Patient Consent and The Right to Notice and Explanation of AI Systems Used in Health Care.

Given the need for enforceable guardrails for artificial intelligence (AI) that protect the public and allow for innovation, the U.S. Government recently issued a Blueprint for an AI Bill of Rights which outlines five principles of safe AI design, use, and implementation. One in particular, the right to notice and explanation, requires accurately informing the public about the use of AI that impacts them in ways that are easy to understand. Yet, in the healthcare setting, it is unclear what goal the right to notice and explanation serves, and the moral importance of patient-level disclosure. We propose three normative functions of this right: (1) to notify patients about their care, (2) to educate patients and promote trust, and (3) to meet standards for informed consent. Additional clarity is needed to guide practices that respect the right to notice and explanation of AI in healthcare while providing meaningful benefits to patients.

Adolescent OCD Patient and Caregiver Perspectives on Identity, Authenticity, and Normalcy in Potential Deep Brain Stimulation Treatment.

The ongoing debate within neuroethics concerning the degree to which neuromodulation such as deep brain stimulation (DBS) changes the personality, identity, and agency (PIA) of patients has paid relatively little attention to the perspectives of prospective patients. Even less attention has been given to pediatric populations. To understand patients' views about identity changes due to DBS in obsessive-compulsive disorder (OCD), the authors conducted and analyzed semistructured interviews with adolescent patients with OCD and their parents/caregivers. Patients were asked about projected impacts to PIA generally due to DBS. All patient respondents and half of caregivers reported that DBS would impact patient self-identity in significant ways. For example, many patients expressed how DBS could positively impact identity by allowing them to explore their identities free from OCD. Others voiced concerns that DBS-related resolution of OCD might negatively impact patient agency and authenticity. Half of patients expressed that DBS may positively facilitate social access through relieving symptoms, while half indicated that DBS could increase social stigma. These views give insights into how to approach decision-making and informed consent if DBS for OCD becomes available for adolescents. They also offer insights into adolescent experiences of disability identity and "normalcy" in the context of OCD.

Trust criteria for artificial intelligence in health: normative and epistemic considerations.

Rapid advancements in artificial intelligence and machine learning (AI/ML) in healthcare raise pressing questions about how much users should trust AI/ML systems, particularly for high stakes clinical decision-making. Ensuring that user trust is properly calibrated to a tool's computational capacities and limitations has both practical and ethical implications, given that overtrust or undertrust can influence over-reliance or under-reliance on algorithmic tools, with significant implications for patient safety and health outcomes. It is, thus, important to better understand how variability in trust criteria across stakeholders, settings, tools and use cases may influence approaches to using AI/ML tools in real settings. As part of a 5-year, multi-institutional Agency for Health Care Research and Quality-funded study, we identify trust criteria for a survival prediction algorithm intended to support clinical decision-making for left ventricular assist device therapy, using semistructured interviews (n=40) with patients and physicians, analysed via thematic analysis. Findings suggest that physicians and patients share similar empirical considerations for trust, which were primarily epistemic in nature, focused on accuracy and validity of AI/ML estimates. Trust evaluations considered the nature, integrity and relevance of training data rather than the computational nature of algorithms themselves, suggesting a need to distinguish 'source' from 'functional' explainability. To a lesser extent, trust criteria were also relational (endorsement from others) and sometimes based on personal beliefs and experience. We discuss implications for promoting appropriate and responsible trust calibration for clinical decision-making use AI/ML.

Deep Brain Stimulation for Pediatric Dystonia: Clinicians' Perspectives on the Most Pressing Ethical Challenges.

INTRODUCTION: Pediatric deep brain stimulation (pDBS) is commonly used to manage treatment-resistant primary dystonias with favorable results and more frequently used for secondary dystonia to improve quality of life. There has been little systematic empirical neuroethics research to identify ethical challenges and potential solutions to ensure responsible use of DBS in pediatric populations. METHODS: Clinicians (n = 29) who care for minors with treatment-resistant dystonia were interviewed for their perspectives on the most pressing ethical issues in pDBS. RESULTS: Using thematic content analysis to explore salient themes, clinicians identified four pressing concerns: (1) uncertainty about risks and benefits of pDBS (22/29; 72%) that poses a challenge to informed decision-making; (2) ethically navigating decision-making roles (15/29; 52%), including how best to integrate perspectives from diverse stakeholders (patient, caregiver, clinician) and how to manage surrogate decisions on behalf of pediatric patients with limited capacity to make autonomous decisions; (3) information scarcity effects on informed consent and decision quality (15/29; 52%) in the context of patient and caregivers' expectations for treatment; and (4) narrow regulatory status and access (7/29; 24%) such as the lack of FDA-approved indications that contribute to decision-making uncertainty and liability and potentially limit access to DBS among patients who may benefit from it. CONCLUSION: These results suggest that clinicians are primarily concerned about ethical limitations of making difficult decisions in the absence of informational, regulatory, and financial supports. We discuss two solutions already underway, including supported decision-making to address uncertainty and further data sharing to enhance clinical knowledge and discovery.

