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Comparison of Interventions to Improve Long-Term Medication Adherence Across Different Clinical Conditions: A Systematic Review With Network Meta-Analysis.

ABSTRACT: Background: Medication non-adherence has a dynamic, temporal and multifactorial nature with a significant impact on economic and clinical outcomes. Interventions to improve adherence are complex and require adaptation to patients' needs, which may include patient's medical conditions. The aim of this study was to assess the comparative effectiveness of medication adherence interventions per type of clinical condition on adult patients. Methods: A systematic review with network meta-analysis was performed (PROSPERO registration number of CRD42018054598). An initial Pubmed search was conducted to select meta-analyses reporting results of interventions aiming to improve medication adherence. Primary studies were selected and those reporting results with a long-term follow up (?10 months) on adult patients were included for data extraction. Study characteristics, description of interventions and adherence outcomes were extracted. Adherence interventions were classified in four groups: educational, attitudinal, technical, and rewards. Clinical conditions were classified in four groups: circulatory system and metabolic diseases, infectious diseases, musculoskeletal diseases, and mental, behavioral or neurodevelopmental disorders. Network meta-analyses with effect sizes expressed as odds ratio (OR) with a 95% credibility interval (CrI) were built. Ranking probabilities for each measure of adherence were calculated by using surface under the cumulative ranking analysis (SUCRA). Results: A total of 61 meta-analysis and 149 primary studies were included in the qualitative synthesis and 80 primary studies in the quantitative analysis. The most effective interventions were: educational + technical 79.6% [OR: 0.44 (CrI: 0.26, 0.73)] and 73.3% [OR: 0.56 (0.36, 0.84)] in circulatory system and metabolic diseases and infectious diseases respectively. Attitudinal intervention had the greatest probability for musculoskeletal diseases of 92.3% in SUCRA [OR: 0.30 (0.10, 0.86)]. Finally, educational + attitudinal interventions had the greatest effect (SUCRA 73.8%) for mental, behavioral or neurodevelopmental disorders, although this was not significant according to consistency analysis. Conclusion: Effectiveness of interventions seems to be related to the clinical condition. Educational and technical interventions resulted in a major effect on long-term management of medication adherence in patients with infectious diseases (HIV) and circulatory system and metabolic diseases whereas attitudinal components presented a higher effect on musculoskeletal and mental, behavioral or neurodevelopmental disorders.

SUBMITTER: Torres-Robles A

PROVIDER: S-EPMC6311651 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Comparison of Interventions to Improve Long-Term Medication Adherence Across Different Clinical Conditions: A Systematic Review With Network Meta-Analysis.

Torres-Robles Andrea A Wiecek Elyssa E Tonin Fernanda S FS Benrimoj Shalom I SI Fernandez-Llimos Fernando F Garcia-Cardenas Victoria V

Frontiers in pharmacology 20181224

<b>Background:</b> Medication non-adherence has a dynamic, temporal and multifactorial nature with a significant impact on economic and clinical outcomes. Interventions to improve adherence are complex and require adaptation to patients' needs, which may include patient's medical conditions. The aim of this study was to assess the comparative effectiveness of medication adherence interventions per type of clinical condition on adult patients. <b>Methods:</b> A systematic review with network meta ...[more]

PMID: 30618748

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Project description:INTRODUCTION:Adherence-enhancing interventions have been assessed in the literature, however heterogeneity and conflicting findings have prohibited a consensus on the most effective approach to maintain adherence over time. With the ageing population and growth of chronic conditions, evaluation of sustainable strategies to improve and maintain medication adherence long term is paramount. We aimed to determine the comparative effectiveness of interventions for improving medication adherence over time among adults with any clinical condition. MATERIALS AND METHODS:Meta-analyses evaluating interventions to improve medication adherence were searched in PubMed in January 2019 and reviewed for primary studies. Experimental studies with a comparison group assessing an intervention to enhance medication adherence in adult patients with reported adherence outcomes were included. Two authors extracted data for study characteristics, interventions and adherence outcomes. Interventions were categorized into four groups or combinations: educational, attitudinal, technical and rewards. Four network meta-analyses were performed to compare interventions based on patient follow-up time. Medication adherence effect sizes were reported as odds ratios (OR) with a 95% credibility interval (CrI) and surface under the cumulative ranking curve (SUCRA) to allow ranking probabilities. Risk of bias was assessed as per Cochrane guidelines. RESULTS:Data was obtained from 69 meta-analyses with 468 primary studies being included in qualitative synthesis. The four networks compromised of 249 studies in total (0-3 month follow-up: 99 studies, 4-6 months: 104, 7-9 months: 18, ?10 months: 94). Interventions showing success in follow-ups of less than 10 months varied across time. Significant effects compared to standard of care (SOC) were found in technical (4-6 months: OR 0.34, 95% CrI 0.25-0.45) and attitudinal interventions (7-9 months: 0.37, 0.17-0.84). Multicomponent interventions demonstrated effectiveness compared to standard of care with an additive effect displayed, particularly in longer follow-ups (educational + attitudinal + technical interventions ?10 months: OR 0.49, 95% CrI 0.27-0.88). DISCUSSION:All interventions reviewed improved medication adherence compared to standard of care. Multicomponent interventions displayed the most promising results in maintenance of long-term medication adherence. Technical and reward components enhanced adherence on a short-term basis, while educational and attitudinal interventions evolved over time to be more effective in follow-ups greater than 7 months. Sustainability of adherence to medications over time is dependent upon multicomponent interventions including educational, attitudinal and technical aspects to modify and enhance patient medication-taking behavior. Future research should focus on the most cost-effective approaches able to be integrated into routine practice.

