Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
J Am Med Dir Assoc. 2023 Mar;24(3):277-283. doi: 10.1016/j.jamda.2022.01.062. Epub 2022 Feb 20.
Develop an approach for identifying Medicare beneficiaries residing in US assisted living (AL) communities in calendar year 2018.
We used the following data sources: national directory of licensed ALs, file of US addresses and their associated 9-digit ZIP codes (ZIP+4), Medicare Enrollment Database (EDB), Master Beneficiary Summary File (MBSF), and the Minimum Data Set (MDS).
A total of 412,723 Medicare beneficiaries who lived in ZIP+4 codes associated with an AL were identified as residents. Approximately 28% of the 16,682 ALs in which these beneficiaries resided were smaller communities (<25 beds).
For each AL, we identified ZIP+4 codes associated with its address. Using this ZIP+4 file, we searched through the Medicare EDB to identify beneficiaries who lived in each ZIP+4 code. The MBSF and MDS were used to exclude beneficiaries who died before 2018 and those whose AL and nursing home stays overlapped. We identified 3 cohorts of Medicare beneficiaries: (1) residents of a specific AL (one AL address per ZIP+4), (2) most likely AL residents, and (3) not likely AL residents. Comparisons across these cohorts were used to examine construct validity of our approach. Additional comparisons were made to AL residents based on the National Survey of Long-Term Care Providers (NSLTCP) and to fee-for-service (FFS) Medicare community-dwelling and long-stay nursing home residents.
The cohorts of beneficiaries identified as AL residents exhibited good construct validity. AL residents also showed similarity in demographic characteristics to the 2018 sample from the NSLTCP, and as expected were different from FFS community and nursing home beneficiaries.
We developed a methodology for identifying Medicare beneficiaries who reside in ALs. As this residential setting continues to grow, future studies will need effective approaches for identifying AL residents in order to evaluate the quality of care they receive.
制定一种方法，以识别 2018 年居住在美国辅助生活（AL）社区的医疗保险受益人。
我们使用了以下数据源：国家许可的 AL 目录、美国地址及其相关的 9 位邮政编码（ZIP+4）文件、医疗保险登记数据库（EDB）、主受益人摘要文件（MBSF）和最小数据集（MDS）。
确定居住在与 AL 相关的 ZIP+4 代码中的 412,723 名医疗保险受益人作为居民。这些受益人居住的 16,682 个 AL 中，约有 28%是较小的社区（<25 张床）。
对于每个 AL，我们确定与其地址相关的 ZIP+4 代码。使用此 ZIP+4 文件，我们在医疗保险 EDB 中搜索居住在每个 ZIP+4 代码中的受益人。MBSF 和 MDS 用于排除 2018 年前死亡的受益人以及 AL 和疗养院入住重叠的受益人。我们确定了 3 组医疗保险受益人：（1）特定 AL 的居民（每个 ZIP+4 有一个 AL 地址），（2）最有可能的 AL 居民，和（3）不太可能的 AL 居民。对这些队列进行比较，以检验我们方法的构建效度。还与基于全国长期护理提供者调查（NSLTCP）的 AL 居民以及按服务收费（FFS）医疗保险社区居住和长期护理院居民进行了比较。
被确定为 AL 居民的受益人群组表现出良好的构建效度。AL 居民在人口统计学特征上也与 NSLTCP 2018 年样本相似，并且与 FFS 社区和疗养院受益人预期不同。
我们开发了一种识别居住在 AL 中的医疗保险受益人的方法。随着这种居住环境的不断发展，未来的研究将需要有效的方法来识别 AL 居民，以便评估他们所接受的护理质量。
