Development of Algorithmic Dementia Ascertainment for Racial/Ethnic Disparities Research in the US Health and Retirement Study

Epidemiology. 2020 Jan;31(1):126-133. doi: 10.1097/EDE.0000000000001101.

Abstract

Background: Disparities research in dementia is limited by lack of large, diverse, and representative samples with systematic dementia ascertainment. Algorithmic diagnosis of dementia offers a cost-effective alternate approach. Prior work in the nationally representative Health and Retirement Study has demonstrated that existing algorithms are ill-suited for racial/ethnic disparities work given differences in sensitivity and specificity by race/ethnicity.

Methods: We implemented traditional and machine learning methods to identify an improved algorithm that: (1) had ≤5 percentage point difference in sensitivity and specificity across racial/ethnic groups; (2) achieved ≥80% overall accuracy across racial/ethnic groups; and (3) achieved ≥75% sensitivity and ≥90% specificity overall. Final recommendations were based on robustness, accuracy of estimated race/ethnicity-specific prevalence and prevalence ratios compared to those using in-person diagnoses, and ease of use.

Results: We identified six algorithms that met our prespecified criteria. Our three recommended algorithms achieved ≤3 percentage point difference in sensitivity and ≤5 percentage point difference in specificity across racial/ethnic groups, as well as 77%-83% sensitivity, 92%-94% specificity, and 90%-92% accuracy overall in analyses designed to emulate out-of-sample performance. Pairwise prevalence ratios between non-Hispanic whites, non-Hispanic blacks, and Hispanics estimated by application of these algorithms are within 1%-10% of prevalence ratios estimated based on in-person diagnoses.

Conclusions: We believe these algorithms will be of immense value to dementia researchers interested in racial/ethnic disparities. Our process can be replicated to allow minimally biasing algorithmic classification of dementia for other purposes.

MeSH terms

  • African Americans
  • Algorithms*
  • Biomedical Research*
  • Dementia* / diagnosis
  • Dementia* / ethnology
  • Ethnic Groups*
  • European Continental Ancestry Group
  • Health Status Disparities*
  • Hispanic Americans
  • Humans
  • Sensitivity and Specificity
  • United States / epidemiology