Transforming ED Throughput With AI-Driven Clinical Decision Support System (TEDAI)

National Taiwan University

Status: Completed

Conditions: Critical Care; Emergency Treatment; Readmission; Triage

Treatments: Procedure: Critical treatment; Other: AI-assisted models providing diagnosis and prognostic information

Study type: Interventional

Funder types: Other

Identifiers

NCT05272267

202108090RINC

Details and patient eligibility

About

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.

Enrollment: 4,016 patients

Sex: All

Ages: 20+ years old

Volunteers: No Healthy Volunteers

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.

Trial design

Primary purpose: Health Services Research

Allocation: Randomized

Interventional model: Crossover Assignment

Masking: None (Open label)

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4,016 participants in 2 patient groups, including a placebo group

AI-assisted

Active Comparator group

Description:

AI-assisted models providing diagnosis and prognostic information

Treatment:

Other: AI-assisted models providing diagnosis and prognostic information

Usual care

Placebo Comparator group

Description:

usual care without AI-assisted models providing diagnosis and prognostic information

Treatment:

Procedure: Critical treatment