Economic impact of medication non-adherence by disease groups: a systematic review

Cutler, Rachelle Louise; Fernández-Llimós, Fernando; Frommer, Michael; Benrimoj, Charlie S; García-Cárdenas, Victoria

doi:10.1136/bmjopen-2017-016982

Cited by 583 publications

(461 citation statements)

References 86 publications

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“…A recent review on the economic burden of medication non-adherence cited the wide variability in adherence measurement and study methodologies as a barrier to meta-analysis. 114 This is evident in the current review. More concerted action is needed to establish and standardise methods of measuring adherence in older patients with multimorbidity, which are comparable across studies.…”

Section: Discussionsupporting

confidence: 56%

“…Despite a relatively large evidence base, meta‐analysis was only feasible for 3 of the specified health outcomes and included only a small number of studies. A recent review on the economic burden of medication non‐adherence cited the wide variability in adherence measurement and study methodologies as a barrier to meta‐analysis . This is evident in the current review.…”

Section: Discussionmentioning

confidence: 86%

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The association between medication non‐adherence and adverse health outcomes in ageing populations: A systematic review and meta‐analysis

Walsh

Cahir

Tecklenborg

et al. 2019

Brit J Clinical Pharma

123

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Aims The aim of this systematic review and meta‐analysis was to synthesise the evidence relating to medication non‐adherence and its association with health outcomes in people aged ≥50 years. Methods Seven databases were searched up to February 2019 for observational studies that measured medication (non‐)adherence as a predictor of the following health outcomes in adults aged ≥50 years: healthcare utilisation (hospitalisation, emergency department visits, outpatient visits and general practitioner visits), mortality, adverse clinical events and quality of life. Screening and quality assessment using validated criteria were completed by 2 reviewers independently. Random effects models were used to generate pooled estimates of association using adjusted study results. The full methodological approach was published on PROSPERO (ID: CRD42017077264). Results Sixty‐six studies were identified for qualitative synthesis, with 11 of these studies eligible for meta‐analyses. A meta‐analysis including 3 studies measuring medication non‐adherence in adults aged ≥55 years showed a significant association with all‐cause hospitalisation (adjusted odds ratio 1.17, 95% confidence interval [CI] 1.12, 1.21). A meta‐analysis including 2 studies showed that medication non‐adherence was not significantly associated with an emergency department visit (adjusted odds ratio 1.05, 95% CI 0.90, 1.22). Good adherence was associated with a 21% reduction in long‐term mortality risk in comparison to medication non‐adherence (adjusted hazard ratio 0.79, 95% CI 0.63, 0.98). Conclusion Medication non‐adherence may be significantly associated with all‐cause hospitalisation and mortality in older people. Medication adherence should be monitored and addressed in this cohort to minimise hospitalisation, improve clinical outcomes and reduce healthcare costs.

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Section: Discussionsupporting

confidence: 56%

Section: Discussionmentioning

confidence: 86%

The association between medication non‐adherence and adverse health outcomes in ageing populations: A systematic review and meta‐analysis

Walsh

Cahir

Tecklenborg

et al. 2019

Brit J Clinical Pharma

123

View full text Add to dashboard Cite

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“…Medicine beliefs have been found to be strongly correlated with medicine adherence . Medicine non‐adherence is a global problem encountered daily by healthcare professionals that contributes to progression of diseases and increases in health service cost . Patients’ SRH and medicine beliefs both reflect personal evaluations or assessments of current health conditions or outcomes .…”

Section: Introductionmentioning

confidence: 99%

Self-rated health and medicine beliefs among older hospital outpatients in Hong Kong

Wan

Ball

Jackson

et al. 2019

International Journal of Pharmacy Practice

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Objectives (1) To identify any demographic characteristics, which predict medicines adherence by reporting Necessity‐Concern Differential (NCD) and Self‐Reported Health (SRH) scores among Hong Kong hospital outpatients. (ii) To investigate any association between SRH and NCD in this cultural group. Methods A total of 709 outpatients completed a questionnaire consisting demographic information, SRH and Belief about Medicines Questionnaire. Findings were analysed statistically. Key findings Descriptive statistics suggested that older participants (mean age > 64 years) tended to report low SRH, but high NCD compared to younger respondents (mean age < 53 years). Males were more likely to return high SRH and NCD scores than females (56.9 versus 42.2% and 74.8 versus 64.6%, respectively). Chi‐squared tests demonstrated that socio‐economic status was not significantly associated with SRH and NCD reporting (P > 0.05). Logistic regressions indicated gender and age groups (young‐old and old‐old) were significant predictors of SRH reporting (P < 0.001). Moreover, patients with high SRH were more likely to report high NCD than those with low SRH (P = 0.02; OR = 1.53; 95%CI 1.07–2.20). This indicates that regular administration of the SRH item followed by specific questioning could enhance early identification of potential medicine non‐believers and, subsequently, non‐adherent patients who may require urgent interventions or monitoring. Conclusions Demographic characteristics and significant association between SRH and NCD reporting support our claim that SRH opens new opportunities for prompt identification of potentially non‐adherent patients. However, further interviews to determine the cause(s) of non‐adherence are necessary to validate such findings.

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“…For example, using “big data” health care delivery partners may see that a patient lives in a lower income neighborhood. Using patient‐reported data, health care delivery partners could discover that the same patient is struggling with the cost of a particular medication and connect him or her with a copayment assistance program . Through that conversation health care delivery partners might also learn that the patient has difficulty interpreting pill bottle instructions for when and how to take their medication, thus health care delivery partners could connect them with more innovative, pictorial medication packaging.…”

Section: Discussionmentioning

confidence: 99%

Novel application of approaches to predicting medication adherence using medical claims data

Zullig

Jazowski

Wang

et al. 2019

Health Services Research

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Objective To compare predictive analytic approaches to characterize medication nonadherence and determine under which circumstances each method may be best applied. Data Sources/Study Setting Medicare Parts A, B, and D claims from 2007 to 2013. Study Design We evaluated three statistical techniques to predict statin adherence (proportion of days covered [PDC ≥ 80 percent]) in the year following discharge: standard logistic regression with backward selection of covariates, least absolute shrinkage and selection operator (LASSO), and random forest. We used the C‐index to assess model discrimination and decile plots comparing predicted values to observed event rates to evaluate model performance. Data Extraction We identified 11 969 beneficiaries with an acute myocardial infarction (MI)‐related admission from 2007 to 2012, who filled a statin prescription at, or shortly after, discharge. Principal Findings In all models, prior statin use was the most important predictor of future adherence (OR = 3.65, 95% CI: 3.34‐3.98; OR = 3.55). Although the LASSO regression model selected nearly 90 percent of all candidate predictors, all three analytic approaches had moderate discrimination (C‐index ranging from 0.664 to 0.673). Conclusions Although none of the models emerged as clearly superior, predictive analytics could proactively determine which patients are at risk of nonadherence, thus allowing for timely engagement in adherence‐improving interventions.

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Economic impact of medication non-adherence by disease groups: a systematic review

Cited by 583 publications

References 86 publications

The association between medication non‐adherence and adverse health outcomes in ageing populations: A systematic review and meta‐analysis

The association between medication non‐adherence and adverse health outcomes in ageing populations: A systematic review and meta‐analysis

Self-rated health and medicine beliefs among older hospital outpatients in Hong Kong

Novel application of approaches to predicting medication adherence using medical claims data

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