Keating Cameron, Marcus Steven C, Bowden Cadence F, Worsley Diana, Doupnik Stephanie K
Division of General Pediatrics, Clinical Futures, and PolicyLab, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Telemed J E Health. 2025 Jul;31(7):821-828. doi: 10.1089/tmj.2024.0555. Epub 2025 Mar 24.
: Implementation of telemental health care in emergency departments (EDs) in the United States (U.S.) has been increasing. Artificial intelligence (AI) can augment traditional qualitative research methods; little is known about its efficiency and accuracy. This study sought to understand ED directors' qualitative recommendations for improving telemental health care implementation and to understand how AI could facilitate analysis of qualitative survey responses. : Directors at a nationally representative sample of 279 U.S. EDs that used telemental health care completed an open-ended survey question about improving telemental health care implementation between June 2022 and October 2023. Two groups of researchers completed independent qualitative coding of responses: one group used traditional qualitative methods, and one group used AI (ChatGPT 4.0) to facilitate analysis. Both groups independently developed a codebook, came to consensus on a combined codebook, and each group independently used it to code the survey responses. The two groups identified themes in ED directors' recommendations and compared codebooks and code application across traditional and AI approaches. : Themes included (1) recommendations for improving telemental health care directly and (2) recommendations for improving mental health care systems broadly to make telehealth more effective. ED directors' most common recommendation was enabling faster and more streamlined access to telemental health care. AI augmented human coding by identifying two valid codes not initially identified by human analysts. In codebook application, 75% of responses were coded consistently across AI and human coders. : For US EDs using telemental health care, there is a need to improve timeliness and efficiency of access to telemental health care.
美国急诊科远程心理健康护理的实施一直在增加。人工智能(AI)可以增强传统的定性研究方法;但其效率和准确性鲜为人知。本研究旨在了解急诊科主任对改善远程心理健康护理实施的定性建议,并了解人工智能如何促进对定性调查回复的分析。
对279家使用远程心理健康护理的美国急诊科进行全国代表性抽样,这些急诊科的主任在2022年6月至2023年10月期间完成了一项关于改善远程心理健康护理实施的开放式调查问题。两组研究人员对回复进行了独立的定性编码:一组使用传统定性方法,另一组使用人工智能(ChatGPT 4.0)来促进分析。两组都独立制定了编码手册,就合并后的编码手册达成共识,并且每组都独立使用它对调查回复进行编码。两组在急诊科主任的建议中确定了主题,并比较了传统方法和人工智能方法的编码手册及编码应用。
(1)直接改善远程心理健康护理的建议,以及(2)广泛改善心理健康护理系统以使远程医疗更有效的建议。急诊科主任最常见的建议是实现更快、更简化的远程心理健康护理获取途径。人工智能通过识别出人类分析人员最初未识别的两个有效编码,增强了人工编码。在编码手册应用方面,75%的回复在人工智能和人工编码人员之间得到了一致编码。
对于使用远程心理健康护理的美国急诊科而言,有必要提高获取远程心理健康护理的及时性和效率。