Project description:BackgroundLipid-lowering drugs are widely underused, despite strong evidence indicating they improve cardiovascular end points. Poor patient adherence to a medication regimen can affect the success of lipid-lowering treatment.ObjectivesTo assess the effects of interventions aimed at improving adherence to lipid-lowering drugs, focusing on measures of adherence and clinical outcomes.Search methodsWe searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, PsycINFO and CINAHL up to 3 February 2016, and clinical trials registers (ANZCTR and ClinicalTrials.gov) up to 27 July 2016. We applied no language restrictions.Selection criteriaWe evaluated randomised controlled trials of adherence-enhancing interventions for lipid-lowering medication in adults in an ambulatory setting with a variety of measurable outcomes, such as adherence to treatment and changes to serum lipid levels. Two teams of review authors independently selected the studies.Data collection and analysisThree review authors extracted and assessed data, following criteria outlined by the Cochrane Handbook for Systematic Reviews of Interventions. We assessed the quality of the evidence using GRADEPro.Main resultsFor this updated review, we added 24 new studies meeting the eligibility criteria to the 11 studies from prior updates. We have therefore included 35 studies, randomising 925,171 participants. Seven studies including 11,204 individuals compared adherence rates of those in an intensification of a patient care intervention (e.g. electronic reminders, pharmacist-led interventions, healthcare professional education of patients) versus usual care over the short term (six months or less), and were pooled in a meta-analysis. Participants in the intervention group had better adherence than those receiving usual care (odds ratio (OR) 1.93, 95% confidence interval (CI) 1.29 to 2.88; 7 studies; 11,204 participants; moderate-quality evidence). A separate analysis also showed improvements in long-term adherence rates (more than six months) using intensification of care (OR 2.87, 95% CI 1.91 to 4.29; 3 studies; 663 participants; high-quality evidence). Analyses of the effect on total cholesterol and LDL-cholesterol levels also showed a positive effect of intensified interventions over both short- and long-term follow-up. Over the short term, total cholesterol decreased by a mean of 17.15 mg/dL (95% CI 1.17 to 33.14; 4 studies; 430 participants; low-quality evidence) and LDL-cholesterol decreased by a mean of 19.51 mg/dL (95% CI 8.51 to 30.51; 3 studies; 333 participants; moderate-quality evidence). Over the long term (more than six months) total cholesterol decreased by a mean of 17.57 mg/dL (95% CI 14.95 to 20.19; 2 studies; 127 participants; high-quality evidence). Included studies did not report usable data for health outcome indications, adverse effects or costs/resource use, so we could not pool these outcomes. We assessed each included study for bias using methods described in the Cochrane Handbook for Systematic Reviews of Interventions. In general, the risk of bias assessment revealed a low risk of selection bias, attrition bias, and reporting bias. There was unclear risk of bias relating to blinding for most studies.Authors' conclusionsThe evidence in our review demonstrates that intensification of patient care interventions improves short- and long-term medication adherence, as well as total cholesterol and LDL-cholesterol levels. Healthcare systems which can implement team-based intensification of patient care interventions may be successful in improving patient adherence rates to lipid-lowering medicines.

