Electronic health record machine learning model predicts trauma inpatient mortality in real time: A validation study.

ABSTRACT:

Introduction

Patient outcome prediction models are underused in clinical practice because of lack of integration with real-time patient data. The electronic health record (EHR) has the ability to use machine learning (ML) to develop predictive models. While an EHR ML model has been developed to predict clinical deterioration, it has yet to be validated for use in trauma. We hypothesized that the Epic Deterioration Index (EDI) would predict mortality and unplanned intensive care unit (ICU) admission in trauma patients.

Methods

A retrospective analysis of a trauma registry was used to identify patients admitted to a level 1 trauma center for >24 hours from October 2019 to July 2020. We evaluated the performance of the EDI, which is constructed from 125 objective patient measur

SUBMITTER: Mou Z 

PROVIDER: S-EPMC9032917 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature