Clinician voices on ethics of LLM integration in healthcare: a thematic analysis of ethical concerns and implications.

OBJECTIVES: This study aimed to explain and categorize key ethical concerns about integrating large language models (LLMs) in healthcare, drawing particularly from the perspectives of clinicians in online discussions. MATERIALS AND METHODS: We analyzed 3049 posts and comments extracted from a self-identified clinician subreddit using unsupervised machine learning via Latent Dirichlet Allocation and a structured qualitative analysis methodology. RESULTS: Analysis uncovered 14 salient themes of ethical implications, which we further consolidated into 4 overarching domains reflecting ethical issues around various clinical applications of LLM in healthcare, LLM coding, algorithm, and data governance, LLM's role in health equity and the distribution of public health services, and the relationship between users (human) and LLM systems (machine). DISCUSSION: Mapping themes to ethical frameworks in literature illustrated multifaceted issues covering transparent LLM decisions, fairness, privacy, access disparities, user experiences, and reliability. CONCLUSION: This study emphasizes the need for ongoing ethical review from stakeholders to ensure responsible innovation and advocates for tailored governance to enhance LLM use in healthcare, aiming to improve clinical outcomes ethically and effectively.

What Are Epidemiological Foundations for Integrating Legal Services Into Health Care Settings?

Medical-legal partnerships vary widely in how they are structured and use data to inform service delivery. Epidemiological data on certain chronic conditions' prevalence, the incidence of potentially preventable morbidity, and health-harming legal factors also influence approaches to care. This article draws on a pediatric example of how data-driven medical care complements data-driven legal care. This article also considers medical and public health ethical frameworks to guide protected information sharing, promote optimal service delivery, and achieve the best possible medical-legal outcomes.

AI ethics in healthcare.

Artificial Intelligence (AI) holds promise in improving diagnostics and treatment. Likewise, AI is anticipated to mitigate the impacts of staff shortages in the healthcare sector. However, realising the expectations placed on AI requires a substantial effort involving patients and clinical domain experts. Against this setting, this review examines ethical challenges related to the development and implementation of AI in healthcare. Furthermore, we introduce and discuss various approaches, guidelines, and standards that proactively aim to address ethical challenges.

Conscience, Caricatures, and Catholic Identities.

Catholic health care is often viewed as antithetical to secular conceptions of autonomy. This view can engender calls to protect "choice" in Catholic facilities. However, this view is built on a fundamental misunderstanding of the Ethical and Religious Directives for Catholic Health Care Services (ERDs). This commentary, which responds to "Principled Conscientious Provision: Referral Symmetry and Its Implications for Protecting Secular Conscience," by Abram Brummett et al., seeks to demonstrate the nuance of the ERDs as well as to address some of the challenges various Catholic identities have when interpreting and living out the ERDs so that all patients receive high-quality, compassionate care. By highlighting the Church's desire to protect all people at every stage, I hope to dispel the caricatures that often result from misunderstandings by Catholics and non-Catholics alike.

KPHA 2023 should explicitly include state accountability: Response to Fernandez et al.

The commentary "Public health ethics and the Kerala Public Health Act, 2023" published on January 27, 2024 in the Indian Journal of Medical Ethics (IJME) has received a response from members of the State Health Systems Resource Centre and Government Medical College, Malappuram, Kerala. They explain that the Kerala Public Health Act (KPHA) is a legal document and not required to explicitly include accountability mechanisms and social obligations of the state. Given the very real danger of state over-reach as was evident during the Covid pandemic, these checks and balances should, in fact, be non-negotiable. The position of KPHA on healthcare of migrant workers and patients with tuberculosis goes against existing public healthcare principles. There is therefore a need to revisit the Act to explicitly include state accountability.

Under siege: The role of settler colonialism in targeting healthcare systems.

This article looks at the effects of armed conflict on healthcare systems in Gaza at the intersection of international humanitarian aid, settler colonialism and the ethics of war. Since October 7, 2023, there has been a systemic assault on the health services in Gaza, rooted in colonial expansion. I begin with an overview of human rights and the concept of medical neutrality. This is followed by biopolitics within Gaza and the contradictions in international law regarding the ethics of war. Explained through the lens of historical revisionism, postcolonial theory and biopolitics, I attempt to highlight how healthcare systems are increasingly becoming targets of armed conflict in Gaza as a war strategy.

Responsibility Gap(s) Due to the Introduction of AI in Healthcare: An Ubuntu-Inspired Approach.

Due to its enormous potential, artificial intelligence (AI) can transform healthcare on a seemingly infinite scale. However, as we continue to explore the immense potential of AI, it is vital to consider the ethical concerns associated with its development and deployment. One specific concern that has been flagged in the literature is the responsibility gap (RG) due to the introduction of AI in healthcare. When the use of an AI algorithm or system results in a negative outcome for a patient(s), to whom can or should responsibility for that outcome be assigned? Although the concept of the RG was introduced in Anglo-American and European philosophy, this paper aims to broaden the debate by providing an Ubuntu-inspired perspective on the RG. Ubuntu, deeply rooted in African philosophy, calls for collective responsibility, and offers a uniquely forward-looking approach to address the alleged RG caused by AI in healthcare. An Ubuntu-inspired perspective can serve as a valuable guide and tool when addressing the alleged RG. Incorporating Ubuntu into the AI ethics discourse can contribute to a more ethical and responsible integration of AI in healthcare.

