number in a reasonable time". Dr. José Luis González Guerrero (joselglezg@gmail.com)
Jager 2017	EXCLUDE Intervention = not directed at consumer nor carer (GP is participant)
Jager 2017a	EXCLUDE Intervention = not directed at consumer nor carer
Jahangard‐Rafsanjani 2015	EXCLUDE Participant mean age ≤ 65 years
Jarab 2012	EXCLUDE Participant mean age ≤ 65 years
Jarab 2012a	EXCLUDE Participant mean age ≤ 65 years
Jensen 2003	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Jerant 2003	EXCLUDE Medications = unable to determine if > 4 medications (trial authors did not collect numbers of medications)
Jiang 2007	EXCLUDE Participant mean age ≤ 65 years
Johnson‐Warrington 2016	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (COPD only)
Johnston 2000	EXCLUDE Medications = unable to determine if > 4 medications (no response from trial authors)
Junling 2015	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Kalichman 2011	EXCLUDE Participant mean age ≤ 65 years
Karagiannis 2016	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (diabetic medications only)
Kaukab 2015	EXCLUDE Participant mean age ≤ 65 years
Kaur 2015	EXCLUDE Participant mean age ≤ 65 years
Kavin 2010	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Kelly 1990	EXCLUDE Participant mean age ≤ 65 years
Kempen 2017	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Keyserling 2014	EXCLUDE Participant mean age ≤ 65 years
Khan 2019	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Khonsari 2015	EXCLUDE Participant mean age ≤ 65 years
Khunti 2012	EXCLUDE Participant mean age ≤ 65 years
Kim 2014	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (adherence to BP medications only)
Kim 2015	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Kim 2015a	EXCLUDE Participant mean age ≤ 65 years
Kimball 2010	EXCLUDE Participant mean age ≤ 65 years
Koberlein‐Neu 2016	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Kogos 2004	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Kono 2004	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Kotowycz 2010	EXCLUDE Participant mean age ≤ 65 years
Kozuki 2006	EXCLUDE Participant mean age ≤ 65 years
Kraemer 2012	EXCLUDE Participant mean age ≤ 65 years
Kranker 2018	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Krass 2007	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Kripalani 2012	EXCLUDE Participant mean age ≤ 65 years
Kripalani 2012a	EXCLUDE Participant mean age ≤ 65 years
Krishnamurthi 2014	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (TB medications only)
Krishnaswami 1981	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Krishnaveni 2019	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Kutzleb 2006	EXCLUDE Participant mean age ≤ 65 years
Lalonde 2017	EXCLUDE Intervention = not directed at consumer nor carer
Lam 2011	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (antihypertensives only)
Lam 2017	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Lange 2010	EXCLUDE Participant mean age ≤ 65 years
Laramee 2003	EXCLUDE Medications = unable to determine if > 4 medications (trial authors did not collect information)
Laufs 2018	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (adherence measure not for all medications)
Leavitt 2017	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Lei 2019	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Leiva‐Fernandez 2014	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (COPD only)
Lenaghan 2007	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Lerma 2017	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Levine 1979	EXCLUDE Participant mean age ≤ 65 years
Levy 2004	EXCLUDE Participant mean age ≤ 65 years
Li 2012	EXCLUDE Participant mean age ≤ 65 years
Li 2013	EXCLUDE Medications = unable to determine if > 4 medications (no response from trial authors)
Li‐Hong 2018	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Lin 2012	EXCLUDE Participant mean age ≤ 65 years
Lluch‐Canut 2006	EXCLUDE Participant mean age ≤ 65 years
Lowe 1995	EXCLUDE Outcome = follow‐up too short (adherence measured at 10 days)
Lowe 2000	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Lu 2015	EXCLUDE Participant mean age ≤ 65 years
Luttik 2014	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (total unknown, adherence for individual medication classes only)
Ma 2014	EXCLUDE Participant mean age ≤ 65 years
MacDonald 1977	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Mackenzie 2013	EXCLUDE Medications = unable to determine if > 4 medications (no response from trial authors)
Maduka 2013	EXCLUDE Participant mean age ≤ 65 years
Magid 2011	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Maislos 2004	EXCLUDE Participant mean age ≤ 65 years
Malet‐Larrea 2016	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Maly 1999	EXCLUDE Participant mean age ≤ 65 years
Margolius 2012	EXCLUDE Participant mean age ≤ 65 years
Marin 2015	EXCLUDE Participant mean age ≤ 65 years
Marquez Contreras 2009	EXCLUDE Participant mean age ≤ 65 years
Martin 1982	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (total not provided, low medication regimen complexity)
Martin 2011	EXCLUDE Participant mean age ≤ 65 years
Martinez 2014	EXCLUDE Participant mean age ≤ 65 years
Matsuyama 1993	EXCLUDE Participant mean age ≤ 65 years
Mazzuca 1986	EXCLUDE Participant mean age ≤ 65 years
McCarthy 2013	EXCLUDE Participant mean age ≤ 65 years
McCarthy 2017	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
McGeoch 2006	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Mehos 2000	EXCLUDE Participant mean age ≤ 65 years
Mehuys 2008	EXCLUDE Participant mean age ≤ 65 years
Mehuys 2011	EXCLUDE Participant mean age ≤ 65 years
Meredith 2002	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Michiels 2017	EXCLUDE Medications ‐ data on number of medications not collected, thus unable to determine eligibility
Miller 1988	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Miller 2008	EXCLUDE Participant mean age ≤ 65 years
Mitchell 2014	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Moczygemba 2012	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Moorhead 2017	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Moreno 2016	EXCLUDE Participant mean age ≤ 65 years
Morisky 1990	EXCLUDE Participant mean age ≤ 65 years
Morrison 2016	EXCLUDE Participant mean age ≤ 65 years
Mullan 2009	EXCLUDE Participant mean age ≤ 65 years
Muniz 2010	EXCLUDE Participant mean age ≤ 65 years
Murray 2007	EXCLUDE Participant mean age ≤ 65 years
NCT00838344	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (diabetic medication only)
NCT01144182	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
NCT01271985	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
NCT01404988	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (adherence not measured for all medications)
NCT01914588	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
NCT02035566	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (adherence not measured for all medications)
NCT02140619	EXCLUDE Medications < 4 regular medications or group mean ≤4 (persistence to statin or antiplatelet only)
NCT02490423	EXCLUDE Participant mean age ≤ 65 years (mean age 63.2 as per investigator, Dr. Horne)
NCT02697422	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
NCT02905474	EXCLUDE Participant mean age ≤ 65 years (mean age 57 as per trial author email)
NCT03342729	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Nesari 2010	EXCLUDE Participant mean age ≤ 65 years
Newman 2016	EXCLUDE study design: not RCT, cluster‐RCT, nor quasi‐RCT
