人工智能和急救部门的定性分析 远程心理健康护理实施调查
Cameron Keating1, Steven C Marcus2,3, Cadence F Bowden1
1Division of General Pediatrics, Clinical Futures, and PolicyLab, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
概括
紧急部门 (ED) 需要更快地获得基本医疗保健. 人工智能 (AI) 帮助进行了定性分析,确定了改善心理健康服务和远程医疗效率的关键建议.
科学领域:
- 紧急医疗 紧急医疗
- 心理健康服务 心理健康服务
- 医疗信息学 医疗信息学
背景情况:
- 在美国的急诊室 (EDs) 中,远程精神健康护理的实施正在增加.
- 人工智能 (AI) 在增强定性研究方面的效率和准确性仍未得到充分探索.
- 了解ED主任的观点对于加强远程医疗保健服务至关重要.
研究的目的:
- 收集ED主任的定性建议,以改善基本医疗保健的实施.
- 评估AI在分析医疗保健研究的定性调查数据中的实用性.
- 将人工智能辅助的定性分析与传统方法进行比较.
主要方法:
- 对279名美国ED主管进行了关于远程医疗保健实施的全国调查 (2022年6月至2023年10月).
- 两个独立的研究小组对开放式响应进行了定性编码:一个是传统的,一个是人工智能辅助的 (ChatGPT 4.0).
- 开发一个共识代码书,并比较方法之间的编码一致性和主题识别.
主要成果:
- 确定了关键主题:对远程医疗保健的直接改进和更广泛的心理健康系统改进.
- 最常见的建议侧重于实现更快,更简单地获得远程基本卫生服务.
- 人工智能发现了人类编码者错过的两个额外的有效代码,并与人类分析师实现了75%的编码一致性.
结论:
- 美国ED需要在获得基本医疗保健方面提高及时性和效率.
- 人工智能显示出作为一种有价值的工具,在医疗保健环境中增强定性研究的潜力.
- 整合人工智能可以提高对医疗保健改进策略的定性数据分析的深度和效率.
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