Identifying observable medication use time in administrative databases: a tutorial using nursing home residents
Year: 2025
Type: article
Study design: Observational Study
Abstract: Nursing home (NH) residents are an important population for pharmacoepidemiologic research due to their prevalence of multimorbidity and polypharmacy. Medicare claims are commonly used to study medication use in this population, but medications dispensed during hospitalizations or post-acute care are unobservable due to bundled payment structures. We developed algorithms to identify NH days when medication dispensings can be observed in claims. Using a cohort of NH residents in the United States from 2013 to 2020, we linked Medicare fee-for-service (FFS) claims with Minimum Data Set clinical assessments. NH days were classified as "observable medication use time" if residents were enrolled in Medicare parts A, B, and D were not receiving post-acute care and were not hospitalized. Among 12.3 million NH residents and 2.7 billion NH days, 1.1 billion days (72.4% of Medicare-enrolled days and 39.6% of all NH days) were identified as observable medication use time. Within the first 100 days of NH admission, 27.3% of days were medication-observable, increasing to 89.4% after 100 days. On average, we identified 68% more person-time, and 51% more residents, compared to standard 100-day definitions for "long-stay" NH residents. Our algorithms enhance researchers' ability to measure medication exposure time, improving the validity of pharmacoepidemiologic studies.
Source: American Journal of Epidemiology
DOI: 10.1093/aje/kwaf227
Authors: Daniel A Harris, Adam D’Amico, Hemalkumar B Mehta, Lori A Daiello, Sarah D Berry, Charles E Leonard, Yu-Chia Hsu, Douglas Kiel, Kaleen N Hayes, Melissa Riester, Jimmie E Roberts, Laura Reich, Peyton Free, Andrew R Zullo
Language: English
Subfield: Geriatrics and Gerontology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,856
OpenAlex ID: W4415005126
