Juanes 2018.

Study characteristics
Methods	Randomised controlled trial
Participants	118 participants randomised (59 to medication review and 59 to control) Patients 65 years or older, with a length of stay in ED longer than 12 hours, decompensation of HF and/or COPD and polypharmacy (4 or more drugs) were included from a tertiary referral hospital from Catalonia, Spain Mean age: 80 years 50% male Mean number of medications taken regularly at home: intervention 10.5 (3.5), control 10.0 (3.3)
Interventions	The intervention consisted of a pharmaceutical care programme focusing on the resolution of potential drug‐related problems, from admission to ED until discharge. The pharmaceutical care programme comprised the following steps: Obtaining and recording the medication chart. As part of this process, the pharmacist confirmed, by interviewing the patient or caregiver, the medication taken at home as listed in the electronic health records. Medication reconciliation in each of the care transitions. Medicine review and validation of physician prescriptions during the stay at the ED and during hospitalisation. This consisted of reviewing the following aspects of the patient’s medication: (a) the indication for each medication in relation to the patient’s condition and (b) the appropriateness of each medication, dose, schedule, duration of the treatment for the patient’s age and/or clinical status (renal function or liver function). In addition, therapeutic drug monitoring was performed for drugs with a narrow therapeutic range. Patient follow‐up. This consisted of evaluation of the effectiveness and safety of the treatment according to standard clinical practice and patients’ objective data from clinical records. Provision of additional written information at discharge, with clear indications for drug therapy regimen using software tools provided by the Catalan Drug Information Centre (CedimCat). Patients in the control group received standard pharmaceutical care, initiated at admission to the ward and consisting of medication review and prescriptions' validation, analogous to step 3 in the intervention group. The study compares the effects of an extended medication review and a basic medication review.
Outcomes	Primary outcome: drug‐related negative outcomes (DNO) defined as health problems that patients experience owing to drug use or non‐use Secondary outcomes: patients readmitted within 180 days to the same ED and/or to the hospital ward: patients readmitted owing to decompensation of HF and/or exacerbation of COPD within 180 days after inclusion in the study
Notes	Funding: not reported
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	Randomisation was performed by the hospital’s pharmacology department using SPSS V.18 (SPSS, Chicago, Illinois, USA) to create a dedicated application to randomise patients to one of the of 2 study groups (distribution 1:1). The application used a seed obtained by rolling two dice to select the row and column from a random‐number table; therefore, while replicable but unpredictable, the series was perfectly balanced between groups in 10‐case blocks.
Allocation concealment (selection bias)	High risk	Trial authors were contacted for clarification. They replied that the pharmacology department created the randomisation scheme. The pharmacist had access to the entire randomisation. After assessing the suitability of the patient through compliance of the inclusion criteria, the pharmacist assigned each individual a group according to the randomisation scheme, chronologically (in function of the onset of the episode in the ED) and correlative according to with the randomisation scheme. We assessed the risk of bias as high, because the pharmacist had access to the randomisation form (which was made in advance by rolling dice) and thus the allocation was not hidden (e.g. if 2 patients arrived at the same time).
Blinding of participants and personnel (performance bias) All outcomes	High risk	Neither patients nor healthcare professionals were blinded to the treatment group.
Blinding of outcome assessment (detection bias) Mortality (all‐cause)	Low risk	A single pharmacist was responsible for the implementation of the programme and the assessment of results, which might have led to observer bias. However, it is unlikely that it would affect mortality.
Blinding of outcome assessment (detection bias) Hospital readmissions (all‐cause)	Low risk	A single pharmacist was responsible for the implementation of the programme and the assessment of results, which might have led to observer bias. However, it is unlikely that it would affect hospital readmissions.
Blinding of outcome assessment (detection bias) Hospital emergency department contacts (all‐cause)	Low risk	A single pharmacist was responsible for the implementation of the programme and the assessment of results, which might have led to observer bias. However, it is unlikely that it would affect hospital emergency department contacts.
Incomplete outcome data (attrition bias) Mortality (all‐cause)	Low risk	States none lost to follow‐up.
Incomplete outcome data (attrition bias) Hospital readmissions (all‐cause)	Low risk	States none lost to follow‐up.
Incomplete outcome data (attrition bias) Hospital emergency department contacts (all‐cause)	Low risk	States none lost to follow‐up.
Selective reporting (reporting bias)	Low risk	Average cost of hospital stay is an outcome according to the clinical trial registration, but not reported or mentioned in the publication. However, as reported results are negative and cost‐effectiveness analyses are often published as secondary publication we therefore assessed the risk of selective reporting bias as low.
Contamination bias	High risk	No cluster‐randomisation.
Other bias	Low risk	No evidence of other types of bias.