Lawrence Katharine, Kuram Vasudev S, Levine Defne L, Sharif Sarah, Polet Conner, Malhotra Kiran, Owens Kellie
Department of Population Health, New York University Grossman School of Medicine, New York.
Department of Health Informatics, Medical Center Information Technology, NYU Langone, New York, New York.
JAMA Netw Open. 2025 Jul 1;8(7):e2522400. doi: 10.1001/jamanetworkopen.2025.22400.
Artificial intelligence (AI)-assisted ambient documentation technologies that use audio from clinic visits to generate documentation are being deployed across hospital systems to optimize clinical note writing and reduce administrative burden. However, little is known about optimal approaches to engage patients in informed consent for these tools.
To explore clinician and patient experiences with consent processes and examine the association between the use of ambient documentation tools and the patient-clinician relationship.
DESIGN, SETTING, AND PARTICIPANTS: This study was conducted from March 1 to December 31, 2024, in ambulatory practices across specialties in a large urban academic health center as part of an ongoing operational quality improvement initiative. Participants included clinicians and patients participating in an operational proof-of-concept exploration of ambient documentation technology.
A pragmatic, sequential, inductive-deductive qualitative evaluation was conducted of informed consent contexts, processes, and challenges among ambulatory clinicians and patients exposed to ambient documentation technology. Evaluation included site visits, clinical observations, clinician interviews, and patient surveys to explore perceptions and challenges related to consent.
A total of 121 ambient documentation pilot users included 18 clinicians (mean [SD] years of practice, 18.6 [100]; 10 men [55.6%]) and 103 patients (mean [SD] age, 37 [12.5] years; 65 women [63.1%]). The most common consent approach was a verbal patient-clinician conversation prior to an individual encounter. Patients and clinicians had a spectrum of comfort with ambient technology; 77 patients (74.8%) reported being comfortable or very comfortable with their physician using ambient documentation. Patient trust, detail in the consent discussion, and intended tool use were associated with patient comfort and intent to consent. Technical understanding was associated with comfort with consent conversations: when provided basic information about the technology, 84 patients (81.6%) consented; this decreased to 57 patients (55.3%) when details about AI features, data storage, and corporate involvement were disclosed. Perceived benefits included reduced documentation burden, improved decision-making, and enhanced communication. Concerns included data security, legal liability, cognitive impacts, and equity. When asked about responsibility for medical errors linked to ambient documentation, 66 patients (64.1%) held physicians accountable; for data security breaches, 79 patients (76.7%) believed vendors should be responsible. Participants suggested a flexible consent model with digital touchpoints, education, nonclinical staff support, and opt-out options.
In this quality improvement study of 121 pilot users of AI-assisted ambient documentation technology, informed consent relied primarily on verbal conversations that varied based on time, knowledge, and the patient-clinician relationship. A flexible, multimodal approach-including education, time to discuss risks and benefits, digital resources, nonclinical staff involvement, and clear opt-out options-may improve consent processes and support broader acceptance of ambient documentation tools.
利用门诊就诊音频生成文档的人工智能（AI）辅助环境记录技术正在医院系统中广泛应用，以优化临床记录撰写并减轻行政负担。然而，对于让患者参与这些工具的知情同意的最佳方法，我们知之甚少。
探讨临床医生和患者在同意过程中的体验，并研究环境记录工具的使用与医患关系之间的关联。
设计、背景和参与者：本研究于2024年3月1日至12月31日在一家大型城市学术医疗中心的各专科门诊进行，是一项正在进行的运营质量改进计划的一部分。参与者包括参与环境记录技术运营概念验证探索的临床医生和患者。
对接触环境记录技术的门诊临床医生和患者的知情同意背景、过程和挑战进行了务实、循序渐进、归纳 - 演绎的定性评估。评估包括实地考察、临床观察、临床医生访谈和患者调查，以探讨与同意相关的看法和挑战。
共有121名环境记录试点用户，其中包括18名临床医生（平均[标准差]执业年限，18.6[10.0]年；10名男性[55.6%]）和103名患者（平均[标准差]年龄，37[12.5]岁；65名女性[63.1%]）。最常见的同意方式是在个体就诊前进行医患口头交谈。患者和临床医生对环境技术的接受程度各不相同；77名患者（74.8%）表示对医生使用环境记录感到舒适或非常舒适。患者信任、同意讨论中的细节以及预期的工具使用与患者的舒适度和同意意愿相关。技术理解与同意交谈的舒适度相关：当提供有关该技术的基本信息时，84名患者（81.6%）同意；当披露有关AI功能、数据存储和公司参与的细节时，这一比例降至57名患者（55.3%）。感知到的好处包括减轻记录负担、改善决策和加强沟通。担忧包括数据安全、法律责任、认知影响和公平性。当被问及与环境记录相关的医疗错误责任时，66名患者（64.1%）认为医生应承担责任；对于数据安全漏洞，79名患者（76.7%）认为供应商应承担责任。参与者建议采用一种灵活的同意模式，包括数字接触点、教育、非临床工作人员支持和退出选项。
在这项对121名AI辅助环境记录技术试点用户的质量改进研究中，知情同意主要依赖于口头交谈，这些交谈因时间、知识和医患关系而异。一种灵活的多模式方法，包括教育、讨论风险和益处的时间、数字资源、非临床工作人员参与以及明确的退出选项，可能会改善同意过程并支持更广泛地接受环境记录工具。
