4.2 Article Proceedings Paper

Primary Care Physician Characteristics Associated with Prescribing Potentially Inappropriate Medication for Elderly Patients: Medicare Part D Data

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AMER BOARD FAMILY MEDICINE
DOI: 10.3122/jabfm.2020.04.190310

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Adverse Drug Event; Geriatrics; Internal Medicine; Medicare Part D; Multivariate Analysis; Potentially Inappropriate Medications; Primary Care Physicians; Primary Health Care; Retrospective Studies

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Background: Despite the high risk of adverse drug events associated with potentially inappropriate medications (PIMs), primary care physicians (PCPs) continue to prescribe them for the elderly. The objective of this study was to explore PIM prescribing behavior in relation to characteristics among PCPs practicing in the United States. Methods: We conducted a retrospective cohort study of PCPs in the 2013 to 2015 Medicare Part D Public Use File. We obtained physician characteristics from the 2015 American Medical Association (AMA) Masterfile. For each PCP, we calculated the ratio of primary care-relevant PIM claims to all drug claims (PIM rate) based on Beers Criteria. We used a multivariate regression model to assess the associations between physician characteristics and PIM rate. Results: The study sample contained 111,461 PCPs who specialized in family medicine, internal medicine, general practice and geriatric medicine. Although the mean PIM rate was low at 4.9%, it varied widely across PCPs with the bottom quartile at 1.2% and the top quartile at 10.1%. PCPs in the top quartile were on average older, more likely to be male, have a DO degree, practice in the South, and have a smaller Medicare patient panel. A multivariate analysis confirmed that even after adjusting for patient panel characteristics, physician characteristics including gender, age, professional degree, specialty, practice location, practice size, and patient panel size were associated with PIM rate. Conclusion: Identifying PCPs with higher PIM rates can guide future interventions to increase safe prescribing for elderly populations.

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