Optimal look back period and summary method for Elixhauser comorbidity measures in a US population-based electronic health record database

Abstract

Background: Comorbidity risk-adjustment tools are widely used in health database research to control for clinical differences between individuals, but they need to be validated a priori. This study aimed to identify the optimal parameters for predicting all-cause inhospital mortality using Quan’s enhanced Elixhauser comorbidity measures (ECMs) in the US-based Cerner Health Facts® (HF) electronic health record database. Methods: Health care recipients aged 18–89 years between 2002 and 2011 were included. Prevalent comorbidities recorded, 1) during the index encounter; 2) in the prior year; and 3) in the prior 2 years were identified using the ECMs. Multiple logistic regression models, with inhospital mortality at index and at 1 year as the predicted outcomes, were fitted with comorbidities summarized as binary indicators, total counts, or weighted scores for the three look back periods. Baseline variables included sex and age. The receiver operating characteristic (ROC) curves of the competing models were compared with a non-parametric Mann–Whitney U test to identify the optimal parameters. Results: A sample of 3,273,298 unique health care recipients were included, of whom 31,298 (1.0%) and 50,215 (1.5%) died during the index encounter and within the 1-year follow-up, respectively. Models of comorbidity based on binary and weighted indicators had near-identical performance and were statistically better than the models based on total counts (p < 0.0001). Discrimination of inhospital mortality was highest with a look back period limited to the index encounter, while inhospital mortality at 1 year was best predicted with 1 year of look back (p < 0.0001). Conclusion: In Cerner HF, the binary and weighted methods for summarizing the Quan ECM were the best predictors of all-cause inhospital mortality at index and at 1 year. Observed differences in predictive performance between models with diagnostic ascertainment periods of up to 2 years of look back were statistically significant but not practically important.