An Analysis of Medication Adherence in a Large Outpatient Population During the COVID-19 Pandemic Using a Novel Value-Based Pharmacy System

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Background:Adherence to a medication regimen is defined as taking the medication as directed by the prescriber. Adherence is critical to achieve the desired therapeutic outcomes. Medication adherence has not been examined in large outpatient populations since the onset of the COVID-19 pandemic. A novel outpatient value-based pharmacy system (VPS) was used to collect adherence data from a large, outpatient population. The aim of this descriptive study was to analyze the reasons, medication classes, and diagnoses associated with nonadherence.

Materials and Methods:Telepharmacist-documented adherence data from a large (n = 6,479) outpatient population that received remote consultation during the COVID-19 pandemic (August 1, 2020–November 28, 2022) were considered for this study. The adherence data were compiled within the VPS.

Results:The overall rate of patients reporting at least one incident of nonadherence to their medication regimens was 21.5%. Medications used to treat hypertension, type 2 diabetes, and hyperlipidemia were least adhered to. Statins, beta-2 agonists, and corticosteroids were least adhered to. The most common reasons for nonadherence included knowledge gaps regarding therapy, forgetfulness, and side effects.

Discussion:This represents the first descriptive analyses of adherence metrics in a large outpatient population during the COVID-19 pandemic. Polypharmacy, prevalence of diagnosis, and medication side effect profile may have contributed to the results observed. This study demonstrates the ability of a VPS to document key data to better inform the health care team. Elucidating adherence metrics in such populations may allow pharmacists and prescribers to identify subpopulations that require further education and management.

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Pharmaceutical Sciences

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Telemedicine and e-Health

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Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.