| Disease |
| Primary versus secondary |
Mann et al. 2010; Lemstra et al. 2012; Xu et al. 2016; Chen et al. 2015 |
|
Similar findings across 100% of reviews.
Of 10 studies comparing adherence or persistence following MI to primary, 90% found better adherence in MI group, with one study non-significant.17 Primary group 52% less likely to adhere than secondary across 18 studies.20 Overall adherence 46% better for secondary prevention compared with primary prevention population at 1 year (PDC).22 Increased adherence following hospitalization in all studies11 and trend continues with number of subsequent hospitalizations.11
|
| Comorbidity- diabetes |
Mann et al. 2010; Lemstra and Alsabbagh 2014 |
Diabetes + |
Similar findings across both reviews, though variation at study level.
|
| Comorbidity- depression |
Khatib et al. 2014; Lemstra and Alsabbagh 2014; Eze-Nliam et al. 2010 |
Depression − |
Depression common barrier, identified in 42% of self-reported studies.14 Meta-analysis of five studies (eight cohorts) found 11% increased risk of nonadherence if depressed or prescribed anti-depressants.10 Only one cohort found inconsistencies.10 Of two studies looking at depression, one found reduced adherence and the other found a non-significant odd ratio.32 |
| Therapy |
| Drug Class |
Matchar et al. 2008; Powers et al. 2012; Lemstra and Alsabbagh 2014; Kronish et al. 2011; Bramlage et al. 2009 |
ARB’s + ACEi’s +/− CCB’s +/− BB’s +/− Diuretics – |
Found overall adherence was >90% for both ACEi and ARBs. In 11 studies of persistence all found higher continuation rate in ARBs (absolute difference of 7% between groups).12 Whether or not this difference is significant is not stated. 39 Studies of adherence or persistence. Nine studies which utilized pill counts found over 90% adherence to ARBs or ACEi’s (no significant difference) and persistence best with ARBs compared to ACEi’s.13 High level of agreement between studies: diuretics had an increased risk of non-adherence compared with ACEi’s (RR 1.36), ARB’s (RR1.47), CCB’s (RR1.35).10 Pooled analysis found higher risk of non-adherence in ACEi’s (RR1.30) and CCB’s (RR1.33) compared to ARBs.10 Across 17 studies, ARB’s consistently associated with better adherence (non-significant result in one study).27 Similarly diuretics found to be associated with poorer adherence in all but two studies—one non-significant result and another favoured diuretics compared to BB’s.27 ARB’s highest persistence in 87% of studies. Next best persistence found in ACEi’s, CCB’s, and then BBs. Diuretics lowest adherence rate in 100% of studies.28 |
| Dosing frequency/Treatment Regimen |
Assawasuwannakit et al. 2015; Bowry et al. 2011; Iskedjian et al. 2002; Ingersoll et al. 2008 |
High dosing freq. – High complexity +/− |
Largely consistent, as number of dosages per day increases adherence decreases.
As age increased, the reduction in adherence associated with dosing frequency became less significant.5 Divided into two subgroups: over 50% of patients take two or more drugs per day and group where less than 50% fall into this category. Found no significant difference in adherence levels between subgroups.8 Largely consistent across eight studies. Pooled results found average adherence of 91% for once-daily, which was 8% higher than for multiple daily dosing.23 Once daily was also higher compared to twice daily dosing (5% better for once daily).23 The difference in adherence rate between twice and multiple daily dosing groups was not significant. Across six studies assessing dosing regimen, adherence was best with once daily dosing compared to 2 per day in all but one study.24 Disease may play a role—the study which was not consistent looked specifically at patients with congestive heart failure while other studies looked at hypertension or CVD more generally.
|
| Healthcare |
| Cost |
Bowry et al. 2011; AlGhurair et al. 2012; Lemstra et al. 2012; Xu et al. 2016; Marshall et al. 2012; Maimaris et al. 2013, Mann et al. 2014 |
Higher costs − |
82% of studies found significant association between high medication cost and non-adherence.8 Financial burden and medication reimbursement cited as reasons for patient non-adherence in seven self-reported studies.6 Pooled result across six studies found that patients liable for co-payments are 28% less likely to be adherent.20 Cost/co-payment most commonly studied factor (29% studies).22
Nine studies (seven US, two Brazil) found cost cited as a barrier to non-adherence.29 14 Studies investigated medication costs or co-payments; seven cohort studies found lower adherence with higher costs, with one exception which found increased adherence at much higher co-payment levels. Remaining cross-sectional and case-control studies also found higher adherence associated with lower costs.30 Variable results across six studies. Some found greater levels of significance than others, though this related to how much patients had to pay (i.e. less significant if cost lower—backs up principle).One study inconsistent—found that higher co-payment reduced level of adherence, while all other found opposite.31
|
| Patient |
| Gender |
Lewey et al. 2013; Mann et al. 2010; Nielsen et al. 2017 |
Female gender +/- |
Inconsistent. Varied with setting.
10% less likely to be adherent in females compared to males across 53 studies.16 20% (n = 11) of studies found no difference between genders, all conducted in Canada.16 Female gender associated with lower adherence in 61% studies.17 In four studies carried out in LMIC’s women were less likely to adhere than men (OR 0.72).9
|
| Age |
Assawasuwannakit et al. 2015; Mann et al. 2010 |
Increasing age +/− |
Significant association between age and adherence in a 77% of studies, though not linear – adherence improved with ages up to 65 yrs, then declined in older adults.5 Studies which did not observe this tended to have an older study cohort and hence only found the decline in adherence associated with older age (over 65).5 Review only found improvement—8% increase in adherence per 10 years increase in age, though maximum age included was 66.7 years.17 |
| Perceptions |
Bowry et al. 2011; Khatib et al. 2014; Rashtid et al. 2014; AlGhurair et al. 2012; McKenzie et al. 2015. |
|
Negative perception of medication common barrier reported in 52% of studies, 73% of which found statistical significance.8 30% of self-reported studies looking at patient factors found patient perception of medications as a barrier.14 Pooled: in 10 self-reported studies, perceptions about consequences were reported as a barrier in 19% of surveys.15 Across 17 qualitative studies, found that patients with either no/reduced symptoms or those with very severe symptoms less likely to adhere as they believe they are not ill or that it is futile as their disease has already progressed too far.6 Suggests patient perception may be a strong barrier to adherence though gives no quantitative summary.21 |
| Social |
| SES |
AlGhurair et al. 2012; Mann et al. 2010; Alsabbagh et al. 2014; Lemstra et al. 2012; McKenzie et al. 2015; Lemstra and Alsabbagh 2014. |
|
In 22% of self-reported studies socioeconomic factors were cited as reducing adherence.6 Overall found that those with a higher income more likely to adhere,17 though inconsistent at study level—55% found this effect while 44% found no difference between low and high income groups.17 Of 32 studies 17 found higher income associated with higher adherence, 14 were non-significant, while 1 found lower adherence.19 In 11 studies, odds of adhering improve with higher income.20 Lower income (concession card holders in Australia healthcare system) found to have higher adherence. May be confounded (co-payments from concession card may improve adherence).21 Pooled analysis across nine studies found overall lower adherence with lower income status.10 |
