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

August 26, 2021 updated by: Colin Graham, Chinese University of Hong Kong
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.

Study Overview

Status

Completed

Conditions

Detailed 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.

Study Type

Observational

Enrollment (Actual)

23425

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Hong Kong
    • NT
      • Sha Tin, NT, Hong Kong
        • Prince of Wales Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • ADULT
  • OLDER_ADULT
  • CHILD

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

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.

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Quantitative models
Time Frame: 12 months after recruitment
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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Chinese University of Hong Kong

Collaborators

The University of Hong Kong

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (ACTUAL)

January 21, 2019

Primary Completion (ACTUAL)

December 1, 2020

Study Completion (ACTUAL)

January 20, 2021

Study Registration Dates

First Submitted

August 19, 2021

First Submitted That Met QC Criteria

August 26, 2021

First Posted (ACTUAL)

August 27, 2021

Study Record Updates

Last Update Posted (ACTUAL)

August 27, 2021

Last Update Submitted That Met QC Criteria

August 26, 2021

Last Verified

August 1, 2021

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • CRE.2018.342

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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