Rethinking Patient Consent in AI-Enhanced Healthcare: A Teleological and Consequential Ethical Framework.

Biological samples—such as tissues, blood and cells—are an increasingly important tool for research into human diseases and their genetic and physiological causes. To ease their storage and access, many of these samples are now stored in biobanks. The number of human biological samples in such collections amounted to several hundred million in 1999 in the USA alone—about one sample per US citizen (Eiseman, 2000; Azarow et al , 2003)—and is increasing rapidly. Three‐quarters of the clinical trials that drug companies submit to the US Food and Drug Administration (Rockville, MD, USA) for approval now include a provision for sampling and storing human tissue for future genetic analysis (Abbott, 2003). At the same time, there is a boom of population biobanks, as more and more countries establish new sample collections (Kaiser, 2002). Among the best known are: the Icelandic Health Sector Database; the Estonian Genome Project; the UK Biobank; the CARTaGENE Project in Quebec, Canada; the Banco Nacional de ADN in Spain; the International HapMap Project; and several US biobanks, such as the National Children's Study, the Marshfield Clinic's Personalized Medicine Research Project and the National Health and Nutrition Examinations Surveys. ![][1] This boom of biobanks has spawned a ‘boomlet’ of regulations and guidelines, which has created controversies, particularly about the importance and definition of informed consent. The consent of participants is usually required before biobank samples can be used in research, but the nature of this consent, and how it is obtained, vary widely. Many European guidelines take the view that general consent is acceptable to use samples for future, as yet unspecified, research projects; US and Canadian policy follows a more rigorous standard of consent. Until 2004, both Europe and the USA considered coded and linked anonymized samples—in which a code links the sample to its donor—as identifiable and therefore … [1]: /embed/graphic-1.gif

BackgroundLiterature on issues relating to comprehension during the process of obtaining informed consent (IC) has largely focused on the challenges potential participants can face in understanding the IC documents, and the strategies used to enhance comprehension of those documents. In this review, we set out to describe the factors that have an impact on comprehension and the strategies used to enhance the IC process in sub-Saharan African countries.MethodsFrom November 2021 to January 2022, we conducted a literature search using a PRISMA tool. We searched electronic databases (PubMed, EMBASE, EBSCOHOST) to identify relevant peer reviewed studies. We then reviewed the references of these articles to find additional literature that might have been missed through the initial search. We were particularly interested in full text articles in English that focused on the IC process in SSA published between 2006 and 2020. We included systematic reviews, and studies from Western and Asian countries that included data about SSA. We excluded articles that focused on medical interventions and studies that did not require IC.ResultsOut of the 50 studies included most were multi-country (n = 13) followed by single country studies in South Africa (n = 12); Kenya, Tanzania, Uganda (n = 5) each; Gambia, Ghana and Nigeria (n = 2)each ; and one each for Botswana, Malawi, Mali, Mozambique. We identified three areas of focus: (1) socio-cultural factors affecting IC; (2) gaps in the ethical and legal frameworks guiding the IC process; and (3) strategies used to improve participants’ understanding of IC.ConclusionOur review showed wide recognition that the process of achieving IC in SSA is inherently challenging, and there are limitations in the strategies aimed at improving comprehension in IC. We suggest that there is a need for greater flexibility and negotiation with communities to ensure that the approach to IC is suited to the diverse socio-cultural contexts. We propose moving beyond the literal translations and technical language to understanding IC comprehension from the participants’ perspectives and the researchers’ views, while examining contextual factors that impact the IC process.

Ethical standards for cardiothoracic surgeons' participation in social media

Ethics and Law.

Family-based research in genetically isolated populations is an effective approach for identifying loci influencing variation in disease traits. In common with all studies in humans, those in genetically isolated populations need ethical approval; however, existing ethical frameworks may be inadequate to protect participant privacy and confidentiality and to address participants' information needs in such populations. Using the ethical-legal guidelines of the Council for International Organizations of Medical Sciences (CIOMS) as a template, we compared the participant information leaflets and consent forms of studies in five European genetically isolated populations to identify additional information that should be incorporated into information leaflets and consent forms to guarantee satisfactorily informed consent. We highlight the additional information that participants require on the research purpose and the reasons why their population was chosen; on the potential risks and benefits of participation; on the opportunities for benefit sharing; on privacy; on the withdrawal of consent and on the disclosure of genetic data. This research raises some important issues that should be addressed properly and identifies relevant types of information that should be incorporated into information leaflets for this type of study.

This theoretical examination explores the challenges and approaches to establishing ethical frameworks for the integration of artificial intelligence (AI) in healthcare entrepreneurship. As AI technologies continue to advance, their applications in healthcare hold immense potential for improving patient outcomes and driving innovation. However, ethical considerations are paramount to ensure the responsible and equitable deployment of AI-driven solutions. This paper delves into key ethical dimensions including privacy and data security, bias and fairness, accountability and transparency, and patient autonomy and consent. It identifies challenges such as technological limitations, regulatory complexities, and organizational barriers that impede the implementation of ethical frameworks. Additionally, it proposes approaches including collaborative governance models, ethical design practices, and continuous monitoring and evaluation to address these challenges. Through case studies and examples, the paper illustrates successful implementations of ethical frameworks in AI healthcare startups, highlighting lessons learned and their impact on patient outcomes and trust. Ultimately, this examination underscores the critical importance of ethical considerations in shaping the future of AI in healthcare entrepreneurship and provides insights for researchers, practitioners, and policymakers navigating this rapidly evolving landscape.

