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

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

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05025683
Enrollment
23425
Registered
2021-08-27
Start date
2019-01-21
Completion date
2021-01-20
Last updated
2021-08-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Emergency Patients

Keywords

Emergency department, Simulation, Patient Flows

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.

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.

Interventions

None listed

Sponsors

The University of Hong Kong
CollaboratorOTHER
Chinese University of Hong Kong
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
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

Design outcomes

Primary

MeasureTime frameDescription
Quantitative models12 months after recruitmentQuantitative 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

Countries

Hong Kong

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026