Project description:BackgroundMedication nonadherence leads to suboptimal treatment outcomes, making it a major priority in health care. eHealth provides an opportunity to offer medication adherence interventions with minimal effort from health care providers whose time and resources are limited.ObjectiveThe aim of this systematic review is twofold: (1) to evaluate effectiveness of recently developed and tested interactive eHealth (including mHealth) interventions on medication adherence in adult patients using long-term medication and (2) to describe strategies among effective interventions.MethodsMEDLINE, EMBASE, Cochrane Library, PsycINFO, and Web of Science were systematically searched from January 2014 to July 2019 as well as reference lists and citations of included articles. Eligible studies fulfilled the following inclusion criteria: (1) randomized controlled trial with a usual care control group; (2) a total sample size of at least 50 adult patients using long-term medication; (3) applying an interactive eHealth intervention aimed at the patient or patient's caregiver; and (4) medication adherence as primary outcome. Methodologic quality was assessed using the Cochrane risk of bias tool. Selection and quality assessment of studies were performed by 2 researchers (BP and BvdB or JV) independently. A best evidence synthesis was performed according to the Cochrane Back Review Group.ResultsOf the 9047 records screened, 22 randomized clinical trials were included reporting on 29 interventions. Most (21/29, 72%) interventions specified using a (mobile) phone for calling, SMS text messaging, or mobile apps. A majority of all interactive interventions (17/29) had a statistically significant effect on medication adherence (P<.05). Of these interventions, 9 had at least a small effect size (Cohen d ≥ 0.2) and 3 showed strong odds for becoming adherent in the intervention group (odds ratio > 2.0). Our best evidence synthesis provided strong evidence for a positive effect of interventions using SMS text messages or interactive voice response, mobile app, and calls as mode of providing adherence tele-feedback. Intervention strategies "to teach medication management skills," "to improve health care quality by coordinating medication adherence care between professionals," and "to facilitate communication or decision making between patients and health care providers" also showed strong evidence for a positive effect.ConclusionsOverall, this review supports the hypothesis that interactive eHealth interventions can be effective in improving medication adherence. Intervention strategies that improve patients' treatment involvement and their medication management skills are most promising and should be considered for implementation in practice.

Project description:BACKGROUND:The National Health Service (NHS) England spent £15.5 billion on medication in 2015. More than a third of patients affected by at least one long-term condition do not adhere to their drug regime. Many interventions have been trialed to improve medication adherence. One promising innovation is the electronic personal health record. OBJECTIVE:This systematic literature review aims to identify the important design features of personal health records to improve medication adherence for patients with long-term conditions. METHODS:This protocol follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P 2015) statement. The following databases will be searched for relevant articles: PubMed, Science Direct, BioMed Central, Cumulative Index to Nursing and Allied Health Literature, Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials. Studies published in the last fifteen years, in English, will be included if the participants are adults who were treated outside the hospital, have the ability to self-administer their medication, and have at least one long-term condition. The review will exclude commercial or political sources and papers without references. Papers that research pediatrics, pregnant, or terminally ill patients will also be excluded, since their medication management is typically more complex. RESULTS:One reviewer will screen the included studies, extract the relevant data, and assess the quality of evidence utilizing the Grading of Recommendations Assessment, Development, and Evaluation system and the risk of bias using the Cochrane RevMan tool. The second reviewer will assess the quality of 25% of the included studies to assess interrater agreement. Any disagreement will be solved by a third reviewer. Only studies of high and moderate quality will be included for narrative synthesis. CONCLUSIONS:NHS policy assumes that increasing usage of personal health records by citizens will reduce demand on health care services. There is limited evidence, however, that the use of health apps can improve patient outcomes, and, to our knowledge, this is the first systematic literature review aiming to identify important design features of the personal health record which may improve medication adherence in the adult population with long-term conditions. TRIAL REGISTRATION:PROSPERO CRD42017060542; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=60542 (Archived by WebCite at http://www.webcitation.org/6zeuWXxVh). REGISTERED REPORT IDENTIFIER:RR1-10.2196/9778.

Project description:OBJECTIVES:This systematic literature review aims to identify important design features of the electronic personal health record (PHR) that may improve medication adherence in the adult population with long-term conditions. DATA SOURCES:PubMed (including MEDLINE), CINAHL, Science Direct (including EMBASE), BioMed Central, ACM digital, Emerald Insight, Google Scholar and Research Gate. METHODS:Studies that were published between 1 January 2002 and 31 May 2018 in English were included if the participants were adults, with at least one long-term condition, were able to self-administer their medication and were treated in primary care settings. The quality of evidence was assessed with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system and the risk of bias was appraised using the Cochrane risk of bias tool. RESULTS:From a total of 27 studies that matched the inclusion criteria, 12 were excluded due to low quality of evidence, 10 were rated moderate and 5 were rated high quality. All the included studies had low sample size and limited follow-up duration. Thirteen of the included studies found that the use of a PHR has increased medication adherence. The identified design features are reminders, education, personalisation and tailoring, feedback and alerts, gamification, medication management, medical appointment management, diary and self-monitoring, health condition management, set goals, patient's blog and tethered. It was impossible to draw conclusions as to which feature is important to what group of patients and why. The most frequently identified conditions were HIV and diabetes. This review did not identify any papers with negative results. It was not possible to numerically aggregate the PHR effect due to high heterogeneity of the medication adherence measurement, study type, participants and PHRs used. CONCLUSION:Although we found recurrent evidence that PHRs can improve medication adherence, there is little evidence to date to indicate which design features facilitate this process. PROSPERO REGISTRATION NUMBER:CRD42017060542.