Ethics Education for Healthcare Professionals in the Era of ChatGPT and Other Large Language Models: Do We Still Need It?

In this paper, we contend with whether we still need traditional ethics education as part of healthcare professional training given the abilities of chatGPT (generative pre-trained transformer) and other large language models (LLM). We reflect on common programmatic goals to assess the current strengths and limitations of LLMs in helping to build ethics competencies among future clinicians. Through an actual case analysis, we highlight areas in which chatGPT and other LLMs are conducive to common bioethics education goals. We also comment on where such technologies remain an imperfect substitute for human-led ethics teaching and learning. Finally, we conclude that the relative strengths of chatGPT warrant its consideration as a teaching and learning tool in ethics education in ways that account for current limitations and build in flexibility as the technology evolves.

A Call for Behavioral Science in Embedded Bioethics.

Bioethicists today are taking a greater role in the design and implementation of emerging technologies by "embedding" within the development teams and providing their direct guidance and recommendations. Ideally, these collaborations allow ethical considerations to be addressed in an active, iterative, and ongoing process through regular exchanges between ethicists and members of the technological development team. This article discusses a challenge to this embedded ethics approach-namely, that bioethical guidance, even if embraced by the development team in theory, is not easily actionable in situ. Many of the ethical problems at issue in emerging technologies are associated with preexisting structural, socioeconomic, and political factors, making compliance with ethical recommendations sometimes less a matter of choice and more a matter of feasibility. Moreover, incentive structures within these systemic factors maintain them against reform efforts. The authors recommend that embedded bioethicists utilize principles from behavioral science (such as behavioral economics) to better understand and account for these incentive structures so as to encourage the ethically responsible uptake of technological innovations.

Impact of personalized risk scores on shared decision making in left ventricular assist device implantation: Findings from a qualitative study.

OBJECTIVE: To assess stakeholders' perspectives on integrating personalized risk scores (PRS) into left ventricular assist device (LVAD) implantation decisions and how these perspectives might impact shared decision making (SDM). METHODS: We conducted 40 in-depth interviews with physicians, nurse coordinators, patients, and caregivers about integrating PRS into LVAD implantation decisions. A codebook was developed to identify thematic patterns, and quotations were consolidated for analysis. We used Thematic Content Analysis in MAXQDA software to identify themes by abstracting relevant quotes. RESULTS: Clinicians had varying preferences regarding PRS integration into LVAD decision making, while patients and caregivers preferred real-time discussions about PRS with their physicians. Physicians voiced concerns about time constraints and suggested delegating PRS discussions to advanced practice providers or nurse coordinators. CONCLUSIONS: Integrating PRS information into LVAD decision aids presents both opportunities and challenges for SDM. Given variable preferences among clinicians and patients, clinicians should elicit patients' desired role in the decision-making process. Addressing time constraints and ensuring patient-centered care will be crucial for optimizing SDM. Practice implications Clinicians should elicit patient preferences for PRS information disclosure and address challenges, such as time constraints and delegation of PRS discussions to other team members.

Ethical considerations for integrating multimodal computer perception and neurotechnology.

