Optimization of Treatment Priority of the Manchester Triage System
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 77,976
- 试验地点
- 1
- 主要终点
- AUROC for Classification of Admission to Intensive Care Unit
研究概览
简要总结
In the emergency department, the urgency for treating patients is determined according to the Manchester Triage System. The parameters collected in this process are deterministically translated into a treatment priority.
The Manchester Triage System (MTS), which has been in use for at least 20 years, is a widely used, validated and standardized procedure for initial assessment in the emergency department - this initial assessment (triage) is done to prioritize medical assistance at a central point. Especially in emergency situations, critically endangered patients often require the deployment of a large part of the available staff at the same time - the medically correct triage of patients according to objective criteria in order to enable an adequate allocation of the available resources at the right time is the main objective. In the optimal case, each patient is treated by medical professionals within the time frame that is adequate for his/her health condition.
Using artificial intelligence methods, it may be possible to increase the accuracy of treatment priority assignment. In the best case, incorrect prioritization of patients can be prevented and medical care can be ensured for those patients who actually need it most urgently.
However, initial assessment, even if standardized and validated, still runs under limited resource conditions - time, space, material and personnel. Last but not least, the very idea of conducting an initial assessment limits its validity, and the results of the allocation fluctuate according to current research, although the determinants of this are currently unknown.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 120 Years(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •All adult patients that were triaged at the emergency department at the Kepler University Hospital in the period between 2015-12-01 to 2020-08-31.
排除标准
- 未提供
结局指标
主要结局
AUROC for Classification of Admission to Intensive Care Unit
时间窗: 2015-12-01 to 2020-08-31
AUROC for Classification of Admission to Intensive Care Unit
AUROC for Classification of 30 Day Mortality
时间窗: 2015-12-01 to 2020-08-31
AUROC for Classification of 30 Day Mortality
AUROC for Classification of Admission to General Ward
时间窗: 2015-12-01 to 2020-08-31
AUROC for Classification of Admission to General Ward
次要结局
- Confusion Matrix(2015-12-01 to 2020-08-31)
