Forecasting ED Overcrowding With Statistical Methods: A Prospective Validation Study

Emergencies Clinical Trial

Official title:

Forecasting ED Overcrowding With Statistical Methods: A Prospective Validation Study

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05174481
• Other study ID #: ed-pro
• Status: Not yet recruiting
• Start date: January 1, 2022
• Est. completion date: December 31, 2022

Study information

• Verified date: January 2022
• Source: Tampere University Hospital
• Contact: Jalmari Tuominen, MD
• Phone: +358505961192
• Email: jalmari.tuominen[@]tuni.fi
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

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

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 160000
• Est. completion date: December 31, 2022
• Est. primary completion date: February 28, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 16 Years and older

Eligibility

Inclusion Criteria:

• All patients presenting in the Emergency Department

Exclusion Criteria:

• No exclusion criteria

Related Conditions & MeSH terms

• Emergencies

Intervention

Other:
• Early warning system for emergency department overcrowding
In this study, no interventions are performed.

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Tampere University Hospital

References & Publications (2)

Gul M, Celik E. An exhaustive review and analysis on applications of statistical forecasting in hospital emergency departments. Health Syst (Basingstoke). 2018 Nov 19;9(4):263-284. doi: 10.1080/20476965.2018.1547348. Review. — View Citation

Richardson DB. Increase in patient mortality at 10 days associated with emergency department overcrowding. Med J Aust. 2006 Mar 6;184(5):213-6. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Next day overcrowding	A day is defined as overcrowded if daily peak occupancy exceeds 80 patients, and severely overcrowded if daily peak occupancy exceeds 100 patients.	24 hours
Secondary	Number of hourly arrivals in the ED 24 hours ahead		24 hour
Secondary	Hourly occupancy in the ED 24 hours ahead		24 hour
Secondary	Number of daily arrivals in the ED 7 days ahead		24 hour
Secondary	Daily peak occupancy in the ED 7 days ahead		24 hours