Forecasting ED Overcrowding With Statistical Methods: A Prospective Validation Study

• Conditions: Emergencies

• Registration Number: NCT05174481
• Lead Sponsor: Tampere University Hospital

Brief Summary

The aim of this study is to prospectively validate statistical forecasting tools that have been widely used retrospectively in forecasting ED overcrowding

Detailed Description

Emergency department (ED) overcrowding is a chronic international issue that has been repeatedly associated with detrimental treatment outcomes such increased 10-day-mortality. Forecasting future overcrowding would enable pre-emptive staffing decisions that could alleviate or prevent overcrowding along with its detrimental effects.

Over the years, several predictive algorithms have been proposed ranging from generalized linear models to state space models and, more recently, deep learning algorithms. However, the performance of these algorithms has only been reported retrospectively and the clinically significant accuracy of these algorithms remains unclear.

In this study the investigators aim to investigate the accuracy of the previously reported ED forecasting algorithms in a prospective setting analogous to the way these tools would be used if used implemented as a decision-support system in a real-life clinical setting.

Study Timeline

• Study First Submitted: 2021-12-13
• Study First Submitted QC: 2021-12-13
• Study First Posted: 2021-12-30
• Status Verified: 2022-01
• Study Start: 2022-01-01
• Last Update Submitted: 2022-01-06
• Last Update Posted: 2022-01-10
• Primary Completion: 2022-02-28
• Study Completion: 2022-12-31

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 160000

Inclusion Criteria

• All patients presenting in the Emergency Department

Exclusion Criteria

• No exclusion criteria

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Next day overcrowding	24 hours	A day is defined as overcrowded if daily peak occupancy exceeds 80 patients, and severely overcrowded if daily peak occupancy exceeds 100 patients.

Secondary Outcome Measures

Name	Time	Method
Number of hourly arrivals in the ED 24 hours ahead	24 hour
Hourly occupancy in the ED 24 hours ahead	24 hour
Number of daily arrivals in the ED 7 days ahead	24 hour
Daily peak occupancy in the ED 7 days ahead	24 hours