Emergency PatientsNCT05025683
Analyzing Patient Flows at the Emergency Department by Data Analytics, Simulation, and Optimization
An observational study of Emergency Patients, run by Chinese University of Hong Kong at 1 site in Hong Kong.
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. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Emergency Patients
- How many people
- 23,425 participants
- Where
- 1 siteHong Kong
- Study dates
- 21 Jan 2019to 20 Jan 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older 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.
Who may be able to join
- 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.
Who cannot join
- No patient will be excluded in this study
Trial locations and contacts
1 site in 1 country.
About this study
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.
Read the 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.
- Conditions
- Emergency Patients
- Keywords
- Emergency department, Simulation, Patient Flows
- Medical subject headings
- Emergencies
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: 12 months after recruitment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Aug 2021
- Study start21 Jan 2019
- Primary completion1 Dec 2020
- Study completion20 Jan 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Emergency PatientsStudies of the same condition, open and under way.
- More trials run by Chinese University of Hong KongThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 23,425 participants (actual)
Sponsor and investigators
- Lead sponsor
- Chinese University of Hong Kong
- Sponsor type
- University, hospital or other
- Collaborators
- The University of Hong Kong
- Responsible party
- Principal investigator, Colin Graham, Chinese University of Hong Kong
- Investigators
- Colin A Graham, MD, Principal investigator, Chinese University of Hong Kong
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05025683
- Sponsor's protocol ID
- CRE.2018.342
- Status last verified
- Aug 2021
- First submitted
- 19 Aug 2021
- Last updated
- 27 Aug 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 27 Aug 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Analyzing Patient Flows at the Emergency Department by Data Analytics, Simulation, and Optimization
- ClinicalTrials.gov ID
- NCT05025683
- Acronym / sponsor ID
- CRE.2018.342
- Conditions
- Emergency Patients
- Keywords
- Emergency department, Simulation, Patient Flows
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 23,425 participants (actual)
- Lead sponsor
- Chinese University of Hong KongUniversity, hospital or other
- Collaborators
- The University of Hong Kong
- Study start
- 21 Jan 2019 (actual)
- Primary completion
- 1 Dec 2020 (actual)
- Study completion
- 20 Jan 2021 (actual)
- First posted
- 27 Aug 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older 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.
Key inclusion criteria (1 listed)
- 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.
Key exclusion criteria (1 listed)
- No patient will be excluded in this study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
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
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Aug 2021.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Colin A Graham, MD principal investigator
Chinese University of Hong Kong
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Emergency Patients, run by Chinese University of Hong Kong at 1 site in Hong Kong.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 27 Aug 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Hong Kong. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Quantitative models (time frame: 12 months after recruitment). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 27 Aug 2021.