Performance of Claims-based Dementia Algorithms in Medicare Fee-for-service and Medicare Advantage Populations

Topic: Risk, prevention and care in population studies

Abstract Claims-based dementia algorithms have not been evaluated in the Medicare Advantage (MA) population, a critical gap given the rapid growth of MA and concerns about data completeness. Using community-dwelling participants from the National Health and Aging Trends Study (NHATS) Round 7 (2017; n = 5,058), Round 9 (2019; n = 4,048), and Round 11 (2021-2022; n = 3,109), we validated the Bynum Standard and Chronic Condition Warehouse (CCW) dementia algorithms against NHATS classification for probable dementia. The prevalence of probable dementia was similar between MA (8.2%-9.1%) and FFS (8.1%-8.5%) across rounds. Overall, both algorithms had comparable performance in MA vs FFS populations, demonstrating high specificity (>97.9%) and negative predictive value [NPV] (>92.9%). The Bynum algorithm had similar sensitivity between MA and FFS in Round 7 (30.2% vs. 29.1%) and 11 (25.6% vs. 23.9%), but statistically significant and clinically meaningful lower sensitivity in MA for Round 9 (25.0% vs. 36.4%). However, positive predictive value [PPV] was similar between MA (62.7%-70.6%) and FFS (62.1%-70.4%) in all rounds. Comparatively, the CCW algorithm had statistically significant and clinically meaningful lower sensitivity in MA than FFS for Round 9 (30.8% vs. 46.9%) and 11 (35.0% vs. 49.3%), yet similar sensitivity for Round 7 (40.4% vs. 42.2%). The PPV in MA and FFS varied across rounds, from Round 7 (76.3% vs. 71.2%) to 11 (68.5% vs. 76.4%). Claims-based dementia algorithms have lower or comparable sensitivity in MA vs. FFS, with similarly moderate PPV and consistently high specificity and NPV. Researchers should consider these trade-offs when selecting algorithms for MA and FFS.

Key findings

• Overall, both algorithms had comparable performance in MA vs FFS populations, demonstrating high specificity (>97.9%) and negative predictive value [NPV] (>92.9%).
• The Bynum algorithm had similar sensitivity between MA and FFS in Round 7 (30.2% vs. 29.1%) and 11 (25.6% vs. 23.9%), but statistically significant and clinically meaningful lower sensitivity in MA for Round 9 (25.0% vs. 36.4%).
• Comparatively, the CCW algorithm had statistically significant and clinically meaningful lower sensitivity in MA than FFS for Round 9 (30.8% vs. 46.9%) and 11 (35.0% vs. 49.3%), yet similar sensitivity for Round 7 (40.4% vs. 42.2%).

Why it matters

This study tested two claims-based dementia algorithms against a gold-standard classification in Medicare Advantage and fee-for-service populations. It found the algorithms had high specificity but lower sensitivity in Medicare Advantage in some years, which matters for identifying dementia cases but does not address treating or curing the disease.

Study details

• Participants5,058
• Effect size8.2%; 9.1%; 8.1%
• Evidence strengthLow

Read the original

• DOI: 10.1093/geroni/igaf122.4238
• Original source →
• Free full text: Innovation in Aging →

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

@article{wu2025-56754501,
  author  = {Wu, You and Park, Chan Mi and Luo, Lan and Chen, Xiecheng and Kim, Eunji G and Shi, Sandra and Kim, Dae Hyun and McCarthy, Ellen P.},
  title   = {{Performance of Claims-based Dementia Algorithms in Medicare Fee-for-service and Medicare Advantage Populations}},
  journal = {Innovation in Aging},
  year    = {2025},
  doi     = {10.1093/geroni/igaf122.4238},
  url     = {https://doi.org/10.1093/geroni/igaf122.4238}
}

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