Measuring Adherence to Multiple Medications Using Guideline-Directed Medical Therapy as a Model

以指南指导的药物治疗为模型,衡量多种药物的依从性

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Abstract

BACKGROUND: There is no gold standard for measuring adherence to a complex medication regimen. Heart failure is a chronic disease state that requires multiple medications for optimal control, known as guideline-directed-medical therapy (GDMT), and can be used a model to explore approaches to assessing multi-medication adherence. We aimed to compare seven proportion of days covered (PDC) measures for assessing adherence to multiple GDMT medications and to evaluate their association with clinical outcomes. METHODS: We conducted a large, single center, retrospective cohort study of 34,603 patients with heart failure who filled a GDMT prescription between April 2021 and July 2022. The primary outcomes were the seven PDC-based adherence measures derived from electronic health record and pharmacy data. PDC was defined as the proportion of days in which patients had possession of GDMT medications. Our secondary outcome was the combined clinical outcome of ED visits, hospitalizations, and death. RESULTS: The seven measures provided a wide range of measured PDC adherence. Using the strictest measure, 'each' (>= 80% of days with each drug available) 54% of patients were considered adherent, compared with 73% measured adherence for the least restrictive measure, 'at least one'. Variability increased with increasing number of medications across all non-average based measures. For example, using the 'all' measure (a more restrictive PDC measure) adherence ranged from 0.53 to 0.41 with increasing number of GDMT prescriptions. Higher PDC for each of the seven measures was associated with increased number of ED, visits, hospitalizations, and death. There was no association with the combined outcome in patients with heart failure with reduced ejection fraction. CONCLUSIONS AND RELEVANCE: There was a wide variability in adherence measures for assessing adherence to GDMT depending on the measure used. This variability has significant implications for the policy, clinical, and intervention context to which the measure is applied.

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