Faculty Bibliography

IMPORTANCE: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. OBJECTIVES: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. MAIN OUTCOMES AND MEASURES: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. RESULTS: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. CONCLUSIONS AND RELEVANCE: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.

INTRODUCTION:As the utility of genomic sequencing increases, its use in healthcare will continue to expand beyond expert clinics toward nonspecialist practices such as primary care. At the same time, discordance in genetic variant identification and classification between laboratories remains a concern for the field. This research assesses how clinicians with and without genetics expertise understand and trust genetic test results, underscoring how variation in the handling of genetic test results can have real impact on patient care. METHODS:We conducted 40 interviews with genetics experts, including clinical geneticists and genetic counselors, and nonexpert clinicians including primary care providers and cardiologists. RESULTS:Clinical geneticists and genetic counselors reported spending significant time assessing the validity of results from genetic testing laboratories, conversing with laboratories about those results, and potentially reinterpreting results. Conversely, primary care providers and cardiologists without specific genetics expertise reported high levels of trust in laboratory accuracy and variant interpretation, and did not reassess results. CONCLUSION:We find significant variation in how genetics experts and nonexperts understand the trustworthiness of genetic laboratory reports. This variation could lead to differences in patient care between clinical settings and requires additional guidance for clinicians regarding the handling of genetic test results.

Research institutions often lack policies addressing the risks and benefits of enrolling "invested parties" such as investigators, research staff, and patient, caregiver, and community representatives (groups most affected by a disease or intervention) in studies where they have direct involvement. Invested parties may have both strong motivations to study the condition or intervention and to participate as study subjects. More guidance is needed to promote appropriate access to research participation and mitigate potential risks. This article addresses the gap in guidance by presenting an ethical framework and practical guidelines for the enrollment of invested parties. Drawing from experiences with the Researching COVID to Enhance Recovery (RECOVER) Initiative, a large multisite observational cohort study, we argue that invested parties should not be categorically excluded from enrollment in their own research studies if certain criteria are met and appropriate safeguards are in place. We underscore the need to balance inclusion with fairness, promote valid voluntary informed consent, ensure data privacy, protect scientific validity, and mitigate unique risks to invested parties as participants. Additionally, we recommend regular reporting and empirical assessment to evaluate the impact of enrolling invested parties on participants and study outcomes.

Harms and risks to groups and third-parties can be significant in the context of research, particularly in data-centric studies involving genomic, artificial intelligence, and/or machine learning technologies. This article explores whether and how United States federal regulations should be adapted to better align with current ethical thinking and protect group interests. Three aspects of the Common Rule deserve attention and reconsideration with respect to group interests: institutional review board (IRB) assessment of the risks/benefits of research; disclosure requirements in the informed consent process; and criteria for waivers of informed consent. In accordance with respect for persons and communities, investigators and IRBs should systematically consider potential group harm when designing and reviewing protocols, respectively. Research participants should be informed about any potential group harm in the consent process. We call for additional public discussion, empirical research, and normative analysis on these issues to determine the right regulatory and policy path forward.

Abstract In Tyranny of the Gene: Personalized Medicine and Its Threat to Public Health (Knopf, 2023), James Tabery traces the ascendance of personalized or precision medicine in America, arguing that America's emphasis on genetics offers more hype than transformational power. In his examination of the power struggles, social relationships, and technological advances that centered the gene in American health policy, Tabery demonstrates how an intensive focus on genetics draws attention away from both the fundamental causes of health disparities and more-effective changes that could be made to developmental, physical, and social environments. American policy-makers, health care institutions, funders, and bioethicists should not let the technological shine and attractive politics of personalized medicine continue to replace the hard but necessary work of addressing sociopolitical causes of disease and illness.

Over the last decade, the concept of actionability has become a primary framework for assessing whether genetic data is useful and appropriate to return to patients. Despite the popularity of this concept, there is little consensus about what should count as "actionable" information. This is particularly true in population genomic screening, where there is considerable disagreement about what counts as good evidence and which clinical actions are appropriate for which patients. The pathway from scientific evidence to clinical action is not straightforward-it is as much social and political as it is scientific. This research explores the social dynamics shaping the integration of "actionable" genomic data into primary care settings. Based on semi-structured interviews with 35 genetics experts and primary care providers, we find that clinicians vary in how they define and operationalize "actionable" information. There are two main sources of disagreement. First, clinicians differ on the levels and types of evidence required for a result to be actionable, such as when we can be confident that genomic data provides accurate information. Second, there are disagreements about the clinical actions that must be available so that patients can benefit from that information. By highlighting the underlying values and assumptions embedded in discussions of actionability for genomic screening, we provide an empirical basis for building more nuanced policies regarding the actionability of genomic data in terms of population screening in primary care settings.