Institution-Specific Machine Learning Models for Prehospital Assessment to Predict Hospital Admission: Prediction Model Development Study.

ABSTRACT:

Background

Although multiple prediction models have been developed to predict hospital admission to emergency departments (EDs) to address overcrowding and patient safety, only a few studies have examined prediction models for prehospital use. Development of institution-specific prediction models is feasible in this age of data science, provided that predictor-related information is readily collectable.

Objective

We aimed to develop a hospital admission prediction model based on patient information that is commonly available during ambulance transport before hospitalization.

Methods

Patients transported by ambulance to our ED from April 2018 through March 2019 were enrolled. Candidate predictors were age, sex, chief complaint, vital signs, and patient medical history,

SUBMITTER: Shirakawa T 

PROVIDER: S-EPMC7655472 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature