Deductible imputation in administrative medical claims datasets
Mark Meiselbach, Matthew Eisenberg, Betsy Q. Cliff PhD, Julia C. P. Eddelbuettel BS
Objective:
To validate imputation methods used to infer plan-level deductibles and determine which enrollees are in high-deductible health plans (HDHPs) in administrative claims datasets.
Data Sources and Study Setting:
2017 medical and pharmaceutical claims from OptumLabs Data Warehouse for US individuals <65 continuously enrolled in an employer-sponsored plan. Data include enrollee and plan characteristics, deductible spending, plan spending, and actual plan-level deductibles. Study Design: We impute plan deductibles using four methods: (1) parametric prediction using individual-level spending; (2) parametric prediction with imputation and plan characteristics; (3) highest plan-specific mode of individual annual deductible spending; and (4) deductible spending at the 80th percentile among individuals meeting their deductible. We compare deductibles’ levels and categories for imputed versus actual deductibles.
Citation:
Cliff BQ, Eddelbuettel JCP, Meiselbach MK, Eisenberg MD. Deductible imputation in administrative medical claims datasets. Health Serv Res. 2024; 1‐7. doi:10.1111/1475-6773.14278