Transforming ED Throughput With AI-Driven Clinical Decision Support System
Not Applicable
Completed
- Conditions
- TriageReadmissionCritical CareEmergency Treatment
- Interventions
- Other: AI-assisted models providing diagnosis and prognostic informationProcedure: Critical treatment
- Registration Number
- NCT05272267
- Lead Sponsor
- National Taiwan University Hospital
- Brief Summary
The aims of this study is to integrate real-time data flow infrastructure between hospital information system and AI models and to conduct a cluster randomized crossover trial to evaluate the efficacy of the AI models in improving patient flow and relieving ED crowding.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 4016
Inclusion Criteria
- ED patients aged 20 years or older
- Patients were treated by the recruited 16 ED attendings.
Read More
Exclusion Criteria
- Patients aged less than 20 years.
- Patients were not treated by the recruited 16 ED attendings.
Read More
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- CROSSOVER
- Arm && Interventions
Group Intervention Description AI-assisted AI-assisted models providing diagnosis and prognostic information AI-assisted models providing diagnosis and prognostic information Usual care Critical treatment usual care without AI-assisted models providing diagnosis and prognostic information
- Primary Outcome Measures
Name Time Method ED length of stay From ED arrival to 3 days after ED discharge. For hospitalized patients with cardiac arrest, the outcome ascertainment continues until hospital discharge.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
National Taiwan University Hospital
🇨🇳Taipei, Taiwan