Identifying observable medication use time in administrative databases: a tutorial using nursing home residents

利用养老院居民数据,在行政数据库中识别可观察的用药时间:一个教程

阅读:1

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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。