NCT05272267

Transforming ED Throughput With AI-Driven Clinical Decision Support System

Transforming ED Throughput With AI-Driven Clinical Decision Support System (TEDAI): The Impact on the Delivery of Care and Patient Experience

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 4,016 (actual)
• Sponsor: National Taiwan University Hospital · Academic / Other
• Sex: All
• Age: 20 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Critical Care
• Emergency Treatment
• Triage
• Readmission

Interventions

Type	Name	Description
OTHER	AI-assisted models providing diagnosis and prognostic information	AI-assisted models providing diagnosis and prognostic information in the ED, including triage, ICD coding, chest x ray alerts, critical event alerts, readmission prediction, and post-cardiac arrest prognostication.
PROCEDURE	Critical treatment	Critical treatment of the emergency room

Timeline

• Start date: 2022-08-30
• Primary completion: 2022-12-31
• Completion: 2023-04-27
• First posted: 2022-03-09
• Last updated: 2023-08-01

Locations

1 site across 1 country: Taiwan