Dataset Information

Prevalence and predictors of medication non-adherence among people living with multimorbidity: a systematic review and meta-analysis.

ABSTRACT:

Objectives

This systematic review aimed to describe medication non-adherence among people living with multimorbidity according to the current literature, and synthesise predictors of non-adherence in this population.

Methods

A systematic review was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses. PubMed, EMBASE, CINAHL and PsycINFO were searched for relevant articles published in English language between January 2009 and April 2019. Quantitative studies reporting medication non-adherence and/or predictors of non-adherence among people with two or more chronic conditions were included in the review. A meta-analysis was conducted with a subgroup of studies that used an inclusive definition of multimorbidity to recruit participants, rather than seeking people with specific conditions. Remaining studies reporting prevalence and predictors of non-adherence were narratively synthesised.

Results

The database search produced 10 998 records and a further 75 were identified through other sources. Following full-text screening, 178 studies were included in the review. The range of reported non-adherence differed by measurement method, at 76.5% for self-report, 69.4% for pharmacy data, and 44.1% for electronic monitoring. A meta-analysis was conducted with eight studies (n=8949) that used an inclusive definition of multimorbidity to recruit participants. The pooled prevalence of non-adherence was 42.6% (95% CI: 34.0 - 51.3%, k=8, I ²=97%, p<0.01). The overall range of non-adherence was 7.0%-83.5%. Frequently reported correlates of non-adherence included previous non-adherence and treatment-related beliefs.

Conclusions

The review identified a heterogeneous literature in terms of conditions studied, and definitions and measures of non-adherence used. Results suggest that future attempts to improve adherence among people with multimorbidity should determine for which conditions individuals require most support. The variable levels of medication non-adherence highlight the need for more attention to be paid by healthcare providers to the impact of multimorbidity on chronic disease self-management.

Prospero registration number

CRD42019133849.

SUBMITTER: Foley L

PROVIDER: S-EPMC8413882 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundEpilepsy is the common neurological disorder in the world, affecting approximately 50 million people. Anti-epileptic medication non-adherence can be a reason for long term hospitalization, repeated emergency seizure attacks, increased health care cost and frequent absence of work due to poor seizure control. Existed studies of anti-epileptic medication non-adherence in Ethiopia have reported great discrepant and inconsistent results which calls a growing demand of systematic review and meta-analysis. Therefore, this review aimed to show the pooled prevalence of anti-epileptic medication non-adherence among people with epilepsy attending outpatient department.MethodsLiteratures were searched from the PubMed/Medline, Science Direct, PsycINFO, Hinnari and Google Scholar for grey literatures. The data were extracted using a prepared data extraction Microsoft Excel format. The data were analyzed using STATA- version 14 (software). The I2 test was used to check the heterogeneity between primary studies with a corresponding 95% confidence interval.ResultsA total of fourteen primary studies of anti-epileptic medication non-adherence were included in the review showing the pooled prevalence of anti-epileptic medication non-adherence to be 39.77 (95% CI: 32.44, 47.10). The highest prevalence [44.13 95% CI: (29.92, 58.34)] was observed among studies used both self-report and medical record review together, and studies used only self-report to screen medication none adherence had the lowest prevalence [37.95% (24.50, 51.41)]. Presence of co-morbid illness [2.27 (95%CI: 1.01, 5.12)], medication side effects [1.84(95% CI: 1.43, 2.38)], substance use or drug abuse [2.01(95% CI: 1.27, 3.20)] had statistically significant association with anti-epileptic medication non-adherence.ConclusionIn this review, we found that there is a high burden of anti-epileptic medication non-adherence among people with epilepsy in Ethiopia. This demonstrates a need for clinicians to give more attention for the monitoring and evaluation of anti-epileptic medication adherence in the health care service. We also highly recommended for the adoption of a standardized and contextualized adherence screening tools.Trial registrationPROSPERO registration number- [CRD42019137631].

Project description:BackgroundSelf-medication of medicines is a global issue particularly among those with good access and familiarity with medications such as university students. It has a significant impact on drug resistance and medication-related complications. There are limited and inconsistent studies on self-medication practices in Ethiopia. The aim of this systematic review and meta-analysis was to estimate the pooled prevalence of self-medication and its predictors among university students in Ethiopia.MethodsA systematic review and meta-analysis was conducted to assess the prevalence and predictors of self-medication among university students in Ethiopia. Published articles from various electronic databases such as Medline, Hinari, Pub Med, Cochrane library, and the Web of Science were accessed. In addition, a manual search was performed including Google Scholar. Searching of articles were searched from January 1st to February 1, 2021. All observational studies conducted among university students in English language were included in the review. Two reviewers independently assessed articles before inclusion in the final review using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) instrument for critical appraisal. The I2 test was used to assess heterogeneity. Since the included studies exhibited high heterogeneity, a random-effects model was used to estimate the pooled prevalence of self-medication.ResultsWe found of 812 published and unpublished studies in our search. Finally, 31 full-text studies were reviewed, and 13 studies fulfilled the inclusion criteria and were included in the final meta-analysis. A total of 5377 study respondents from 13 studies were included in the study. The results of our study revealed that the pooled prevalence of self-medication among university students was 49.41% (95% CI 38.67%, 60.13%). The included studies had a sample size ranging from 250 to 792 with the lowest prevalence (19.87%) of self-medication from the University of Gondar, whereas the highest prevalence (77.01%) was recorded in a study conducted at Arsi University. From the pooled estimation, there was a significant association between self-medication and income (OR = 0.67: 95% CI 0.55-0.80). However, the association between self-medication and year of study and sex of participants was insignificant.ConclusionThe pooled prevalence of self-medication among Ethiopian university students was relatively high compared to the current global health problem with an increase in anti-microbial resistance. Health professionals and concerned bodies should pay attention to raising awareness regarding the consequences of using medications without prescription.