Nguyen 2017	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Nishita 2013	EXCLUDE Participant mean age ≤ 65 years
Noureldin 2012	EXCLUDE Participant mean age ≤ 65 years
NTR2288, 2010	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Obreli‐Neto 2011	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Ogedegbe 2012	EXCLUDE Participant mean age ≤ 65 years
Oliveira‐Filho 2014	EXCLUDE Participant mean age ≤ 65 years
Oonk 2017	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Ostbring 2014	EXCLUDE Outcome = follow‐up too short (adherence measured 2 weeks after intervention)
Ostovaneh 2015	EXCLUDE Participant mean age ≤ 65 years
Park 2011	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Parker 2014	EXCLUDE Participant mean age ≤ 65 years
Pearl 2003	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Peng 2014	EXCLUDE Participant mean age ≤ 65 years
Perl 2016	EXCLUDE Participant mean age ≤ 65 years
Persaud 2017	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Peters‐Klimm 2010	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Phumipamorn 2008	EXCLUDE Participant mean age ≤ 65 years
Pitner 2004	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Pladevall 2010	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Pladevall 2015	EXCLUDE Participant mean age ≤ 65 years
Plant 2015, ACTRN12609000554268	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Polack 2008	EXCLUDE Participant mean age ≤ 65 years
Ponnusankar 2004	EXCLUDE Participant mean age ≤ 65 years
Powers 2011	EXCLUDE Medications = unable to determine if > 4 medications (CVD adherence only; email sent to trial authors for actual number of medications but no response)
Pringle 2014	EXCLUDE Participant mean age ≤ 65 years
Pérez‐Escamilla 2015	EXCLUDE Participant mean age ≤ 65 years
Radini 2017	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Ramaekers 2009	EXCLUDE Medications = unable to determine if > 4 medications (trial authors provided no additional information)
Ramanath 2011	EXCLUDE Participant mean age ≤ 65 years
Ravn‐Nielsen 2018	EXCLUDE Setting = participants not all living in community or discharged from hospital to community (possibility of subgroup analyses not explored as adherence data were not available)
Raynor 1993	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Reed 2018	EXCLUDE Medications ‐ unable to determine eligibility as data on number of medications not collected
Richmond 2010	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Roden 1985	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Rose 2016	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Rothschild 2014	EXCLUDE Participant mean age ≤ 65 years
Rozenfeld 1999	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (adherence only to 1 or 2 CV medications)
Rubak 2011	EXCLUDE Participant mean age ≤ 65 years
Rytter 2010	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Safren 2014	EXCLUDE Participant mean age ≤ 65 years
Salisbury 2016	EXCLUDE Medications = unable to determine whether > 4 medications (trials authors collected only info on CVD medications)
Samtia 2013	EXCLUDE Participant mean age ≤ 65 years
Sanchez 2012	EXCLUDE Outcome = follow‐up too short (adherence at 7 days only)
Sandler 1989	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Schneider 2008	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (adherence to lisinopril only)
Schou 2013	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Schou 2014	EXCLUDE Outcome = not medication adherence nor medication‐taking ability (conference abstract to 2013 paper)
Schwalm 2015	EXCLUDE Participant mean age ≤ 65 years
Schwartz 2015	EXCLUDE Participant mean age ≤ 65 years
Schwartz 2017	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Scott 2004	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Selak 2014	EXCLUDE Participant mean age ≤ 65 years
Shah 2013	EXCLUDE Outcome = follow‐up too short (adherence 7 to 14 days only)
Sherrard 2009	EXCLUDE Participant mean age ≤ 65 years
Sherrard 2015	EXCLUDE Participant mean age ≤ 65 years
Shuster 1998	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Sidel 1990	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Simkins 1986	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Simoni 2011	EXCLUDE Participant mean age ≤ 65 years
Sit 2016	EXCLUDE Medications = unable to determine whether > 4 medications (no response from trial authors)
Sledge 2006	EXCLUDE Participant mean age ≤ 65 years
Smith 1997	EXCLUDE Outcome = follow‐up too short (adherence measured at 7 to 10 days only)
Smith 2004	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Smith 2007	EXCLUDE Medications = unable to determine whether > 4 medications (no information available from trial authors)
Soloman 1998	EXCLUDE Medications = unable to determine whether > 4 medications (no response from trial authors)
Sookaneknun 2004	EXCLUDE Participant mean age ≤ 65 years
Soong 2014	EXCLUDE Participant mean age ≤ 65 years
Souter 2017	EXCLUDE Medications = unable to determine whether > 4 medications (no response from trial authors)
Stange 2013	EXCLUDE Participant mean age ≤ 65 years
Stanhope 2013	EXCLUDE Participant mean age ≤ 65 years
Strobach 2000	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Stromberg 2005	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Sweeney 1989	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Tai 2014	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Touchette, 2012	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Towfighi 2017	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Tu 1999	EXCLUDE Setting = participants not living in community or discharged from hospital to community
Tu 2018	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (hypertensive medications only)
Vaillant‐Roussel 2016	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Valimaki 2017	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Varleta 2017	EXCLUDE Participant mean age ≤ 65 years, or more than 20% aged 65 years
Varma 1999	EXCLUDE Medications = unable to determine whether > 4 medications (trial authors did not collect this information)
Verbeek 2016	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Via‐Sosa 2013	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Villani 2014	EXCLUDE Medications = unable to determine whether > 4 medications (no response from trial authors)
Vinks 2009	EXCLUDE Study design not RCT, cluster‐RCT, nor quasi‐RCT
Vivian 2002	EXCLUDE Participant mean age ≤ 65 years
Vollmer 2014	EXCLUDE Participant mean age ≤ 65 years
Wakefield 2011	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Wakefield 2012	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Wandless 1981	EXCLUDE Medications < 4 regular medications or group mean ≤ 4
Wang 2013	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Wild 2016	EXCLUDE Participant mean age ≤ 65 years
Williams 2004	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (adherence to diabetic medication only)
Williford 1995	EXCLUDE Participant mean age ≤ 65 years
Yatabe 2018	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (hypertension medications only)
Yu 2012	EXCLUDE Participant mean age ≤ 65 years
Zermansky 2002	EXCLUDE Outcome = not medication adherence nor medication‐taking ability
Zhao 2004	EXCLUDE Participant mean age ≤ 65 years
Zhao 2015	EXCLUDE Medications = unable to determine if > 4 medications (trial authors did not provide information regarding number of medications)
李静, 2017	EXCLUDE Medications < 4 regular medications or group mean ≤ 4 (hypertension medications only)

