Emergency Medicine
Conditions
Keywords
Machine Learning, Data Mining, Artificial Intelligence
Brief summary
This observational study aims to use electronic health records to build an International Big Data Centre in Emergency Medicine, within the Institute of Sciences in Emergency Medicine (ISEM) at the Guangdong Provincial People's Hospital. The main questions it seeks to answer are not limited to the following: * Identify the relationship between Emergency Department Length of Stay (EDLOS), Mortality, and Adverse Events (AE) * Identify the risk factors associated with high mortality and AE rate among patients who experience prolonged EDLOS * Other research questions related to emergency medicine, such as building prediction and cluster models for acute diseases
Detailed description
The relationship between the emergency department length-of-stay (EDLOS), mortality, and adverse events (AE) rate remains unclear and underestimated. EDLOS is the time elapsed between the time of arrival and the time of the release of a patient admitted to ED. Mortality is defined as short-term (14 hours, 48 hours, 7 days, 15 days) and 30 days death of patients managed in the ED discharged or admitted. An AE is an event that can result whether from medical mismanagement or happen by accident and causes physical and mental harm to the patient during the stay and remains after leaving. To separate the mismanagement from accidental causes i.e., compliant management but the unfortunate situation or persons, this study will refer to indicators that are objectively measurable and can be compared at different times throughout the patient's stay in the ED. The hypothesis is that a prolonged stay of the patients in the ED especially without diagnosis or decision of admission is associated with increased mortality and AEs. This project will test this hypothesis through a prospective international multicenter study in contributing to whether a prolonged EDLOS is associated with an increased rate of adverse outcomes.
Interventions
None listed
Sponsors
Guangdong Provincial People's Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
Inclusion criteria
* Every patient who ever visited Emergency Department from 2011-2022
Exclusion criteria
* Patients with missing demographic (age, gender, etc.) and triage data
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| In-hospital Mortality | From date of ED triage until the date of discharge or date of death from any cause, whichever came first, assessed up to 1 month | IHM |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Number of Adverse Events | From date of ED triage until the date of discharge or date of death from any cause, whichever came first, assessed up to 1 month | AE |
Countries
China
Contacts
CONTACTAbdelouahab Bellou, MD, PhD, MSc
PRINCIPAL_INVESTIGATORAbdelouahab Bellou, MD, PhD, MSc
Guangdong Provincial People's Hospital
Outcome results
None listed