确保紧急救护服务响应中的安全人工智能:研究方案。

Mark Sujan, Harold Thimbleby, Ibrahim Habli, Andreas Cleve, Lars Maaløe, Nigel Rees
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引用次数: 1

摘要

引言:救护车服务呼叫中心接线员对院外心脏骤停(OHCA)的早期识别非常重要,这样可以立即进行心肺复苏,但约25%的院外心脏骤停没有被呼叫中心接线员发现。一个人工智能(AI)系统已经开发出来,以支持呼叫中心操作员检测OHCA。本研究旨在(1)探讨救护车服务利益相关者对呼叫中心OHCA AI决策支持安全性的看法,以及(2)为OHCA AI决策支持系统开发临床安全案例。方法和分析:该研究将在威尔士救护车服务中心进行。本研究部分是研究,部分是服务评价。本研究采用基于访谈数据专题分析的定性研究设计。服务评估包括基于文献分析的临床安全案例的开发,人工智能模型及其开发过程的分析以及与技术开发人员的非正式访谈。结论:人工智能为救护车服务提供了许多机会,但需要了解安全保障要求。ASSIST项目将继续探索和建立这一领域的知识体系。
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Assuring safe artificial intelligence in critical ambulance service response: study protocol.

Introduction: Early recognition of out-of-hospital cardiac arrest (OHCA) by ambulance service call centre operators is important so that cardiopulmonary resuscitation can be delivered immediately, but around 25% of OHCAs are not picked up by call centre operators. An artificial intelligence (AI) system has been developed to support call centre operators in the detection of OHCA. The study aims to (1) explore ambulance service stakeholder perceptions on the safety of OHCA AI decision support in call centres, and (2) develop a clinical safety case for the OHCA AI decision-support system.

Methods and analysis: The study will be undertaken within the Welsh Ambulance Service. The study is part research and part service evaluation. The research utilises a qualitative study design based on thematic analysis of interview data. The service evaluation consists of the development of a clinical safety case based on document analysis, analysis of the AI model and its development process and informal interviews with the technology developer.

Conclusions: AI presents many opportunities for ambulance services, but safety assurance requirements need to be understood. The ASSIST project will continue to explore and build the body of knowledge in this area.

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