BP: blood pressure.

COPD: chronic obstructive pulmonary disease.

CV: cardiovascular.

CVD: cardiovascular disease.

GP: general practitioner.

RCT: randomised controlled trial.

TB: tuberculosis.

Characteristics of studies awaiting classification [ordered by study ID]

ACTRN12606000247572.

Methods	RCT
Participants	Inclusion: (i) Australian veteran or war widow(er)s living in the community aged 39 to 97 years; (ii) receiving more than 5 medicines every day; or (iii) having 3 or more concurrent medical conditions. Participation restricted to veterans who are willing to use just 1 local medical officer (LMO) and 1 community pharmacy for the duration of the trial, and whose LMO and community pharmacy are willing to participate Exclusion: already using a DAA, residing in an aged care facility, or participating in other studies with similar aims
Interventions	Intervention: involved the veteran's local medical officer (LMO) prescribing a DAA in which the veteran's pharmacy packed and dispensed the veteran's medication for the 12 months of the intervention phase Control: usual care
Outcomes	Change in adherence and number of medications found in the home, change in GP‐rated severity of illness
Notes	ACTRN12606000247572 First enrolment December 2000. No protocol nor results published Investigators could not be contacted

ACTRN12611000452998.

Methods	RCT
Participants	Inclusion: aged 18 to 80 years and with a working diagnosis of acute coronary syndrome, who are admitted to 2 public, acute care hospitals, will be screened for enrolment into the trial Exclusion: not being discharged home, documented cognitive decline, non‐Medicare eligibility, presence of a terminal malignancy
Interventions	Intervention: patients will be offered usual post‐discharge care and a directed home medicines review at 2 months post discharge (i.e. acute coronary syndrome as a referral trigger). The pharmacist review should occur at or near 2 months post discharge. Accredited pharmacists completing the reviews will be given additional training and a brief assessment quiz on evidence‐based management of acute coronary syndrome (ACS) and how to include this into an ACS‐specific home medicine review Control: usual care
Outcomes	Primary outcome will be the proportion of patients who are adherent to a complete, guideline‐based medication regimen (using medication possession ratio assessed by dispensing records). Secondary outcomes will include hospital re‐admission rates, length of hospital stays, changes in quality of life, smoking cessation rates, cardiac rehabilitation completion rates, and mortality
Notes	ACTRN12611000452998 First enrolment 25/04/2012. Protocol published 2012. Intending to publish results soon Investigator contacted: Dr. Bernal (email: ddbernal@utas.edu.au) confirmed participant mean age > 65 years and mean number of medications > 4

ACTRN12616000910404.

Methods	Sequential mixed methods with a nested pilot RCT
Participants	Inclusion: 18 years or older; established diagnosis of cardiac disease and referred to cardiac rehabilitation; ≥ 1 cardioprotective medication; must have primary responsibility for taking medications; able to speak, read, and understand English; own a mobile phone (able to receive and reply to phone/text messages); willing to give written and oral consent; ≥ 1 medication non‐adherence factor
Interventions	Patients identified as non‐adherent based on the result of exploratory phases (phases 1 and 2) will be invited to participate in the pilot randomised controlled trial (RCT) phase Intervention: participants will receive usual care plus behavioural counselling about medication adherence using motivational interviewing (MINT) techniques and text message reminders (TM). Each patient will receive approximately 30 to 40 minutes of a single MINT counselling session by the researcher following recruitment. The MINT counselling will be delivered by the researcher, who is a registered nurse. TM will be sent to participants: 1 text message daily for 2 weeks, then on alternate days for 2 weeks, then on a weekly basis for the next 6 months Control: usual care
Outcomes	Self‐reported medication adherence rate ‐ assessed by Medication Adherence Questionnaire (MAQ)
Notes	ACTRN12616000910404 First enrolment: 1/09/2016. Last data collection: 03/07/17 Trial not completed due to lack of participants within inclusion criteria. Manuscript currently under review (January 2019) Investigator contacted: Dr. Ali Al‐Ganmi (email: ali.h.al‐ganmi@student.uts.edu.au) provided unpublished data: 120 participants = 82 (68.3%) aged 65 years or older, 66 (55%) used 4 or more medications

ACTRN12617000665336.

Methods	RCT
Participants	Inclusion criteria: (1) attend medical follow‐up in Specialized Out‐Patient Clinic (SOPC) of the Department of Medicine, (2) are 65 years or older, (3) have hyperpolypharmacy (defined as 10 or more regular drugs, and (4) agree to provide oral informed consent Exclusion criteria: (1) patients who are cognitively impaired (defined as a clinical diagnosis of dementia or mild cognitive impairment and/or not communicable and do not have caregivers, (2) patients who had received pharmacist medication review within 6 months before randomisation
Interventions	Intervention: patients receive a pharmacist medication chart review, which includes assessing the appropriateness of each of the regular medications based on laboratory findings, medication lists, consultation and discharge notes, procedures, and test results. Face‐to‐face interview (lasts around 30 to 45 minutes) will then be conducted with patients on the day before SOPC follow‐up. Clinical pharmacists will assess drug use history, identify drug‐related problems, and provide drug therapy interventions through written pharmacist note to physicians during SOPC follow‐up, based on the medication chart review and the above pharmaceutical assessments. Immediately after SOPC follow‐up, clinical pharmacist will provide education (which lasts about 15 minutes) on drug‐related problem identified before the visit, reinforce physician’s instruction, and encourage drug compliance using written patient educational leaflets. Phone follow‐up will be conducted 1 month after the pharmacist intervention Control: usual care at SOPC
Outcomes	Medication adherence measured by Morisky Medication Adherence Scale (MMAS‐4), change in number of drug‐related problems, 30‐day unplanned hospital admission, patient satisfaction
Notes	ACTRN12617000665336 Start date: 7 March 2017. Anticipated last data collection: 30 September 2017 Project proposal published on trial registry website. No published results; unsure if study ever completed Investigator Miss Heidi Chan (email: cyh123@ha.org.hk) contacted for further information – no response

Ahmad 2010.

Methods	RCT
Participants	Inclusion: patients older than 60 years; using 5 or more prescription‐only chronically used drugs when admitted to the hospital; discharged from the department of cardiovascular disease, lung disease, or internal medicine Exclusion: discharged to nursing home, too confused to participate, terminally ill, unable to communicate in Dutch
Interventions	Intervention: systematic medication review by community pharmacists. Pharmacy technicians will counsel patients at home at baseline and at 1, 3, 6, 9, and 12 months, using cognitive‐behavioural therapy according to the theory of planned behaviour Control: usual care
Outcomes	Persistence of drug adherence, quality of life, re‐hospitalisation related to medicines and cost adherence, occurrence of drug‐related problems, attitudes toward drugs
Notes	NTR1194 Protocol published 2010. Baseline (qualitative) published 2012. Conference abstract 2017 Investigator contacted for follow‐up adherence data ‐ no response

Cao 2017.

Methods	RCT
Participants	Inclusion: (i) aged ≥18 years; (ii) diagnosed with coronary heart disease and admitted for the first time; (iii) lived in the central districts of Chengdu; (iv) returned to the home residence, not to long‐term care facilities, after discharge; (v) could be contacted by mobile phone after discharge; and (vi) agreed to participate in the study Exclusion: patients with visual or hearing impairment, mental disorder, or dementia
Interventions	Intervention: transitional care programme. (1) Cardiologist and hospital nurse evaluated medications at admission; (2) cardiologist educated patients about medications during hospital stay and nurse provided written self‐management advice; (3) written and individualised discharge plan developed by cardiologist, nurse, patient, and caregiver day before discharge, (4) post‐discharge nurse sent discharge plan to home nurse, who created electronic health record and notified family physician. Nurse and physician provided structured telephone calls to patients during weeks after discharge Control: usual care
Outcomes	Medicine adherence using 8‐item Morisky Medication Adherence Scale, hospital re‐admission rates after discharge, chronic disease self‐efficacy, quality of care transitions
Notes	Results published 2017 Mean/median number of medications unclear ‐ investigator contacted, no response

Char 2017.

Methods	RCT
Participants	Inclusion: ≥ 21 years old; taking ≥ 5 long‐term medications; self‐administering own medication (or accompanied by caregiver); able to speak English, Mandarin, or Malay; attending first follow‐up visit to clinic for chronic disease management following recent discharge from a local public hospital or emergency department short stay ward Exclusion: nursing home residents, attending clinic for acute condition, or unwilling to consent to 30‐day follow‐up phone call
Interventions	Intervention: pharmacist conducted medication reconciliation with patient before physician consultation and best possible medication history was created Control: usual care Both groups underwent medication reconciliation with a different pharmacist after physician visits
Outcomes	Medication adherence using 8‐item Morisky Medication Adherence Scale (MMAS‐8), rehospitalisation
Notes	Not published – was retracted from journal; trial author (Dr. Kok Wai) contacted for unpublished manuscript and stated desire to change journal Note: mean age 74.8/73.7, thus eligible

Cheema 2017.

