ArticleJournal of general internal medicine2025
Approach to Estimating Adherence to Heart Failure Medications Using Linked Electronic Health Record and Pharmacy Data.
Article in Journal of general internal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Association Between Social Determinants of Health and Adherence to Antihypertensive Medications in US Patients With Uncontrolled, Treated Hypertension.Circulation. Population health and outcomes · 2026Trial
- Linking Dispense Data to Electronic Health Orders: Tutorial for Querying Commercial Pharmacy Databases to Support Systemwide Quality Improvement.Journal of medical Internet research · 2026Article
- Measuring Adherence to Multiple Medications Using Guideline-Directed Medical Therapy as a Model.medRxiv : the preprint server for health sciences · 2025Article
- Machine learning based prediction of medication adherence in heart failure using large electronic health record cohort with linkages to pharmacy-fill and neighborhood-level data.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Factors Associated with Medication Adherence and Glycemic Control among American Indian/Alaska Native Adults with Type 2 Diabetes Within a Commercial Health Care System: A System-Wide Cross-Sectional Study.Journal of racial and ethnic health disparities · 2025Article
- Lessons Learned from the Usability Assessment of an EHR-Based Tool to Support Adherence to Antihypertensive Medications.Applied clinical informatics · 2025Article
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Authors and funding
7 authors.
Funding
Abstract
backgroundMedication non-adherence, which is common in chronic diseases such as heart failure, is often estimated using proportion of days covered (PDC). PDC is typically calculated using medication fill information from pharmacy or insurance claims data, which lack information on when medications are prescribed. Many electronic health records (EHRs) have prescription and pharmacy fill data available, enabling enhanced PDC assessment that can be utilized in routine clinical care.
objectiveTo describe our approach to calculating PDC using linked EHR-pharmacy data and to compare to PDC calculated using pharmacy-only data for patients with heart failure.
methodsWe performed a retrospective cohort study of adult patients with heart failure who were prescribed guideline-directed medical therapy (GDMT) and seen in a large health system. Using linked EHR-pharmacy data, we estimated medication adherence by PDC as the percent of days in which a patient possessed GDMT based on medication pharmacy fills over the number of days the prescription order was active. We also calculated PDC using pharmacy-only data, calculated as medications possessed over days with continued medication fills. We compared these two approaches for days observed and PDC using a paired t-test.
resultsAmong 33,212 patients with heart failure who were prescribed GDMT, 2226 (6.7%) never filled their medications, making them unavailable in the assessment of PDC using pharmacy-only data (n = 30,995). Linked EHR-pharmacy data had slightly longer days observed for PDC assessment (164.7 vs. 163.4 days; p < 0.001) and lower PDC (78.5 vs. 90.6, p < 0.001) as compared to assessment using pharmacy-only data.
conclusionsLinked EHR-pharmacy data can be used to identify patients who never fill their prescriptions. Estimating adherence using linked EHR-pharmacy data resulted in a lower mean PDC as compared to estimates using pharmacy-only data.
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