Improving Emergency Triage with Machine Learning: Emergency Severity Index Score Prediction and Validation
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 250
- 试验地点
- 1
- 主要终点
- Accuracy of machine learning–predicted Emergency Severity Index (ESI) scores compared with nurse-assigned ESI scores, assessed at baseline triage during emergency department presentation and at the end of the study period (6 months)
研究概览
简要总结
This prospective observational study aims to evaluate the effectiveness of a machine learning–based tool in predicting Emergency Severity Index (ESI) scores in an emergency department setting. Adult patients presenting to the emergency department will undergo routine triage by trained personnel using the ESI system. The tool will independently predict ESI scores using structured clinical data without influencing real-time patient management. The predicted scores will be compared with nurse-assigned ESI scores to assess accuracy and agreement. Secondary objectives include evaluating the impact of the tool on triage efficiency and inter-rater variability. The study seeks to determine whether machine learning can enhance consistency and accuracy in emergency triage while maintaining patient safety
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 18.00 Year(s) 至 65.00 Year(s)（—）
- 性别
- All
入选标准
- •Adult patients aged 18–65 years presenting to the emergency department Patients triaged using the Emergency Severity Index (ESI) by trained personnel Availability of complete triage data including vital signs and chief complaints Patients providing informed consent for use of de-identified data.
排除标准
- •Incomplete or missing triage data Interfacility transfers or direct admissions without ED triage Patients leaving against medical advice or leaving without being seen Repeat ED visits of the same patient during the study period Palliative or end-of-life care patients Records with documented clerical or software errors.
结局指标
主要结局
Accuracy of machine learning–predicted Emergency Severity Index (ESI) scores compared with nurse-assigned ESI scores, assessed at baseline triage during emergency department presentation and at the end of the study period (6 months)
时间窗: Baseline (at ED triage) and end of study (6 months)
次要结局
- Change in emergency department triage time before & after implementation of the machine learning–based triage tool, assessed at baseline (at emergency department presentation) & at the end of the study period (6 months)(At ED presentation / triage)
研究者
Dr Karthika Santhosh
Vinayaka Missions Kirupanandha Variyar Medical College and Hospital Salem