Methods	RCT
Participants	Patients will be identified from a larger study, TAPER (Team Approach to Polypharmacy Evaluation and Reduction) Inclusion: 70 years or older, currently taking 5 or more medications, did not have a recent comprehensive medication review, participating family doctor as most responsible provider, patient of the McMaster Family Health Team Exclusion: English language or cognitive skills inadequate to understand and respond to rating scales. Terminal illness or other circumstance precluding 13‐month study period
Interventions	Intervention: a medication wallet card will be given to the intervention group. This will be personalised for each patient and will include the patient's medications, dosages, and medical conditions. It will be personally given to a patient after a medical appointment with the family physician Control (placebo intervention): a reminder card will be given to this group. The card will not be personal and will be mailed to patients. It will state, "Remember to keep an up‐to‐date listing of your medications and bring your medications to your doctor's appointments"
Outcomes	Quote: “quantification of medication discrepancies (including dosages and frequency, unidentified discontinued medications, and those prescribed by others not included in electronic medication record)”
Notes	NCT02820129 Start date: July 2016. Estimated completion: December 2018 Conference abstract 2017; no other published results found Unclear whether primary outcome relevant. Investigator A/Prof Ainsley Moore (email: amoore@mcmaster.ca) contacted for further information – no response

ChiCTR‐TRC‐12002106.

Methods	RCT
Participants	Inclusion: aged ≥ 65, with acute coronary syndrome in department of cardiology of West China Hospital, Sichuan University Exclusion: lacked self‐care ability; did not ensure buying medicine at the same site; refused to attend the test or sign the consent form
Interventions	Intervention: patients given picture album of daily self‐questionnaires for improving medication adherence in addition to conventional drug education Control: usual care (conventional drug education)
Outcomes	Adherence rate (unclear how this is measured)
Notes	http://www.chictr.org.cn/showproj.aspx?proj=7443 Investigators (email: hmaochen@vip.sina.com) contacted for results ‐ no response Need to determine mean/median number of medications to confirm eligibility

Demers 2014.

Methods	Pilot RCT
Participants	Inclusion: patients with heart failure
Interventions	Intervention: multi‐component intervention to enhance HF care after discharge, with or without the support of a CP for the patient. The 3‐month intervention included: (1) a talking scale, (2) a diuretic decision support tool, (3) literacy‐sensitive HF home‐based educational sessions, and (4) an HF‐specific hospital discharge summary sent immediately to the primary care physician
Outcomes	Medication adherence with the medication possession ratio; self‐care was assessed using the SCHFI for the patient and CP; HF knowledge was explored with the Knowledge Assessment questionnaire; CP burden was measured with the modified Oberst Scale
Notes	Conference abstract only Patient enrolment started in October 2012 with last follow‐up visit planned for July 2014. Full results plan for submission January 2019 Age and number of medications unknown (mean age of first 85 patients recruited was 76 years) Investigator contacted: Dr. Catherine Demers, Hamilton Health Sciences, Canada

Flink 2016.

Methods	RCT
Participants	Inclusion: 18 years or older with COPD or congestive heart failure admitted at a short‐term medical ward and living in own private home Exclusion: diagnosis of dementia, need for an interpreter to communicate in Swedish
Interventions	Intervention: included patients' transition to home will be bridged through a telephone call from a patient activation coach 2 days post discharge. Patients will thereafter have motivational interviewing sessions by the same patient activation coach with the goal that patients are motivated to acquire the knowledge, skills, and confidence needed to manage the 4 main activity areas: (1) medication management; (2) adherence to care plan/follow‐up visits according to the discharge plan; (3) recognition of indications (symptoms/signs) that the condition is worsening and how to respond; and (4) contact with and management of relations/encounters with healthcare providers. Patients in control group will receive standard care (i.e. discharge and follow‐up as in normal procedures) Control: usual care
Outcomes	Medication adherence (Morisky), rehospitalisation, healthcare usage, patient activation, health‐related quality of life, basic psychological needs, depression
Notes	NCT02823795 Protocol published 2016. Estimated study completion date September 2018 Need to determine mean/median age and number of medications to confirm eligibility Investigator Dr. Maria Flink (email: maria.flink@ki.se) contacted for more information ‐ no response

Madarshahian 2018.

Methods	RCT
Participants	Inclusion: > 50 years, history of stroke longer than 1 year, more than 5 years of schooling, recruited from neurology and stroke clinic
Interventions	Intervention: key family members taught in small groups according to their educational needs Control: unclear (? usual care)
Outcomes	Medication adherence using Morisky Medication Adherence Scale (MMAS), cognition (MMSE)
Notes	Conference abstract only. Unable to find any published protocol or results Investigator F. Madarshahian contacted – no response Note: need to determine mean/median age and mean/median number of medications to confirm eligibility

Marusic 2018.

Methods	RCT
Participants	Inclusion: ≥ 18 years old, T2DM diagnosis, hospital discharge to the community Exclusion: cognitive disorders, terminal illness (< 1 month life expectancy), transfer to other hospital or discharge to a long‐term care facility, refusal to participate
Interventions	Intervention: participants received additional 30‐minute individual pre‐discharge pharmacotherapeutic education by a qualified physician about discharge medication (indications, dosage, administration, importance of adherence, and possible adverse drug reactions). Participants were given the same information in writing Control: usual care Both groups during the hospital stay received standardised diabetes education, including education about the disease, diet, physical activity, alcohol intake, smoking, diabetes medications, glucose self‐monitoring, and acute and chronic diabetes complications
Outcomes	Medication adherence using pill count, adverse drug reactions, hospital re‐admissions, emergency department visits, and mortality
Notes	NCT03438162; completed trial Note: median age 72/71, mean number of prescribed drugs 7.5/7.3

Muth 2018.

Methods	Cluster‐RCT
Participants	Clinic inclusion: providing primary care under the German statutory health insurance system, at least 1 healthcare assistant staff member able to access the Internet Clinic exclusion: practices specialising in unconventional treatments or in special indications (e.g. HIV) Participant inclusion: ≥ 60 years old, ≥ 3 chronic conditions (affecting ≥ 2 different organ systems) under pharmacological treatment, ≥ 5 long‐term prescription drugs with systemic effects, made ≥ 1 practice visit during the past quarter, able to fill in questionnaires and participate in telephone interviews Participant exclusion: MMSE < 26, life expectancy ≤ 12 months, alcohol and drug abuse, participation in another clinical trial 30 days before inclusion
Interventions	Intervention: 4 elements: (1) a brown bag review, and (2) a checklist‐based preconsultation interview with the patient conducted by the healthcare assistant, (3) a computerised decision support system (CDSS)‐assisted medication review carried out by the GP, and (4) a GP–patient consultation to optimise and prioritise medication Control: usual care Both groups: practice team received GP guidelines for ambulatory geriatric care
Outcomes	Medication adherence using Morisky and observed adherence (difference between patient‐reported and GP‐prescribed), hospitalisations, quality of life (EQ‐5D), functional status (Vulnerable Elderly Survey‐13 items)
Notes	ISRCTN99526053; NCT01171339 ‐ completed trial Note: this is the full report of the Muth 2016 pilot study

NCT00560001.

