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

TL;DR

This study compares how well dementia detection algorithms work in two Medicare populations, finding that they perform similarly in most cases but with some differences in accuracy.

Contribution

The study evaluates dementia algorithms in Medicare Advantage for the first time, revealing performance differences in sensitivity and predictive value.

Findings

Both algorithms showed high specificity and negative predictive value in Medicare Advantage and Fee-for-Service populations.

Bynum algorithm had lower sensitivity in Medicare Advantage during Round 9 compared to Fee-for-Service.

CCW algorithm showed significantly lower sensitivity in Medicare Advantage for Rounds 9 and 11.

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.