Health administrative data enrichment using cohort information: Comparative evaluation of methods by simulation and application to real data.

ABSTRACT: BACKGROUND:Studies using health administrative databases (HAD) may lead to biased results since information on potential confounders is often missing. Methods that integrate confounder data from cohort studies, such as multivariate imputation by chained equations (MICE) and two-stage calibration (TSC), aim to reduce confounding bias. We provide new insights into their behavior under different deviations from representativeness of the cohort. METHODS:We conducted an extensive simulation study to assess the performance of these two methods under different deviations from representativeness of the cohort. We illustrate these approaches by studying the association between benzodiazepine use and fractures in the elderly using the general sample of French health insurance beneficiaries (EGB) as

SUBMITTER: Silenou BC 

PROVIDER: S-EPMC6354983 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature