  Interest in an electronic health record-based computational model that can
accurately predict a patient's risk of sepsis at a given point in time has
grown rapidly in the last several years. Like other EHR vendors, the Epic
Systems Corporation has developed a proprietary sepsis prediction model (ESPM).
Epic developed the model using data from three health systems and penalized
logistic regression. Demographic, comorbidity, vital sign, laboratory,
medication, and procedural variables contribute to the model. The objective of
this project was to compare the predictive performance of the ESPM with a
regional health system's current Early Warning Score-based sepsis detection
program.