Project description:BackgroundMedications for the prevention and treatment of cardiovascular disease save lives but adherence is often inadequate. The optimal role for physicians in improving adherence remains unclear.ObjectiveUsing existing evidence, we set the goal of evaluating the physician's role in improving medication adherence.DesignWe conducted systematic searches of English-language peer-reviewed publications in MEDLINE and EMBASE from 1966 through 12/31/2008.Subjects and interventionsWe selected randomized controlled trials of interventions to improve adherence to medications used for preventing or treating cardiovascular disease or diabetes.Main measuresArticles were classified as either (1) physician "active"-a physician participated in designing or implementing the intervention; (2) physician "passive"-physicians treating intervention group patients received patient adherence information while physicians treating controls did not; or (3) physicians noninvolved. We also identified studies in which healthcare professionals helped deliver the intervention. We did a meta-analysis of the studies involving healthcare professionals to determine aggregate Cohen's D effect sizes (ES).Key resultsWe identified 6,550 articles; 168 were reviewed in full, 82 met inclusion criteria. The majority of all studies (88.9%) showed improved adherence. Physician noninvolved studies were more likely (35.0% of studies) to show a medium or large effect on adherence compared to physician-involved studies (31.3%). Among interventions requiring a healthcare professional, physician-noninvolved interventions were more effective (ES 0.47; 95% CI 0.38-0.56) than physician-involved interventions (ES 0.25; 95% CI 0.21-0.29; p < 0.001). Among physician-involved interventions, physician-passive interventions were marginally more effective (ES 0.29; 95% CI 0.22-0.36) than physician-active interventions (ES 0.23; 95% CI 0.17-0.28; p = 0.2).ConclusionsAdherence interventions utilizing non-physician healthcare professionals are effective in improving cardiovascular medication adherence, but further study is needed to identify the optimal role for physicians.

Project description:Background/objectiveAs pharmacists work to ensure reimbursement for chronic disease management services on the national level, evidence of their impact on important health metrics, such as medication adherence, is needed. However, summative evidence is lacking on the effectiveness of pharmacists to improve medication adherence in older adults. The objective was to assess the effectiveness of pharmacist-led interventions on medication adherence in older adults (65+ years).Design/setting/participantsUsing a systematic review and meta-analytic approach, a comprehensive search of publications in PubMed, Scopus, CINAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Google Scholar was conducted through April 2, 2020 for randomized clinical trials of pharmacist-led interventions to improve medication adherence in older adults. A standardized mean difference effect size (Cohen's d) was calculated for medication adherence in each study. Study effect sizes were pooled using a random-effects model, with effect sizes weighted by inverse of its total variance.MeasurementsMedication adherence using any method of measurement.ResultsAmong 40 unique randomized trials of pharmacist-led interventions with data from 8822 unique patients (mean age, range: 65-85 years), the mean effect size was 0.57 (k = 40; 95% Confidence Interval [CI]: 0.38-0.76). When two outlier studies were excluded from the analysis, the mean effect size reduced to 0.41 (k = 38; 95% CI: 0.27-0.54). A sensitivity analysis of medication adherence outcome by time point resulted in a mean effect size of 0.64 at 3 months (k = 12; 95% CI: 0.32-0.97), 0.30 at 6 months (k = 13; 95% CI: 0.11-0.48), 0.22 at 12 months (k = 12; 95% CI: 0.08-0.37), and 0.36 for outcome time points beyond 12 months (k = 5; 95% CI: 0.02-0.70).ConclusionThis meta-analysis found a significant improvement in medication adherence among older adults receiving pharmacist-led interventions. Implementation of pharmacist-led interventions supported by Medicare reimbursement could ensure older adults' access to effective medication adherence support.

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Comparison of Interventions to Improve Long-Term Medication Adherence Across Different Clinical Conditions: A Systematic Review With Network Meta-Analysis.

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Comparison of Interventions to Improve Long-Term Medication Adherence Across Different Clinical Conditions: A Systematic Review With Network Meta-Analysis.

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