Analyzing Patient Flows at the Emergency Department by Data Analytics, Simulation, and Optimization

Emergency Patients Clinical Trial

Official title:

Analyzing Patient Flows at the Emergency Department by Data Analytics, Simulation, and Optimization

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05025683
• Other study ID #: CRE.2018.342
• Status: Completed
• Start date: January 21, 2019
• Est. completion date: January 20, 2021

Study information

• Verified date: August 2021
• Source: Chinese University of Hong Kong
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

In this project, investigators apply operations research techniques, more specifically data analytics, system simulation, mathematical modelling, and optimization, for analyzing and improving operations in the Emergency Department at the Prince of Wales Hospital. The long term goals of this project are to demonstrate that integrated approach of data analytics and systems thinking is beneficial to health service planning and to extend present work to applications in other health-service systems.

Description:

Design and subjects The current study requires time stamps for which patients start and end activities in the department. Personally identifiable information is not needed in this study. Investigators will collect the data from the computer system of the Department. The data will be used for data analysis and the development of simulation and optimization models. With current models, investigators investigate the effects of queueing policies, study workforce planning, and conduct a cost-effectiveness analysis for strategic planning. Study instruments Data analytics tools and simulation and optimization softwares are needed in this research. Interventions With simulation and optimization models, investigators examine the impacts of different operational strategies on the performance of the Emergency Department. The Computational experiments will not disturb the actual operations but will provide insights into the effectiveness of the various intervention policies. Main Outcome Measures Investigators will derive insights from computational experiments and deliver useful recommendations for managing emergency department operations in Hong Kong.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 23425
• Est. completion date: January 20, 2021
• Est. primary completion date: December 1, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• All the patients attended to the Emergency Department of Prince of Wales Hospital in the period of July 2017 to June 2018 will be included in this study.

Exclusion Criteria:

• No patient will be excluded in this study

Related Conditions & MeSH terms

• Emergencies
• Emergency Patients

Locations

Country	Name	City	State
Hong Kong	Prince of Wales Hospital	Sha Tin	NT

Sponsors (2)

Lead Sponsor	Collaborator
Chinese University of Hong Kong	The University of Hong Kong

Country where clinical trial is conducted

Hong Kong, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Quantitative models	Quantitative models, powered by domain knowledge of the Emergency Department (ED) system and ED operational data, will be developed to address three main operational problems in an ED: patient waiting time prediction, impacts of an adoption of a fast-track system, and patient scheduling	12 months after recruitment