Informed Consent for Ambient Documentation Using Generative AI in Ambulatory Care.

Abstract

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. 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.