Transforming ED Throughput With AI-Driven Clinical Decision Support System

Not Applicable

Completed

• Conditions: Triage; Readmission; Critical Care; Emergency 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

Study Timeline

• Study First Submitted: 2022-02-28
• Study First Submitted QC: 2022-02-28
• Study First Posted: 2022-03-09
• Status Verified: 2022-07
• Study Start: 2022-08-30
• Primary Completion: 2022-12-31
• Study Completion: 2023-04-27
• Last Update Submitted: 2023-07-28
• Last Update Posted: 2023-08-01

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.

Exclusion Criteria

• Patients aged less than 20 years.
• Patients were not treated by the recruited 16 ED attendings.

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: CROSSOVER

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.

Trial Locations

Locations (1)

National Taiwan University Hospital; 🇨🇳 Taipei, Taiwan