Abstract
Objectives
Develop an approach for identifying Medicare beneficiaries residing in US assisted
living (AL) communities in calendar year 2018.
Design
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).
Setting and Participants
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).
Methods
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.
Results
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.
Conclusion and Implications
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.
Keywords
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Article info
Publication history
Published online: February 20, 2022
Footnotes
This work was supported by the Agency for Healthcare Research and Quality, United States grant number R01HS026893.
The authors declare no conflicts of interest.
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