Artificial Intelligence System for the Medical Regulation of Emergencies
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 500,000
- 主要终点
- Performance (sensitivity and specificity) of the artificial intelligence system in Emergency medical Communication Centres, concerning time sensitive disease
研究概览
简要总结
Population health needs are increasing. Information and communication technologies are changing. The digital shift offers new opportunities for the exploration and analysis of mass health data. It is possible to rely on these new technologies to modernize, optimize patient management at the level of emergency medical communication centres.
Our project aims to integrate the methods and tools of artificial intelligence for emergency medical communication centres. The system aims to help regulate emergency calls at CRRA 15 in France, or Centrale 144 in Switzerland, to assess the severity of calls, identify care pathways, and improve efficiency when committing resources.
The development of such a system is aimed at securing and optimising the information system and the means of telecommunication used in the emergency medical communication centres, and provide an individualized response to the patient management.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •all patient which call the emergency medical communication centres
排除标准
- •patient opposed to the study
结局指标
主要结局
Performance (sensitivity and specificity) of the artificial intelligence system in Emergency medical Communication Centres, concerning time sensitive disease
时间窗: through study completion, average 3 years
Once the artificial intelligence system in place, the diagnosis suspected by this system will be compared to the diagnosis validated in the medical record of each patient included. It will then be measured the performance values, such as sensitivity, specificity, positive and negative predictive value, time of identification of the pathology type time sensitive. These results will then be compared to the usual practice of the Emergency medical Communication Centres without the help of the software to evaluate: * the added value of the software for the patient, * the added value of the call center through the quality indicators (intake rate, quality of service, load rate, average call duration, productivity)
次要结局
- Patient transport time(through study completion, average 3 years)