Building an International Big Data Centre in Emergency Medicine
Official title: Institute of Sciences in Emergency Medicine - International Big Data Centre in Emergency Medicine
Run by Guangdong Provincial People's Hospital · NCT05616416 · Data updated 2026-11-12
This study is trying to see how the time patients spend in the emergency department affects their health outcomes, using data from past visits to help improve emergency care.
Quick facts
| Study type | Observational |
|---|---|
| Sex | All |
| Enrollment | 500000 (estimated) |
| Sponsor | Guangdong Provincial People's Hospital Academic / other |
| Locations | 1 site (Guangzhou, Guangdong) |
| Status | Recruiting |
| Started | January 1, 2011 |
| Main results expected | December 2027 |
| Study ends | December 2027 |
| Registry record updated | July 1, 2026 |
| Trial ID | NCT05616416 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates for this study include any patients who visited the emergency department from 2011 to 2022.
✕Probably not a fit
Patients with incomplete demographic or triage data will not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study aims to utilize electronic health records to establish an International Big Data Centre focused on emergency medicine at the Guangdong Provincial People's Hospital. It seeks to explore the relationship between emergency department length of stay (EDLOS), mortality rates, and adverse events among patients. The study will analyze data from patients who visited the emergency department between 2011 and 2022 to identify risk factors associated with prolonged EDLOS and its impact on patient outcomes. By building predictive models, the research aims to enhance understanding of acute diseases and improve emergency care.
Why it matters
Potential benefit: If successful, this study could lead to improved patient outcomes in emergency medicine by identifying critical risk factors and enhancing predictive capabilities.
How similar studies have gone: Other studies utilizing big data and machine learning in emergency medicine have shown promise, indicating potential for success in this approach.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Every patient who ever visited Emergency Department from 2011-2022 Exclusion Criteria: * Patients with missing demographic (age, gender, etc.) and triage data
Where it's running
-
Guangdong Provincial People's Hospital
Guangzhou, Guangdong, China Recruiting
Study contacts
- Principal investigator: Abdelouahab Bellou, MD, PhD, MSc — Guangdong Provincial People's Hospital
- Study coordinator: Abdelouahab Bellou, MD, PhD, MSc
- Email: abellou402@gmail.com
- Phone: +16176693707
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.