Methods	RCT
Participants	Inclusion: coming up for regular review in case or medication management; requiring medication management services; having 2 or more doses of medication per day; having someone to fill MD.2; in independent living (may be assisted living with NO medication management services); expected to live through follow‐up period of 6 months; having an active phone line that can be utilised by the MD.2 system Exclusion: having someone available to administer medications for every dose; having someone in household who is likely to interfere with MD.2; blind and deaf; eligible for hospice; having an MD.2 currently
Interventions	Intervention: MD.2 medication dispenser machine that provides verbal and auditory explicit reminders for individuals to take their medication Control: usual care (i.e. no MD.2 machine)
Outcomes	Medication adherence (unclear if just for intervention group), hospitalisations, emergency department visits
Notes	NCT00560001 Start date: January 2006. Estimated completion: May 2008 No published protocol or results Investigator Karen Farris contacted (email: karen-farris@uiowa.edu) – no response Note: unable to confirm eligibility as mean/median number of medications unclear

NCT00916214.

Methods	RCT
Participants	Inclusion: > 65 years taking > 2 medications Exclusion: living in nursing home, people receiving unit dose dispensing by medicine
Interventions	Intervention: pharmaceutical care programme involving individualised medication education and regular follow‐up Control: unclear (? usual care)
Outcomes	Medication adherence (unclear how it was measured)
Notes	NCT00916214 Start date: June 2009. End date: June 2011 No published protocol or results Investigator Muhammad Saeed not contactable Note: need to determine mean/median number of medications to confirm eligibility

NCT01105104.

Methods	RCT
Participants	Inclusion: ≥ 55 years, coming in for routine outpatient visits, speaks and reads English, history of high blood pressure, systolic BP ≥ 130 mmHg, using antihypertensive medication, using ≥ 2 prescription medications, plans to stay in area for the 9 months of the study Exclusion: receives personal help or reminders to take medication, moderate to severe dementia (MMSE < 18), severe hearing or vision deficiency
Interventions	Intervention: MedMinder System. Participants will receive a fully activated reminder unit as well as at least 1 call per month from a counsellor. The in‐home ReMinder will use a familiar pillbox layout (4 doses/d for 7 days) and will allow easy removal of medication cups by elderly, rheumatic fingers. The built‐in pager will continuously download remotely programmed visual and/or aural prompts and reminders from a central server (RemoteMind). It will continuously upload the date and time when each medication cup is removed, and when weekly refill is carried out, enabling remote adherence monitoring, alerts to caregivers, and follow‐up intervention(s) from personal and/or professional caregivers as needed Control: MedMinder deactivated. Participants will receive a 1‐way reminder unit that will remotely transmit information on medication adherence
Outcomes	Medication adherence, change in self‐efficacy about taking medication, self‐reported medication‐taking, change in systolic blood pressure
Notes	NCT01105104 Start date: September 2011. Estimated completion: June 2013 Investigator Dr. Sundar Natarajan (sundar.natarajan@va.gov) contacted for results ‐ no response Note: need to determine mean/median participant age and number of medications to confirm eligibility

NCT01534559.

Methods	RCT
Participants	Inclusion: > 18 years admitted to hospital and meeting at least 1 of the following: ≥ 5 medications, ≥ 3 changes to medication in hospital, past history of medication‐related problems, patient referred to medicines management clinic service by hospital doctor or pharmacist due to concerns about ability to manage medicines
Interventions	Intervention: medicines management clinic within an outpatient setting as well as follow‐up telephone calls from a clinical pharmacist (extension of ongoing integrated medicines management programme (IMMP))
Outcomes	Medication adherence (using medication adherence report scale and beliefs about medicines questionnaire), time to re‐admission to hospital, number of re‐admissions, number of GP consultations/home visits, number of accident and emergency visits, health‐related quality of life, cost utility analysis
Notes	NCT01534559 Study start date: November 2014. Final data collection: December 2017 Manuscripts currently being drafted Investigator Anita Hogg (email: anita.hogg@northerntrust.hscni.net) contacted and confirmed participant mean age > 65 years and mean number of medications > 4

NCT02047448.

Methods	RCT
Participants	Inclusion: 18 years and older, admitted to hospital with heart failure or COPD, anticipated eventual discharge to home, agreeable to participate in monthly counselling sessions Exclusion: cognitive impairment, non‐English speaking, anticipated discharge to a long‐term care or skilled nursing facility, permanent long‐term care facility resident, surgical patient, hospice patient, patients who die within 30 days of initial hospitalisation
Interventions	Intervention: hospital pharmacist will meet with the patient and complete medication reconciliation, assess patient's understanding of the medications, and identify medication‐related problems. Hospital pharmacist will complete a pharmacist discharge care plan, and a copy will be sent to the participating community pharmacist. Patients will be scheduled for the first meeting with their community pharmacist within 1 week of hospital discharge. Community pharmacist will interview the patient about his or her general health and any current symptoms of heart failure or COPD, identify any additional medication‐related problems, follow up on any issues as described in the pharmacist discharge care plan, and provide patient education. Patients will then meet with their community pharmacist for counselling and patient education at monthly intervals for 6 months following hospital discharge Control: usual care
Outcomes	Medication adherence (proportion of days covered calculation), medication‐related problems, patient satisfaction, hospital re‐admissions or ED visits
Notes	NCT02047448 Note: need to determine mean/median age and mean/median number of medications to confirm eligibility Contacted investigator ‐ A/Prof Judith Kristeller, Wilkes University ‐ no response

NCT02424786.

Methods	RCT
Participants	Inclusion: patients > 65 years in dialysis treatment or with CKD stage 5
Interventions	Medication lists from patients randomised to the intervention group will be evaluated by the research physician with the help of STOPP/START criteria Feedback on this screening will be given to the team responsible for patient treatment
Outcomes	Medication non‐adherence ‐ measured by Morisky Medication Adherence Scale and visual adherence scale Secondary outcomes: improvement in polypharmacy, associations between beliefs about medication/anxiety/depression with adherence and QoL, predictors of non‐adherence, risk factors for non‐adherence, changes in number of inappropriate medications
Notes	NCT02424786 Start date: May 2015. Study completion: September 2017 Results manuscripts currently being prepared Investigator contacted ‐ Krystina Parker confirmed: 180 patients, mean number of medications 11.1 (range 4 to 19)

NCT02842840.

Methods	RCT
Participants	Inclusion: participants aged > 65 years and able to give informed consent Exclusion: recurrent stroke, diagnosis of subarachnoid haemorrhage, significant impairments precluding participation, another condition likely to impact participation (e.g. life‐threatening condition), expected discharge to hospital/nursing home setting
Interventions	Intervention: combined patient and family‐based intervention involving behavioural treatment and series of educational/motivational interventions Control: usual care
Outcomes	Patient‐reported medication adherence rating scale, changes in blood pressure, changes in intention to medication adherence, changes in action plan, changes in coping plan, changes in quality of life, changes in perceived behavioural control of medication adherence, changes in self‐monitoring of medication adherence, changes in illness perceptions (Brief Illness Perception Questionnaire)
Notes	NCT02842840 Estimated study completion: November 2017 Investigator contacted (email: amir.pakpour@gmail.com) ‐ no results provided, currently being analysed Note: need to determine mean/median number of medications to confirm eligibility

NCT03156348.

