The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
Identification of prevalent dementia in Medicare Advantage encounters, compared with rigorous cohort assessments.
СтатьяСравнительное исследованиеНазвание и аннотация: Перевод в очереди
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Chen Yi, Benloucif Slim, James Bryan D, Banerjee Mousumi, Grodstein Francine, Bynum Julie P W
Аннотация
BACKGROUND: Rapid growth in Medicare Advantage (MA) enrollment has spurred dementia research using diagnoses in MA encounter data. However, the validity of MA-encounter-based dementia diagnoses is uncertain.
METHODS: Using four cohort studies at the Rush Alzheimer's Disease Center linked to Medicare data from 2017-19, we validated prevalent dementia indicators in MA encounter data, based on the Bynum-Standard algorithm, against dementia status determined by rigorous cognitive assessment in the cohort studies. We replicated analyses among participants in Traditional Medicare (TM).
RESULTS: Of the 508 eligible MA enrollees, mean age was 82.8 (SD = 7.2) years, 81% were female, and 49% were non-Latino White; 62 participants (12%) were classified as having dementia by the cohort assessment. MA-encounter-based dementia indicators performed reasonably well in identifying participants with cohort-assessed dementia: using encounters alone, positive predictive value was 63% (95% CI: 52%-75%), negative predictive value was 96% (95% CI: 94%-98%), and accuracy was 92% (95% CI: 89%-94%). Inclusion of chart reviews did not impact performance. Compared to TM-based indicators during the same period, MA-based indicators yielded similar validity metrics but identified a less functionally impaired group as having dementia. In secondary validation analysis of mild cognitive impairment (MCI), sensitivity was low.
CONCLUSIONS: As one of the first studies to validate dementia diagnoses in MA encounter data, indicators based on the Bynum-Standard algorithm can be a valid tool for identifying prevalent dementia. Findings support the use of MA-encounter-based dementia indicators for research within MA. However, observed health differences between MA- and TM-identified dementia groups suggest potential for selection bias in MA plans.
METHODS: Using four cohort studies at the Rush Alzheimer's Disease Center linked to Medicare data from 2017-19, we validated prevalent dementia indicators in MA encounter data, based on the Bynum-Standard algorithm, against dementia status determined by rigorous cognitive assessment in the cohort studies. We replicated analyses among participants in Traditional Medicare (TM).
RESULTS: Of the 508 eligible MA enrollees, mean age was 82.8 (SD = 7.2) years, 81% were female, and 49% were non-Latino White; 62 participants (12%) were classified as having dementia by the cohort assessment. MA-encounter-based dementia indicators performed reasonably well in identifying participants with cohort-assessed dementia: using encounters alone, positive predictive value was 63% (95% CI: 52%-75%), negative predictive value was 96% (95% CI: 94%-98%), and accuracy was 92% (95% CI: 89%-94%). Inclusion of chart reviews did not impact performance. Compared to TM-based indicators during the same period, MA-based indicators yielded similar validity metrics but identified a less functionally impaired group as having dementia. In secondary validation analysis of mild cognitive impairment (MCI), sensitivity was low.
CONCLUSIONS: As one of the first studies to validate dementia diagnoses in MA encounter data, indicators based on the Bynum-Standard algorithm can be a valid tool for identifying prevalent dementia. Findings support the use of MA-encounter-based dementia indicators for research within MA. However, observed health differences between MA- and TM-identified dementia groups suggest potential for selection bias in MA plans.