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

Sponsor
Chinese University of Hong Kong (Other)
Overall Status
Completed
CT.gov ID
NCT05025683
Collaborator
The University of Hong Kong (Other)
23,425
Enrollment
1
Location
24
Actual Duration (Months)
976.7
Patients Per Site Per Month

Study Details

Study Description

Brief 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.

Condition or Disease Intervention/Treatment Phase

    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 Design

    Study Type:
    Observational
    Actual Enrollment :
    23425 participants
    Observational Model:
    Cohort
    Time Perspective:
    Retrospective
    Official Title:
    Analyzing Patient Flows at the Emergency Department by Data Analytics, Simulation, and Optimization
    Actual Study Start Date :
    Jan 21, 2019
    Actual Primary Completion Date :
    Dec 1, 2020
    Actual Study Completion Date :
    Jan 20, 2021

    Outcome Measures

    Primary Outcome Measures

    1. Quantitative models [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

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    N/A and Older
    Sexes Eligible for Study:
    All
    Accepts Healthy Volunteers:
    No
    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

    Contacts and Locations

    Locations

    Site City State Country Postal Code
    1 Prince of Wales Hospital Sha Tin NT Hong Kong

    Sponsors and Collaborators

    • Chinese University of Hong Kong
    • The University of Hong Kong

    Investigators

    • Principal Investigator: Colin A Graham, MD, Chinese University of Hong Kong

    Study Documents (Full-Text)

    None provided.

    More Information

    Publications

    None provided.
    Responsible Party:
    Colin Graham, Professor, Chinese University of Hong Kong
    ClinicalTrials.gov Identifier:
    NCT05025683
    Other Study ID Numbers:
    • CRE.2018.342
    First Posted:
    Aug 27, 2021
    Last Update Posted:
    Aug 27, 2021
    Last Verified:
    Aug 1, 2021
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No
    Keywords provided by Colin Graham, Professor, Chinese University of Hong Kong
    Emergency department
    Simulation
    Patient Flows
    Additional relevant MeSH terms:
    Emergencies

    Study Results

    No Results Posted as of Aug 27, 2021