Analyzing Patient Flows at the Emergency Department by Da... | NCT05025683

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

NCT05025683

Sponsor

Chinese University of Hong Kong

Status

Completed

Last Update Posted

Aug 27, 2021Actual

Enrollment

23,425Actual

Phase

Not provided

Conditions

Emergency Patients

Interventions

Not provided

Countries

Hong Kong

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Aug 2021

Overall Recruitment Status or Expanded Access Status

Completed

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Jan 21, 2019Actual

Primary Completion Date

Dec 1, 2020Actual

Completion Date

Jan 20, 2021Actual

First Submitted Date

Aug 19, 2021

First Submission Date that Met QC Criteria

Aug 26, 2021

First Posted Date

Aug 27, 2021Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Aug 26, 2021

Last Update Posted Date

Aug 27, 2021Actual

Name	Class
The University of Hong Kong	OTHER

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

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.

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

23,425Actual

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
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

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

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

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

Not provided

Maximum Age

Not provided

Standard Ages

ChildAdultOlder Adult

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.

Sampling Method

Probability Sample

Contacts/Locations Module

Central Contacts

Not provided

Overall Officials

Name	Affiliation	Role
Colin A Graham, MD	Chinese University of Hong Kong	Principal Investigator

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Prince of Wales Hospital		Shatin	NT		Hong Kong

Condition Browse Module

MeSH Terms

ID	Term
D004630	Emergencies

Ancestor Terms

ID	Term
D020969	Disease Attributes
D010335	Pathologic Processes
D013568	Pathological Conditions, Signs and Symptoms

Browse Leaves

Not provided

Browse Branches

Not provided