The Integration of Clinical Trials With the Practice of Medicine: Repairing a House Divided.

Importance: Optimal health care delivery, both now and in the future, requires a continuous loop of knowledge generation, dissemination, and uptake on how best to provide care, not just determining what interventions work but also how best to ensure they are provided to those who need them. The randomized clinical trial (RCT) is the most rigorous instrument to determine what works in health care. However, major issues with both the clinical trials enterprise and the lack of integration of clinical trials with health care delivery compromise medicine's ability to best serve society. Observations: In most resource-rich countries, the clinical trials and health care delivery enterprises function as separate entities, with siloed goals, infrastructure, and incentives. Consequently, RCTs are often poorly relevant and responsive to the needs of patients and those responsible for care delivery. At the same time, health care delivery systems are often disengaged from clinical trials and fail to rapidly incorporate knowledge generated from RCTs into practice. Though longstanding, these issues are more pressing given the lessons learned from the COVID-19 pandemic, heightened awareness of the disproportionate impact of poor access to optimal care on vulnerable populations, and the unprecedented opportunity for improvement offered by the digital revolution in health care. Four major areas must be improved. First, especially in the US, greater clarity is required to ensure appropriate regulation and oversight of implementation science, quality improvement, embedded clinical trials, and learning health systems. Second, greater adoption is required of study designs that improve statistical and logistical efficiency and lower the burden on participants and clinicians, allowing trials to be smarter, safer, and faster. Third, RCTs could be considerably more responsive and efficient if they were better integrated with electronic health records. However, this advance first requires greater adoption of standards and processes designed to ensure health data are adequately reliable and accurate and capable of being transferred responsibly and efficiently across platforms and organizations. Fourth, tackling the problems described above requires alignment of stakeholders in the clinical trials and health care delivery enterprises through financial and nonfinancial incentives, which could be enabled by new legislation. Solutions exist for each of these problems, and there are examples of success for each, but there is a failure to implement at adequate scale. Conclusions and Relevance: The gulf between current care and that which could be delivered has arguably never been wider. A key contributor is that the 2 limbs of knowledge generation and implementation-the clinical trials and health care delivery enterprises-operate as a house divided. Better integration of these 2 worlds is key to accelerated improvement in health care delivery.

AI Through Ethical Lenses: A Discourse Analysis of Guidelines for AI in Healthcare.

While the technologies that enable Artificial Intelligence (AI) continue to advance rapidly, there are increasing promises regarding AI's beneficial outputs and concerns about the challenges of human-computer interaction in healthcare. To address these concerns, institutions have increasingly resorted to publishing AI guidelines for healthcare, aiming to align AI with ethical practices. However, guidelines as a form of written language can be analyzed to recognize the reciprocal links between its textual communication and underlying societal ideas. From this perspective, we conducted a discourse analysis to understand how these guidelines construct, articulate, and frame ethics for AI in healthcare. We included eight guidelines and identified three prevalent and interwoven discourses: (1) AI is unavoidable and desirable; (2) AI needs to be guided with (some forms of) principles (3) trust in AI is instrumental and primary. These discourses signal an over-spillage of technical ideals to AI ethics, such as over-optimism and resulting hyper-criticism. This research provides insights into the underlying ideas present in AI guidelines and how guidelines influence the practice and alignment of AI with ethical, legal, and societal values expected to shape AI in healthcare.

A critical and systematic literature review of epistemic justice applied to healthcare: recommendations for a patient partnership approach.

Invalidation from healthcare practitioners is an experience shared by many patients, especially those marginalized or living with contested conditions (e.g., chronic pain, fibromyalgia, etc.). Invalidation can include not taking someone's testimony seriously, imposing one's thoughts, discrediting someone's emotions, or not perceiving someone's testimony as equal and competent. Epistemic injustices, that is, the disqualification of a person as a knower, are a form of invalidation. Epistemic injustices have been used as a theoretical framework to understand invalidation that occurs in the patient-healthcare provider relationship. However, to date, the different recommendations to achieve epistemic justice have not been listed, analyzed, nor compared yet. This paper aims at better understanding the state of the literature and to critically review possible avenues to achieve epistemic justice in healthcare. A systematic and critical review of the existing literature on epistemic justice was conducted. The search in four databases identified 629 articles, from which 35 were included in the review. Strategies to promote epistemic justice that can be applied to healthcare are mapped in the literature and sorted in six different approaches to epistemic justice, including virtuous, structural, narrative, cognitive, and partnership approaches, as well as resistance strategies. These strategies are critically appraised. A patient partnership approach based on the Montreal Model, implemented at all levels of healthcare systems, seems promising to promote epistemic justice in healthcare.