{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T02:07:39Z","timestamp":1787018859931,"version":"build-2736575974"},"reference-count":28,"publisher":"SAGE Publications","issue":"7","license":[{"start":{"date-parts":[[2023,3,10]],"date-time":"2023-03-10T00:00:00Z","timestamp":1678406400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100000016","name":"U.S. Department of Health and Human Services","doi-asserted-by":"publisher","award":["HHSP233201500038I"],"award-info":[{"award-number":["HHSP233201500038I"]}],"id":[{"id":"10.13039\/100000016","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Appl Gerontol"],"published-print":{"date-parts":[[2023,7]]},"abstract":"<jats:p>Functional impairment predicts mortality and health care utilization. However, validated measures of functional impairment are not routinely collected during clinical encounters and are impractical to use for large-scale risk-adjustment or targeting interventions. This study\u2019s purpose was to develop and validate claims-based algorithms to predict functional impairment using Medicare Fee-for-Service (FFS) 2014\u20132017 claims data linked with post-acute care (PAC) assessment data and weighted to better represent the overall Medicare FFS population. Using supervised machine learning, predictors were identified that best predicted two functional impairment outcomes measured in PAC data\u2014any memory limitation and a count of 0\u20136 activity\/mobility limitations. The memory limitation algorithm had moderately high sensitivity and specificity. The activity\/mobility limitations algorithm performed well in identifying beneficiaries with five or more limitations, but overall accuracy was poor. This dataset shows promise for use in PAC populations, though generalizability to broader older adult populations remains a challenge.<\/jats:p>","DOI":"10.1177\/07334648231162613","type":"journal-article","created":{"date-parts":[[2023,3,11]],"date-time":"2023-03-11T01:05:41Z","timestamp":1678496741000},"page":"1651-1661","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Development and Validation of Algorithms to Predict Activity, Mobility, and Memory Limitations Using Medicare Claims and Post-Acute Care Assessments"],"prefix":"10.1177","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0196-9000","authenticated-orcid":false,"given":"Sara E.","family":"Heins","sequence":"first","affiliation":[{"name":"RAND Corporation, Pittsburgh, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Denis","family":"Agniel","sequence":"additional","affiliation":[{"name":"RAND Corporation, Santa Monica, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacob","family":"Mann","sequence":"additional","affiliation":[{"name":"Solutions By Design, Vienna, VA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melony E.","family":"Sorbero","sequence":"additional","affiliation":[{"name":"RAND Corporation, Pittsburgh, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2023,3,10]]},"reference":[{"key":"bibr1-07334648231162613","doi-asserted-by":"publisher","DOI":"10.1111\/1475-6773.12316"},{"key":"bibr2-07334648231162613","volume-title":"Minimum data set MDS 3.0","author":"Centers for Medicare &amp; 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