Development of a Real-Time Risk Model (RTRM) for Predicting In-Hospital COVID-19 Mortality

Background: With over 83 million cases and 1.8 million deaths reported worldwide by the end of 2020 for SARS-CoV-2 (COVID-19), there is an urgent need to enhance identification of high-risk populations to properly evaluate therapy effectiveness with real-world evidence and improve outcomes. Methods: Baseline and daily indicators were evaluated using electronic health records for 46,971 patients hospitalized with COVID-19 from 176 HCA Healthcare-affiliated hospitals, presenting from March to September 2020, to develop a real-time risk model (RTRM) of all-cause, hospitalized mortality. Patient facility, dates-of-care, clinico-demographics, comorbidities, vitals, laboratory markers, and respiratory support findings were aggregated in a logistic regression model. Findings: The RTRM predicted overall mortality as well as mortality 1, 3, and 7 days in advance with an area under the receiver operating characteristic curve (AUCROC) of 0.905, 0.911, 0.905, and 0.901 respectively, significantly outperforming a combined model of age and daily modified WHO progression scale (all p<0.0001; AUCROC, 0.846, 0.848, 0.850, and 0.852). The RTRM delineated risk at presentation from ongoing risk associated with medical care and showed that mortality rates decreased over time due to both decreased severity and changes in care. Interpretation: To our knowledge, this study is the largest of its kind to comprehensively evaluate predictors and incorporate daily risk measures of COVID-19 mortality. The RTRM validates current literature trends in mortality across time and allows direct translation for research and clinical applications.