Background: Artificial intelligence (AI)-based computer perception technologies (e.g., digital phenotyping and affective computing) promise to transform clinical approaches to personalized care in psychiatry and beyond by offering more objective measures of emotional states and behavior, enabling precision treatment, diagnosis, and symptom monitoring. At the same time, passive and continuous nature by which they often collect data from patients in non-clinical settings raises ethical issues related to privacy and self-determination. Little is known about how such concerns may be exacerbated by the integration of neural data, as parallel advances in computer perception, AI, and neurotechnology enable new insights into subjective states. Here, we present findings from a multi-site NCATS-funded study of ethical considerations for translating computer perception into clinical care and contextualize them within the neuroethics and neurorights literatures. Methods: We conducted qualitative interviews with patients (n = 20), caregivers (n = 20), clinicians (n = 12), developers (n = 12), and clinician developers (n = 2) regarding their perspective toward using PC in clinical care. Transcripts were analyzed in MAXQDA using Thematic Content Analysis. Results: Stakeholder groups voiced concerns related to (1) perceived invasiveness of passive and continuous data collection in private settings; (2) data protection and security and the potential for negative downstream/future impacts on patients of unintended disclosure; and (3) ethical issues related to patients' limited versus hyper awareness of passive and continuous data collection and monitoring. Clinicians and developers highlighted that these concerns may be exacerbated by the integration of neural data with other computer perception data. Discussion: Our findings suggest that the integration of neurotechnologies with existing computer perception technologies raises novel concerns around dignity-related and other harms (e.g., stigma, discrimination) that stem from data security threats and the growing potential for reidentification of sensitive data. Further, our findings suggest that patients' awareness and preoccupation with feeling monitored via computer sensors ranges from hypo- to hyper-awareness, with either extreme accompanied by ethical concerns (consent vs. anxiety and preoccupation). These results highlight the need for systematic research into how best to implement these technologies into clinical care in ways that reduce disruption, maximize patient benefits, and mitigate long-term risks associated with the passive collection of sensitive emotional, behavioral and neural data.

Deep Brain Stimulation for Childhood Treatment-Resistant Obsessive-Compulsive Disorder: Mental Health Clinician Views on Candidacy Factors.

INTRODUCTION: Deep brain stimulation (DBS) is approved under a humanitarian device exemption to manage treatment-resistant obsessive-compulsive disorder (TR-OCD) in adults. It is possible that DBS may be trialed or used clinically off-label in children and adolescents with TR-OCD in the future. DBS is already used to manage treatment-resistant childhood dystonia. Evidence suggests it is a safe and effective intervention for certain types of dystonia. Important questions remain unanswered about the use of DBS in children and adolescents with TR-OCD, including whether mental health clinicians would refer pediatric patients for DBS, and who would be a good candidate for DBS. OBJECTIVES: To explore mental health clinicians' views on what clinical and psychosocial factors they would consider when determining which children with OCD would be good DBS candidates. MATERIALS AND METHODS: In depth, semi-structured interviews were conducted with n = 25 mental health clinicians who treat pediatric patients with OCD. The interviews were transcribed, coded, and analyzed using thematic content analysis. Three questions focused on key, clinical, and psychosocial factors for assessing candidacy were analyzed to explore respondent views on candidacy factors. Our analysis details nine overarching themes expressed by clinicians, namely the patient's previous OCD treatment, OCD severity, motivation to commit to treatment, presence of comorbid conditions, family environment, education on DBS, quality of life, accessibility to treatment, and patient age and maturity. CONCLUSIONS: Clinicians generally saw considering DBS treatment in youth as a last resort and only for very specific cases. DBS referral was predominantly viewed as acceptable for children with severe TR-OCD who have undertaken intensive, appropriate treatment without success, whose OCD has significantly reduced their quality of life, and who exhibit strong motivation to continue treatment given the right environment. Appropriate safeguards, eligibility criteria, and procedures should be discussed and identified before DBS for childhood TR-OCD becomes practice.

Patients' and physicians' beliefs and attitudes towards integrating personalized risk estimates into patient education about left ventricular assist device therapy.

BACKGROUND: Personalized risk (PR) estimates may enhance clinical decision making and risk communication by providing individualized estimates of patient outcomes. We explored stakeholder attitudes toward the utility, acceptability, usefulness and best-practices for integrating PR estimates into patient education and decision making about Left Ventricular Assist Device (LVAD). METHODS AND RESULTS: As part of a 5-year multi-institutional AHRQ project, we conducted 40 interviews with stakeholders (physicians, nurse coordinators, patients, and caregivers), analyzed using Thematic Content Analysis. All stakeholder groups voiced positive views towards integrating PR in decision making. Patients, caregivers and coordinators emphasized that PR can help to better understand a patient's condition and risks, prepare mentally and logistically for likely outcomes, and meaningfully engage in decision making. Physicians felt it can improve their decision making by enhancing insight into outcomes, enhance tailored pre-emptive care, increase confidence in decisions, and reduce bias and subjectivity. All stakeholder groups also raised concerns about accuracy, representativeness and relevance of algorithms; predictive uncertainty; utility in relation to physician's expertise; potential negative reactions among patients; and overreliance. CONCLUSION: Stakeholders are optimistic about integrating PR into clinical decision making, but acceptability depends on prospectively demonstrating accuracy, relevance and evidence that benefits of PR outweigh potential negative impacts on decision making quality.