Project description:OBJECTIVE:To determine the economic impact of medication non-adherence across multiple disease groups. DESIGN:Systematic review. EVIDENCE REVIEW:A comprehensive literature search was conducted in PubMed and Scopus in September 2017. Studies quantifying the cost of medication non-adherence in relation to economic impact were included. Relevant information was extracted and quality assessed using the Drummond checklist. RESULTS:Seventy-nine individual studies assessing the cost of medication non-adherence across 14 disease groups were included. Wide-scoping cost variations were reported, with lower levels of adherence generally associated with higher total costs. The annual adjusted disease-specific economic cost of non-adherence per person ranged from $949 to $44?190 (in 2015 US$). Costs attributed to 'all causes' non-adherence ranged from $5271 to $52?341. Medication possession ratio was the metric most used to calculate patient adherence, with varying cut-off points defining non-adherence. The main indicators used to measure the cost of non-adherence were total cost or total healthcare cost (83% of studies), pharmacy costs (70%), inpatient costs (46%), outpatient costs (50%), emergency department visit costs (27%), medical costs (29%) and hospitalisation costs (18%). Drummond quality assessment yielded 10 studies of high quality with all studies performing partial economic evaluations to varying extents. CONCLUSION:Medication non-adherence places a significant cost burden on healthcare systems. Current research assessing the economic impact of medication non-adherence is limited and of varying quality, failing to provide adaptable data to influence health policy. The correlation between increased non-adherence and higher disease prevalence should be used to inform policymakers to help circumvent avoidable costs to the healthcare system. Differences in methods make the comparison among studies challenging and an accurate estimation of true magnitude of the cost impossible. Standardisation of the metric measures used to estimate medication non-adherence and development of a streamlined approach to quantify costs is required. PROSPERO REGISTRATION NUMBER:CRD42015027338.

Project description:BACKGROUND:Electronic health (eHealth) is increasingly used for self-management and service delivery of HIV-related diseases. With the publication of studies increasingly focusing on antiretroviral therapy (ART) adherence, this makes it possible to quantitatively and systematically assess the effectiveness and feasibility of eHealth interventions. OBJECTIVE:The purpose of this review was to explore the effectiveness of eHealth interventions on improving ART adherence in people living with HIV. The effects of different intervention characteristics, participant characteristics, and study characteristics were also assessed. METHODS:We systematically searched MEDLINE (via PubMed), EMBASE, the Cochrane Central Register of Controlled Trials, and 3 conference abstract databases using search terms related to HIV, ART, adherence, and eHealth interventions. We independently screened the studies, extracted the data, and assessed the study quality and then compared the information in pairs. Articles published in English that used randomized controlled trials to assess eHealth interventions to improve ART adherence of people living with HIV were identified. We extracted the data including study characteristics, participant characteristics, intervention characteristics, and outcome measures. The Cochrane risk-of-bias tool was used to assess the risk of bias and study overall quality. Odds ratios, Cohen d, and their 95% CIs were estimated using random-effects models. We also performed multiple subgroup analyses and sensitivity analyses to define any sources of heterogeneity. RESULTS:Among 3941 articles identified, a total of 19 studies (including 21 trials) met the inclusion criteria. We found 8 trials from high-income countries and 13 trials from low- and middle-income countries. Furthermore, at baseline, the health status of participants in 14 trials was healthy. Of the trials included, 7 of 21 used personality content, 12 of 21 used a 2-way communication strategy, and 7 of 21 used medical content. In the pooled analysis of 3937 participants (mean age: 35 years; 47.16%, 1857/3937 females), eHealth interventions significantly improved the ART adherence of people living with HIV (pooled Cohen d=0.25; 95% CI 0.05 to 0.46; P=.01). The interventions were also correlated with improved biochemical outcomes reported by 11 trials (pooled Cohen d=0.25; 95% CI 0.11 to 0.38; P<.001). The effect was sensitive to sample size (Q=5.56; P=.02) and study duration (Q=8.89; P=.003), but it could not be explained by other moderators. The primary meta-analysis result was stable in the 3 sensitivity analyses. CONCLUSIONS:Some of the eHealth interventions may be used as an effective method to increase the ART adherence of people living with HIV. Considering that most of the trials included a small sample size and were conducted for a short duration, these results should be interpreted with caution. Future studies need to determine the features of eHealth interventions to better improve ART adherence along with long-term effectiveness of interventions, effectiveness of real-time adherence monitoring, enhancement of study design, and influences on biochemical outcomes.