Methods	RCT (3 groups)
Participants	Inclusion: patients 60 years or older attended by the staff of internists of the internal medicine service of the Clinical Hospital of the University of Chile for acute condition or decompensation of chronic pathology; with estimated survival > 6 months; on pharmacological therapy; having a contact person or responsible caregiver willing to comply with the scheduled care plan; and having a contact telephone number Exclusion: cognitive impairment and no caregiver, any other condition that in the judgement of the research team affects the quality of the collection of information
Interventions	Intervention: during hospitalisation and at discharge, a clinical pharmacist (CP) will monitor daily pharmacological safety and efficacy of the medication to assess and make appropriate recommendations. CP will explain the reasons for use of each of the drugs. At 30 days post discharge, CP will review the updated clinical record of the patient and will conduct a home visit to enhance and ask about adherence, self‐medication, medication use at that time, and possible results of laboratory tests performed and to clarify doubts regarding the use of current medications. The same activities will be conducted at 60 days by telephonic way, to reinforce the recommendations Parallel control: usual care by team with training on pharmacogeriatrics Historical control group: usual care (no training)
Outcomes	Adherence measured with Morisky and Green scale, adverse drug events, hospitalisations, prevalence of self‐medication (taking a drug without medical indications)
Notes	NCT03156348 Start date: May 2015. Estimated completion: December 2017 Investigators contacted for more information (email: comiteetica@hcuch.cl) ‐ no response Note: need to determine mean/median number of medications to confirm eligibility

NCT03162848.

Methods	Pilot RCT
Participants	Inclusion: 50 years or older; heart failure diagnosis; prescribed diuretics; self‐administering medications; able to open an electronic cap; able to speak, hear, and understand English; not hospitalised; no cognitive impairment
Interventions	Intervention: The SystemCHANGE™ intervention utilises the socioecological model and the Plan‐Do‐Check Act model as its framework and focuses on changing the individual's environment to change behaviour using small experiments with feedback. At initial home visit, the PI will work with the participant to identify important people for medication‐taking, routines, and cycles of routines. Possible solutions to incorporate medication‐taking into routines will be identified by the participant and the PI, and the participant will start to implement these solutions. Medication adherence will continuously be monitored via medication event monitoring systems. At 1 month, the participant will be sent a report on medication‐taking and a phone call with the PI will occur to discuss whether solutions improved medication adherence or whether other solutions need to be implemented. At month 2, the intervention will end but participants are urged to continue to use solutions long term Control: usual care with education at baseline, 1 month, and 2 months
Outcomes	Medication adherence using medication event monitoring systems, acceptability and feasibility using open‐ended questionnaire, systems thinking using questionnaire, Kansas City Cardiomyopathy questionnaire
Notes	NCT03162848 No protocol or results published. Estimated study completion date: July 2018 Need to determine mean/median number of medications to confirm eligibility Investigator contacted for more information ‐ no response Investigator contacted: Angela Andrews, University of Missouri, Kansas City

Ostbring 2018.

Methods	RCT
Participants	Inclusion: 18 years or older, admitted for angiography, verified coronary artery disease, planned for follow‐up at the outpatient clinic, Swedish speaking Exclusion: cognitive impairment or any other condition making interview or phone calls impossible, non‐participation in standard follow‐up, prior participation in this study (pilot)
Interventions	Intervention: medication review and motivational interviewing (MI) for patients with coronary heart disease (CHD). Clinical pharmacists competent in MI and cardiology will conduct medication interviews and medication reviews at the outpatient clinic. Intervention will continue during 9 months, with interviews and reviews as needed. Follow‐up of results will take place 16 months after inclusion (corresponding to 4 months after end of intervention) Control: usual care
Outcomes	Cholesterol levels, percentage of patients adherent to individual medications (cholesterol, ACE inhibitors, acetylsalicylic acid, PSY‐12 antagonist, and beta‐blocker), blood pressure, quality of life, hospital re‐admissions, emergency department visits
Notes	NCT02102503 Protocol published 2018. Extension of earlier pilot study (Ostbring 2014), which was excluded due to short follow‐up Unclear whether overall adherence measure will be provided. Age and number of medications unavailable (but pilot study met eligibility) Publication anticipated 2019

Prados‐Torres 2017.

Methods	Cluster‐RCT
Participants	Inclusion: 65 to 74 years, multi‐morbidity (3 or more chronic diseases), polypharmacy (5 or more drugs taken for at least 3 months), at least 1 visit to family physician in past year, agree to participate and provide written informed consent Exclusion: institutionalised at nursing home or similar, life expectancy < 12 months, mental and/or physical conditions considered by family physician to prevent fulfilment of study requirements
Interventions	Intervention: family physicians receive training related to multi‐morbidity, appropriateness of prescribing, treatment adherence, Ariadne principles, and physician‐patient shared decision‐making. Then physicians conduct physician‐patient interviews based on Ariadne principles including structured review of treatment plan, inclusion of patient preferences, and a pharmacological treatment plan Control: usual care
Outcomes	Medication adherence using Morisky‐Green questionnaire and Haynes‐Sackett questionnaire, health‐related quality of life (EQ‐5D‐5L), use of health services (hospitalisations, emergency services, and primary care), medication safety (incidence of adverse drug reactions), and cost utility (time spent on training family physicians, cost of teaching staff, time spent on physician‐patient interviews, utilities measured using the EuroQol‐5D‐5L)
Notes	NCT02866799 Start date: November 2016. End date: February 2018 Protocol published 2017. Results not yet published Investigator: Alexandra Prados‐Torres (email: sprados.iacs@aragon.es)

Reilly 2016.

Methods	Pilot RCT
Participants	Inclusion: 60 inpatients with congestive heart failure
Interventions	Intervention: multi‐component health education intervention that combines (a) an interactive computer‐based CHF education video viewed during hospital stay and geared toward helping patients understand CHF and its management, (b) educational weekly mailings to reinforce the Kognito video, and (c) 4‐weekly post‐discharge phone counselling using motivational interviewing techniques
Outcomes	Medication adherence using the Morisky Medication Adherence Scale, Atlanta HF Knowledge Score, HF‐specific quality of life using the Minnesota Living With Heart Failure questionnaire (HF‐specific), general quality of life using the SF‐36 physical component score, diet adherence using sodium intake estimated from 24‐hour dietary recall
Notes	Conference abstract published 2016. No full paper Investigator contacted: Dr. Natarajan Sundar (email: Sundar.Natarajan@nyulangone.org). Intention to publish, not published yet Age and number of medications unknown ‐ trial author believes > 65 years and > 4 medications. Need to confirm when results available

ACS: acute coronary syndrome.

COPD: chronic obstructive pulmonary disease.

CP: clinical pharmacist.

DAA: dose administration aid.

GP: general practitioner.

HF: heart failure.

LMO: local medical officer.

MAQ: Medication Adherence Questionnaire.

MINT: motivational interviewing technique.

MMAS: Morisky Medication Adherence Scale.

MMSE: Mini‐Mental State Examination.

RCT: randomised controlled trial.

SCHFI: Self‐Care Heart Failure Index.

SOPC: Specialized Out‐Patient Clinic.

T2DM: type 2 diabetes mellitus.

TM: text message.