Ethical hazards of health data governance in the metaverse.

Metaverse-enabled healthcare is no longer hypothetical. Developers must now contend with ethical, legal and social hazards if they are to overcome the systematic inefficiencies and inequities that exist for patients who seek care in the real world.

Advances in prosthetic technology: a perspective on ethical considerations for development and clinical translation.

Technological advancements of prostheses in recent years, such as haptic feedback, active power, and machine learning for prosthetic control, have opened new doors for improved functioning, satisfaction, and overall quality of life. However, little attention has been paid to ethical considerations surrounding the development and translation of prosthetic technologies into clinical practice. This article, based on current literature, presents perspectives surrounding ethical considerations from the authors' multidisciplinary views as prosthetists (HG, AM, CLM, MGF), as well as combined research experience working directly with people using prostheses (AM, CLM, MGF), wearable technologies for rehabilitation (MGF, BN), machine learning and artificial intelligence (BN, KKQ), and ethics of advanced technologies (KKQ). The target audience for this article includes developers, manufacturers, and researchers of prosthetic devices and related technology. We present several ethical considerations for current advances in prosthetic technology, as well as topics for future research, that may inform product and policy decisions and positively influence the lives of those who can benefit from advances in prosthetic technology.

Clinician Perspectives on Levels of Evidence and Oversight for Deep Brain Stimulation for Treatment-Resistant Childhood OCD.

Approximately 10-20% of children with obsessive-compulsive disorder (OCD) have treatment-resistant presentations, and there is likely interest in developing interventions for this patient group, which may include deep brain stimulation (DBS). The World Society for Stereotactic and Functional Neurosurgery has argued that at least two successful randomized controlled trials should be available before DBS treatment for a psychiatric disorder is considered "established." The FDA approved DBS for adults with treatment-resistant OCD under a humanitarian device exemption (HDE) in 2009, which requires that a device be used to manage or treat a condition impacting 8,000 or fewer patients annually in the United States. DBS is currently offered to children ages 7 and older with treatment-resistant dystonia under an HDE. Ethical and empirical work are needed to evaluate whether and under what conditions it might be appropriate to offer DBS for treatment-resistant childhood OCD. To address this gap, we report qualitative data from semi-structured interviews with 25 clinicians with expertise in this area. First, we report clinician perspectives on acceptable levels of evidence to offer DBS in this patient population. Second, we describe their perspectives on institutional policies or protocols that might be needed to effectively provide care for this patient population.

Hope and Optimism in Pediatric Deep Brain Stimulation: Key Stakeholder Perspectives.

Introduction: Deep brain stimulation (DBS) is utilized to treat pediatric refractory dystonia and its use in pediatric patients is expected to grow. One important question concerns the impact of hope and unrealistic optimism on decision-making, especially in "last resort" intervention scenarios such as DBS for refractory conditions. Objective: This study examined stakeholder experiences and perspectives on hope and unrealistic optimism in the context of decision-making about DBS for childhood dystonia and provides insights for clinicians seeking to implement effective communication strategies. Materials and Methods: Semi-structured interviews with clinicians (n = 29) and caregivers (n = 44) were conducted, transcribed, and coded. Results: Using thematic content analysis, four major themes from clinician interviews and five major themes from caregiver interviews related to hopes and expectations were identified. Clinicians expressed concerns about caregiver false hopes (86%, 25/29) and desperation (68.9%, 20/29) in light of DBS being a last resort. As a result, 68.9% of clinicians (20/29) expressed that they intentionally tried to lower caregiver expectations about DBS outcomes. Clinicians also expressed concern that, on the flip side, unrealistic pessimism drives away some patients who might otherwise benefit from DBS (34.5%, 10/29). Caregivers viewed DBS as the last option that they had to try (61.3%, 27/44), and 73% of caregivers (32/44) viewed themselves as having high hopes but reasonable expectations. Fewer than half (43%, 19/44) expressed that they struggled setting outcome expectations due to the uncertainty of DBS, and 50% of post-DBS caregivers (14/28) expressed some negative feelings post treatment due to unmet expectations. 43% of caregivers (19/44) had experiences with clinicians who tried to set low expectations about the potential benefits of DBS. Conclusion: Thoughtful clinician-stakeholder discussion is needed to ensure realistic outcome expectations.