Department of Epidemiology and Preventive Medicine, Medical Sociology, University of Regensburg, Regensburg, Germany
Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Corporate Member of Free University of Berlin, Berlin Institute of Health, Humboldt-University of Berlin, Berlin, Germany.
BMJ Open. 2024 Oct 1;14(10):e081318. doi: 10.1136/bmjopen-2023-081318.
As healthcare is shifting from a paternalistic to a patient-centred approach, medical decision making becomes more collaborative involving patients, their support persons (SPs) and physicians. Implementing shared decision-making (SDM) into clinical practice can be challenging and becomes even more complex with the introduction of artificial intelligence (AI) as a potential actant in the communicative network. Although there is more empirical research on patients' and physicians' perceptions of AI, little is known about the impact of AI on SDM. This study will help to fill this gap. To the best of our knowledge, this is the first systematic empirical investigation to prospectively assess the views of patients, their SPs and physicians on how AI affects SDM in physician-patient communication after kidney transplantation. Using a transdisciplinary approach, this study will explore the role and impact of an AI-decision support system (DSS) designed to assist with medical decision making in the clinical encounter.
This is a plan to roll out a 2 year, longitudinal qualitative interview study in a German kidney transplant centre. Semi-structured interviews with patients, SPs and physicians will be conducted at baseline and in 3-, 6-, 12- and 24-month follow-up. A total of 50 patient-SP dyads and their treating physicians will be recruited at baseline. Assuming a dropout rate of 20% per year, it is anticipated that 30 patient-SP dyads will be included in the last follow-up with the aim of achieving data saturation. Interviews will be audio-recorded and transcribed verbatim. Transcripts will be analysed using framework analysis. Participants will be asked to report on their (a) communication experiences and preferences, (b) views on the influence of the AI-based DSS on the normative foundations of the use of AI in medical decision-making, focusing on agency along with trustworthiness, transparency and responsibility and (c) perceptions of the use of the AI-based DSS, as well as barriers and facilitators to its implementation into routine care.
Approval has been granted by the local ethics committee of Charité-Universitätsmedizin Berlin (EA1/177/23 on 08 August 2023). This research will be conducted in accordance with the principles of the Declaration of Helsinki (1996). The study findings will be used to develop communication guidance for physicians on how to introduce and sustainably implement AI-assisted SDM. The study results will also be used to develop lay language patient information on AI-assisted SDM. A broad dissemination strategy will help communicate the results of this research to a variety of target groups, including scientific and non-scientific audiences, to allow for a more informed discourse among different actors from policy, science and society on the role and impact of AI in physician-patient communication.
随着医疗保健从家长式作风向以患者为中心的方法转变,医学决策变得更加协作,涉及患者、他们的支持人员 (SPs) 和医生。将共同决策 (SDM) 实施到临床实践中可能具有挑战性,并且随着人工智能 (AI) 作为沟通网络中的潜在行动者的引入,情况变得更加复杂。尽管已经有更多关于患者和医生对人工智能感知的实证研究,但对于人工智能对 SDM 的影响知之甚少。这项研究将有助于填补这一空白。据我们所知,这是第一项系统的实证研究,旨在前瞻性评估患者、他们的 SPs 和医生对 AI 在肾移植后医患沟通中如何影响 SDM 的看法。本研究将采用跨学科方法,探索旨在协助临床就诊中医疗决策的人工智能决策支持系统 (DSS) 的作用和影响。
这是一项在德国肾移植中心开展为期 2 年的纵向定性访谈研究的计划。将在基线以及 3、6、12 和 24 个月的随访时对患者、SP 和医生进行半结构化访谈。基线时将招募 50 对患者-SP 二人组及其治疗医生。假设每年 20%的流失率,预计最后一次随访将有 30 对患者-SP 二人组参与,目的是实现数据饱和。访谈将进行录音并逐字记录。将使用框架分析对记录进行分析。参与者将被要求报告他们的 (a) 沟通体验和偏好,(b) 对基于人工智能的 DSS 对医疗决策中使用人工智能的规范性基础的影响的看法,重点关注代理机构以及可信度、透明度和责任,以及 (c) 对基于人工智能的 DSS 的看法,以及将其实施到常规护理中的障碍和促进因素。
当地伦理委员会 Charité-Universitätsmedizin Berlin(2023 年 8 月 8 日的 EA1/177/23)已批准该研究。本研究将遵循《赫尔辛基宣言》(1996 年)的原则进行。研究结果将用于为医生制定关于如何引入和可持续实施 AI 辅助 SDM 的沟通指南。研究结果还将用于制定关于 AI 辅助 SDM 的通俗易懂的患者信息。广泛的传播策略将有助于向各种目标群体传达这项研究的结果,包括科学和非科学受众,以便在政策、科学和社会的不同行为者之间就 AI 在医患沟通中的作用和影响进行更具信息性的讨论。