Characteristics of ongoing studies [ordered by study ID]

Adam 2019.

Study name	OPtimising thERapy to Prevent Avoidable Hospital Admissions in the Multimorbid Older People (OPERAM)
Methods	Multi‐centre cluster‐RCT
Participants	Inclusion: hospitalised patients ≥ 70 years with ≥ 3 chronic medical conditions and concurrent use of ≥ 5 long‐term medications at 1 of 4 participating study centres Exclusion: inability to provide informed consent, direct admission to palliative care (< 24 hours after admission), has passed or will pass a systematic structured drug review during this hospitalisation or within last 2 months
Interventions	Intervention group: Systematic Tool to Reduce Inappropriate Prescribing (STRIP) intervention during initial hospital admission (index hospitalisation) or an equivalent situation for outpatients. STRIP intervention consists of 9 steps: (1) structured history‐taking of medication; (2) recording of medication and diagnoses in decision‐support software, (3) structured drug review based; (4) communication and discussion of structured drug review with prescribing physician; (5) shared decision‐making with patient; (6) optional revision based on new accumulating data during hospitalisation (e.g. new diagnoses, adverse drug reactions); (7) generation of GP report; (8) delivery of the report to the patient and to the GP; (9) follow‐up Control group: receive usual care and 1 questionnaire will be conducted by the intervention team in both arms, which is considered a sham intervention Patients will be followed up by phone at 2, 6, and 12 months
Outcomes	Drug compliance using Morisky Mediation Adherence Questionnaire (MMAS‐8), healthcare utilisation, hospitalisations, mortality, adverse medical events (including adverse drug events and number of falls), quality of life using EQ‐5D
Starting date	Start date: December 2016. Anticipated completion: 2019
Contact information	Professor Nicolas Rodondi (email: nicolas.rodondi@insel.ch)
Notes	NCT02986425 Protocol published 2019. Communication with investigator; results expected early 2020

Bailey 2017.

Study name	A Universal Medication Schedule to Promote Adherence to Complex Drug Regimens
Methods	RCT Four groups: (1) enhanced usual care alone; (2) daily medication reminders via SMS text messages; (3) medication monitoring via a patient portal‐based assessment; (4) both SMS text message reminders and portal‐based medication monitoring
Participants	Inclusion: (1) age 50 years and older, (2) English or Spanish speaking, (3) currently prescribed 3 or more medications used on a regular basis, (4) primary responsibility for administering one’s own medication, (5) owns a cell phone and feels comfortable receiving texts, (6) Internet access at home, (7) a personal email account, and (8) basic familiarity with text messaging and with using the Internet for email Exclusion: major cognitive, visual, or hearing impairment
Interventions	Enhanced usual care (EHR): patients will receive EHR tools (e.g. patient‐friendly medication lists) EHR + Text: EHR tools + text message reminders telling them to take their medicine EHR + Portal: EHR tools + enrolment into their clinic’s portal. Patients prompted every other week to fill out an online survey asking if they filled their medication and about any side effects or concerns. Concerns and questions followed up by nurse EHR + Text + Portal: EHR tools, text reminders, and portal communication (i.e. all interventions)
Outcomes	Medication adherence (self‐report, pill count, and proportion of days covered, with medication based on pharmacy claims), clinical markers (HbA1c, blood pressure, and cholesterol)
Starting date	Start date: April 2017. Anticipated completion date: March 2020
Contact information	Dr. Stacey Bailey (email: scbailey@unc.edu)
Notes	NCT02820753 Protocol published 2017 Need to confirm mean/median age > 65 years when results are available

Dodge 2018.

Study name	Internet‐Based Conversational Engagement Clinical Trial (I‐CONNECT study)
Methods	RCT
Participants	Socially isolated participants aged 80 and older (Lubben's Social Network Scale Y 12 and other criteria) will be recruited from a local Meals on Wheels programme in Portland, Oregon, and Detroit, Michigan, the latter targeting African American participants Note: website states participants aged 75 and older
Interventions	Intervention: face‐to‐face communications with trained interviewers using an Internet‐enabled link to a study‐dedicated home computer will be conducted 4 times per week for 6 months and twice per week for additional 6 months Control: brief weekly phone calls
Outcomes	Medication adherence monitored by an electronic pillbox (MedTracker), cognitive function in memory and executive domains
Starting date	Start: 2018. Results expected: 2023
Contact information	Dr. Hiroko Dodge (email: dodgeh@ohsu.edu)
Notes	Two conference abstracts. Website: https://www.i-conect.org/ Investigator contacted ‐ results available 2023

ISRCTN13355076, 2018.

Study name	An educational intervention to promote health‐related quality of life after an acute coronary syndrome
Methods	RCT
Participants	Inclusion: 21 years or older, hospitalised due to acute coronary syndrome, able to read and write in Portuguese, no diagnosed cognitive condition, able to provide informed consent
Interventions	Intervention: educational intervention. First session 1 hour lecturing and take‐home individualised information booklet on their heart condition, lifestyle changes, medication, etc. Second session involving telephone contact 10 days after discharge to reinforce teaching. Third session involving clinic or home visit to monitor participant’s lifestyle and discuss returning to work Control: usual care Participants in both groups will receive a calendar to register daily activity, number of smoked cigarettes, forgotten medicine, and any complications that may occur
Outcomes	Adherence to therapy, number of rehospitalisations, health‐related quality of life (EQ‐5D), clinical markers (body weight, blood pressure, lipids)
Starting date	Start date: February 2014. Anticipated end date: July 2019
Contact information	Maria Teresa Leal (email: tleal@esel.pt)
Notes	ISRCTN13355076 Investigator contacted for results – reported delay in start date, study still ongoing (September 2019) Need to determine mean/median age and number of medications to confirm eligibility once results are available

NCT03511027.

Study name	Medication dispenser to improve care at home for the elderly
Methods	RCT
Participants	Inclusion: 18 years and older, manage medications independently at home, stabilised on medication, mild to moderate cognitive/physical impairments, Montreal Cognitive Assessment (MoCA) not less than 16, English speaking Exclusion: absent from community for longer than 1 month during study, inability to access study site pharmacy following discharge
Interventions	All participants will undergo screening for self‐medication readiness, will receive self‐medication education by a study occupational therapist and a 5‐day self‐medication performance assessment by a registered nurse before discharge Intervention: medication self‐management education + orientation to Karie Automated Medication Delivery by the study Occupational Therapist (SME + K). Participants will use the Karie device for all applicable medications for the study duration Control: medication self‐management education (SME) by an occupational therapist followed by a 5‐day self‐medication performance assessment by a registered nurse before discharge. Patients will fill prescriptions as usual for duration of the study
Outcomes	Medication adherence using the Medication Adherence Questionnaire (MAQ) and medication 7‐day recall, self‐medication behaviours using the Self‐Efficacy for Appropriate Medication Scale (SEAMS), quality of life (EQ‐5D), health care consumption (hospitalisations, GP visits, and emergency department visits), economic analysis
Starting date	Start date: December 2018. Anticipated completion: September 2019
Contact information	Lee Verweel (email: lee.verweel@westpark.org)
Notes	NCT03511027; study protocol available on trial registry Investigator contacted – enrolment ongoing, no available results Need to determine mean/median age to confirm eligibility once results are available

NCT03722017.

