Beating the Clock: A Prediction Model for Timely Care in Emergency Departments

Jonas Bienzeisler; Wiliam Hoy; Alexander Kombeiz; Mohamed Alhaskir; Rainer Röhrig; Raphael Majeed; Jenny Unterkofler; Behrus Puladi

doi:10.3233/SHTI240741

Beating the Clock: A Prediction Model for Timely Care in Emergency Departments

Stud Health Technol Inform. 2024 Aug 22:316:1657-1658. doi: 10.3233/SHTI240741.

Authors

Jonas Bienzeisler¹, Wiliam Hoy¹, Alexander Kombeiz¹, Mohamed Alhaskir¹, Rainer Röhrig¹, Raphael Majeed¹, Jenny Unterkofler², Behrus Puladi¹

Affiliations

¹ Institute of Medical Informatics, Medical Faculty of RWTH Aachen University, Aachen, Germany.
² Department for Acute and Emergency Medicine, Medical Faculty of RWTH Aachen University, Aachen, Germany.

PMID: 39176528
DOI: 10.3233/SHTI240741

Abstract

We developed and validated a statistical prediction model using 2.5 electronic health records from 24 German emergency departments (EDs) to estimate treatment timeliness at triage. The model's moderate fit and reliance on interoperable, routine data suggest its potential for implementation in ED crowding management.

Keywords: EHR; Predictive Modelling; clinical routine data.

MeSH terms

Crowding
Electronic Health Records*
Emergency Service, Hospital*
Germany
Humans
Models, Statistical
Triage*