ArticleJournal of the American Geriatrics Society2022
Leveraging survey and claims data to identify high-need Medicare beneficiaries in the National Health and Aging Trends Study.
Article in Journal of the American Geriatrics Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Predicting Mortality and Costs After Emergency Department Visits by People With Dementia: Timing and Location Matter.Journal of the American Geriatrics Society · 2026Article
- Multimorbidity quantification from the perspective of precision management: challenges and strategies.Annals of medicine · 2025Review
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Authors and funding
3 authors.
Funding
Abstract
backgroundMultiple algorithms have been developed to identify and characterize the high-need (HN) Medicare population. However, they vary in components and yield different populations, and were developed for varying purposes. We compared the performance of existing survey and claims-based definitions in identifying HN beneficiaries and predicting poor outcomes among a community-dwelling population.
methodsA retrospective cohort study using Round 5 (2015) of the National Health and Aging Trends Study (NHATS) linked with Medicare claims. We applied HN definitions from previous studies to our cohort of community-dwelling, fee-for-service beneficiaries (n = 4201) using sampling weights to obtain nationally representative estimates. The Bélanger et al. (2019) definition defines HN as individuals with complex conditions, multi-morbidity, acute and post-acute healthcare utilization, dependency in activities of daily living, and frailty. The Hayes et al. (2016) definition defines HN as individuals with 3+ chronic conditions and a functional limitation. We applied each definition to survey and claims data. Outcomes were hospitalization or mortality in the subsequent year.
resultsThe proportion of NHATS respondents classified as HN varied greatly across definitions, ranging from 3.1% using the claims-based Hayes definition to 32.9% using the survey-based Bélanger definition. HN respondents had significantly higher mortality and hospitalization rates in 2016. Although all definitions had good specificity, none were able to predict outcomes in the following year with good accuracy.
conclusionsWhile mortality and hospitalization rates were significantly higher among respondents classified as HN, existing claims and survey-based HN definitions were not able to accurately predict future outcomes in a community-dwelling, nationally representative sample measured by the area under the curve.
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