Study name	Drug reduction in older patients: the DROP trial (DROP)
Methods	RCT
Participants	Inclusion: referred to short‐term stay, being discharged from Nashville VA hospital from a medicine or orthopaedics team, age 50 years or older, polypharmacy (> 5 medications), able to self‐consent or have a surrogate Exclusion: resides in long‐term care, on hospice, not expected to be discharged within 48 hours of referral
Interventions	Intervention: pharmacist or nurse practitioner will ascertain indication and de‐prescribing rationale for each medication identified during medication history‐taking. De‐prescribing recommendations will be made as appropriate Control: usual care (including structured interview and chart review by study pharmacist or nurse practitioner)
Outcomes	Medication adherence using 12‐item Adherence to Refills Medication Scale (ARMS), unplanned healthcare utilisation, adverse drug withdrawal events, mortality, number of falls, health status (long‐term care, hospice, or death)
Starting date	Start date: October 2019. Estimated completion: November 2021
Contact information	Dr. Sandra Simmons (email: Sandra.Simmons@Vanderbilt.edu)
Notes	NCT03722017 Need to determine mean/median age to confirm eligibility once results are available

Vasilevskis 2019.

Study name	A randomized controlled trial to de‐prescribe for older patients with polypharmacy transferred from the hospital to skilled nursing facilities (Shed‐Meds)
Methods	Randomised controlled trial ‐ 1 hospital and 14 area skilled nursing facilities
Participants	Inclusion: 50 years or older, hospitalised, Medicare‐eligible, discharged to a post‐acute care facility, > 5 medications, speaks English, primary home residence within one of 9 surrounding counties Exclusion: long‐term care, life expectancy < 6 months, enrolled in a clinical drug trial, stage IV cancer, incarcerated, homeless, unable to provide consent (and no surrogate)
Interventions	Inclusion: participants will receive a clinical review of their prescribed medications by a research clinician (pharmacist, physician, and/or nurse practitioner) followed by a patient interview to assess their willingness to discontinue or reduce some of their medicines based on clinical recommendations of the team. Hospital and outpatient providers also will be part of the de‐prescribing decision process. De‐prescribing actions will be initiated in the hospital before discharge and will continue through the skilled nursing facility stay Control: usual care
Outcomes	Changes in total number of medications, change in functional health status, change in drug burden index, change in medication adherence (using adherence to refills and medication scale)
Starting date	Study start date: March 2017. Completion date: April 2021
Contact information	Dr. Sandra Simmons, Vanderbilt University Medical Center (email:sandra.simmons@vanderbilt.edu)
Notes	NCT02979353 Pilot study published ‐ did not assess adherence Full study ongoing

Verweij 2018.

Study name	Cardiac Care Bridge trial (CCB‐trial)
Methods	RCT
Participants	Inclusion: 70 years and older, admitted to cardiology or cardiac surgery department, admission > 48 hours, high risk of functional decline Exclusion: MMSE < 15, congenital heart disease, terminal illness (< 3 months to live), transferred from or planned discharge to a nursing home, planned discharge to another hospital/department not participating in study, unable to communicate in Dutch, delirium confirmed by treating physician
Interventions	Intervention: patients will receive a comprehensive geriatric assessment (CGA) performed by a cardiac nurse and care based on CGA integrated care plan, face‐to‐face handover from the cardiac nurse with the community care registered nurse (CCRN) before discharge, and 4 home visits post discharge. CCRNs will collaborate with physical therapists who will perform home‐based cardiac rehabilitation, and with a pharmacist who advises CCRNs in medication management Control: usual care
Outcomes	Medication adherence using questionnaire and pharmacy dispensing records, unplanned hospital re‐admission, mortality, health‐related quality of life (EQ‐5D), healthcare utilisation (GP visits, physical therapy, cardiac rehabilitation), clinical parameters (e.g. cholesterol, blood pressure), cost‐effectiveness
Starting date	Start date: June 2017. Anticipated completion: March 2020
Contact information	Lotte Verweig (email: l.verweij@hva.nl)
Notes	NTR6316 Protocol published 2018 Investigator contacted to confirm eligibility regarding number of medications: at baseline, 74.5% and 81% of participants took 5 or more medications

ARMS: Adherence to Refills Medication Scale.

CCRN: community care registered nurse.

CGA: comprehensive geriatric assessment.

EHR: electronic health record.

EQ‐5D: EuroQoL Group Quality of Life Questionnaire based on 5 dimensions.

GP: general practitioner.

HbA1c: glycosylated haemoglobin.

K: Karie Automated Medication Delivery.

MAQ: Medication Adherence Questionnaire.

MMSE: Mini‐Mental State Examination.

MoCA: Montreal Cognitive Assessment.

SEAMS: Self‐Efficacy for Appropriate Medication Scale.

SME: self‐management education.

SMS: short message service.

Differences between protocol and review

The MEDLINE search strategy was updated by John Kis‐Rigo, the information specialist with the Cochrane Consumers and Communication Group, after the protocol was published but before the database search was performed. The updated search strategy contained additional terms to minimise the potential for missed studies.

Interventions were grouped as educational, behavioural, or mixed, which was not specified in our protocol. We believe this grouping was necessary to help describe and understand the large number of heterogeneous studies, and this grouping had been used in a previous systematic review of interventions to improve medication adherence (George 2008).

Risk factor(s) for poor medication‐taking ability and/or medication adherence targeted by the intervention(s) were not extracted. In general, this information was poorly reported within the included studies, as medication‐taking ability and/or medication adherence was not always the primary outcome of the included studies. We attempted to extract potential participant factors that may affect medication use (e.g. number of medications used, frailty, cognitive impairment, number of comorbidities); however even this was limited by poor reporting in the included studies. Analysis of specific risk factors targeted by interventions should be considered in future updates of this review, when further high‐quality studies are identified.

We could not conduct several subgroup analyses as planned due to an insufficient number of studies identified within each comparison and each outcome.

Contributions of authors

• Writing of protocol and review: AC, RE, JG

• Screening of titles and abstracts: AC, RE, KP, LK, JG

• Assessment of studies for inclusion: AC, RE, KP, LK, JG

• Quality assessment: AC, RE, KP, LK, JG

• Data extraction: AC, RE, KP, LK, JG

• Data entry into RevMan: AC

• Data analysis: AC in consultation with RE and JG

• Disagreement resolution: AC, RE, JG

Declarations of interest

Amanda J Cross: none declared.

Rohan A Elliott: none declared.

Kate Petrie: none declared

Lisha Kuruvilla: none declared

Johnson George has received investigator‐initiated research grants from Boehringer Ingelheim (2014), from Pfizer through the Global Research Awards for Nicotine Dependence (2017), and from GSK through Medical Education Grants (2018) for unrelated projects. He has also provided consultancy services to GSK (review of educational materials ‐ 2018) and Pfizer (delivering education sessions as part of CPD – 2019; not for promoting any particular product or molecule). These grants have been largely interdisciplinary and involved multiple investigators. He has not used any part of the funding for his salary or for other personal benefits. He has a tenured academic appointment at Monash University. These funds were paid to his employer (Monash University) and were used to support staff working on those projects or for professional development (e.g. conference attendance).

Rohan Elliott was an author of one study that was potentially eligible for inclusion in this review (Elliott 2012). To avoid bias, two independent members of the review team (AC and JG) screened this study and deemed that it was ineligible for inclusion.

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