Validation of a Retrospective Computing Model for Mortality Risk in the Intensive Care Unit
Year: 2020
Type: article
Study design: Observational Study
Abstract: Objective To compare the predictive performance of Epic Systems Corporation's proprietary intensive care unit (ICU) mortality risk model (IMRM) with that of the Acute Physiology and Chronic Health Evaluation (APACHE) IV score. Methods This is a retrospective cohort study of patients treated from January 1, 2008, through January 1, 2018. This single-center study was performed at Mayo Clinic (Rochester, MN), a tertiary care teaching and referral center. The primary outcome was death in the ICU. Discrimination of each risk model for hospital mortality was assessed by comparing area under the receiver operating characteristic curve (AUROC). Results The cohort mostly comprised older patients (median age, 64 years) and men (56.7%). The mortality rate of the cohort was 3.5% (2251 of 63,775 patients). The AUROC for mortality prediction was 89.7% (95% CI, 89.5% to 89.9%) for the IMRM, which was significantly greater than the AUROC of 88.2% (95% CI, 87.9% to 88.4%) for APACHE IV ( P <.001). Conclusion The IMRM was superior to the commonly used APACHE IV score and may be easily integrated into electronic health records at any hospital using Epic software.
Authors: Eugene M. Tan, Rahul Kashyap, Ian C. Olson, John C. O’Horo
Institutions: Mayo Clinic, Epic Systems (United States)
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,000
OpenAlex ID: W3091867920