Interpretable machine learning models for prolonged Emergency Department wait time prediction.

ABSTRACT:

Objective

Prolonged Emergency Department (ED) wait times lead to diminished healthcare quality. Utilizing machine learning (ML) to predict patient wait times could aid in ED operational management. Our aim is to perform a comprehensive analysis of ML models for ED wait time prediction, identify key feature importance and associations with prolonged wait times, and interpret prediction model clinical relevance among ED patients.

Methods

This is a single-centered retrospective study. We included ED patients assigned an Emergency Severity Index (ESI) level of 3 at triage. Patient wait times were categorized as <30 minutes and ≥30 minutes (prolonged wait time). We employed five ML algorithms - cross-validation logistic regression (CVLR), random forest (RF), extreme gradient boos

SUBMITTER: Wang H 

PROVIDER: S-EPMC11917090 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature