Development and Validation of an Index Score to Adjust for Healthy User Bias in Observational Studies.

Abstract

Objectives: To develop a healthy user index to serve as a method of confounding adjustment in future observational studies of preventive therapies. A large administrative database of patients with type 2 diabetes was split in half randomly, yielding derivation and validation cohorts. Influenza vaccination was used as a 'prototypical marker' of a healthy user. In our derivation cohort, we fitted a mixed effects logistic regression model, and a points-based system was used to construct the index. The healthy user index was then evaluated in the validation cohort. Overall, 13% had received the influenza vaccination. In the derivation cohort (n= 914 732), the healthy user index ranged from 0 to 91 with a mean of 41.6 (SD 12.9). When applied to the validation cohort (n= 913 231), the index ranged from 0 to 96 (mean 41.6, SD 12.9) and significantly predicted influenza vaccination with a c-statistic of 0.605, suggesting moderate discrimination ability. Our healthy user index combined age, sex and healthy behaviors to predict healthy users within administrative datasets. This index score may allow for better adjustment of healthy user bias in health services research; however, external validation is further required. Key Words: Administrative Data Uses, Bias, Biostatistical Methods, Observational Data.