NCT05272267已完成不适用
Transforming ED Throughput With AI-Driven Clinical Decision Support System (TEDAI): The Impact on the Delivery of Care and Patient Experience
适应症
干预措施
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 4,016
- 试验地点
- 1
- 主要终点
- ED length of stay
研究概览
简要总结
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Crossover
- 主要目的
- Health Services Research
- 盲法
- None
入排标准
- 年龄范围
- 20 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •ED patients aged 20 years or older
- •Patients were treated by the recruited 16 ED attendings.
排除标准
- •Patients aged less than 20 years.
- •Patients were not treated by the recruited 16 ED attendings.
研究组 & 干预措施
AI-assisted
Active Comparator
AI-assisted models providing diagnosis and prognostic information
干预措施: AI-assisted models providing diagnosis and prognostic information (Other)
Usual care
Placebo Comparator
usual care without AI-assisted models providing diagnosis and prognostic information
干预措施: Critical treatment (Procedure)
结局指标
主要结局
ED length of stay
时间窗: From ED arrival to 3 days after ED discharge. For hospitalized patients with cardiac arrest, the outcome ascertainment continues until hospital discharge.
次要结局
未报告次要终点
研究者
研究点 (1)
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