Yannick Fortin,1,2 James AG Crispo,1–4 Deborah Cohen,2,5,6 Douglas S McNair,7 Donald R Mattison,1,8 Daniel Krewski1,2,8 1McLaughlin Centre for Population Health Risk Assessment, 2School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, ON, Canada; 3Fulbright Canada, 4Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; 5Canadian Population Health Initiative, Canadian Institute for Health Information, Ottawa, 6Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada; 7Cerner Corporation, Kansas City, MO, USA; 8Risk Sciences International, Ottawa, ON, Canada 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