Clinical Research in Neglected Tropical Diseases: The Challenge of Implementing Good Clinical (Laboratory) Practices.

BackgroundAs genomics and biobanking expanded rapidly across Africa, ethical governance frameworks for genomic research and biobanking often failed to keep pace, particularly in countries like Zimbabwe, where research increasingly involved international collaboration, but regulatory oversight remained limited. This study analysed how Zimbabwean researchers addressed the ethical, legal, and sociocultural issues (ELSIs) central to human biospecimen and genomic research.MethodsWe conducted a comprehensive review of research protocols submitted to the Medical Research Council of Zimbabwe between 2009 and 2016, specifically those involving human biospecimen collection, biobanking, and genomic research. A structured abstraction form was employed to evaluate how these protocols addressed key ELSIs, including informed consent, biospecimen and data sharing, benefit sharing, and intellectual property considerations.ResultsOf the 200 eligible protocols, 92(46%) were submitted by independent research institutions and 67(33.5%) by universities. Consent practices varied: 99(49.5%) protocols utilized specific consent, 37(18.5%) employed broad consent, and 37(18.5%) used blanket consent. Notably, 2(1%) protocols did not use consent forms, opting instead for broad or specific notifications. Only 44(22%) protocols included plans for the destruction of collected samples. While 44(22%) protocols involved exporting biospecimens, nearly two-thirds of these lacked a material transfer agreement (MTA). Critically, benefit sharing was absent across all protocols, and only 26(13%) addressed intellectual property rights.ConclusionsThis review exposes systemic gaps in the ethical planning of genomics and biobanking research in Zimbabwe. Although researchers are increasingly engaging in cutting-edge science, the regulatory and ethical frameworks require transformation. The limited attention to benefit sharing, consent for future use, and intellectual property reflects deeper governance and equity challenges. To protect research participants and ensure ethical integrity, Zimbabwe urgently needs updated national guidelines that define minimum standards for addressing a full range of ELSIs, moving beyond consent and privacy to embrace justice, accountability, and long-term stewardship. Strengthening these frameworks is crucial to ensuring ethical integrity in Zimbabwe’s growing biobanking and genomic research landscape.

The sharing of medical data between different healthcare organizations in Europe must comply with the legislation of the Member State where the data were originally collected. These legal requirements may differ from one state to another. Privacy requirements such as patient consent may be subject to conflicting conditions between different national frameworks as well as between different legal and ethical frameworks within a single Member State. These circumstances have made the compliance management process in European healthgrids very challenging. In this paper, we present an approach to tackle these issues by relying on several technologies in the semantic Web stack. Our work suggests a direct mapping from high-level legislation on privacy and data protection to operational-level privacy-aware controls. Additionally, we suggest an architecture for the enforcement of these controls on access control models adopted in healthgrid security infrastructures.

AI scribes have had a rapid uptake in primary care across New Zealand (NZ). The benefits of this new technology must be weighed against the potential risks they may pose. This study provides a snapshot of AI scribes use in primary care to generate clinical notes. We aimed to understand emerging provider experiences, identify perceived clinical benefits and concerns, and flag potential ethical and legal issues as a basis for future research and policy development. GPs and health providers working in primary care across NZ were invited to participate in an anonymous survey about their experience with AI scribes (February-March 2024). One hundred and ninety-seven respondents completed the survey, 88% (n=164) of whom were GPs. Of these, 40% (n=70) had experience with AI scribes. Reported benefits included: reduced multitasking (n=46), saved time (n=43), and improved rapport with patients (n=43). Key concerns included: compliance with NZ legal and ethical frameworks (n=108), data security (n=98), errors or omissions (n=93), and data leaving New Zealand (n=91). Only 66% (n=41) had read the terms and conditionss of the AI scribe tool, and 59% (n=35) reported seeking patient consent. Most (80%, n=50) found AI scribes helpful or very helpful, and 56% (n=35) said the tool changed consultation dynamics. While there is strong uptake and enthusiasm for AI scribes in primary care in NZ, critical issues remain around legal and ethical oversight, patient consent, data security, and the broader impact on clinician-patient interactions. Health providers need clearer guidance and regulatory support for safe, ethical, and legal use of AI tools.

Integration of technology in healthcare has led to new fronts of innovative patient care which also have ethical issues, particularly with regard to sustainability. This chapter examines the ethics of these healthcare technology design, deployment, and disposal in a time increasingly defined by environmentally aware and socially responsible climate. It dares to look at the balance between technological innovation and sustainable practices in medical devices, principles such as equity, accessibility, patient consent, data security and the environmental impact of medical devices. The chapter, through a multidisciplinary approach, takes ethical frameworks, and real world case studies, and enumerates them to aid responsible innovation in sustainable healthcare systems.

The reuse of single use medical items is a complex ethical issue that many healthcare providers are faced with, for while recommendations and literature do not advocate the reuse of...

To be processed within a healthgrid environment, medical data goes through a complete lifecycle and several stages until it is finally used for the primary reason it has been collected for. This stage is not always the final occurrence of when the data would have been manipulated. The data could rather continue to be needed for secondary purposes of legitimate or non legitimate nature. Although other privacy issues are related to the processing of patient data while it is residing on a healthgrid environment, the control of data disclosure is our primary interest. When sharing medical data between different Healthcare and biomedical research organizations in Europe, it is important that the different parties involved in the sharing handle the data in the same way indicated by the legislation of the member state where the data was originally collected as the requirements might differ from one state to another. Privacy requirements, such as patient consent, may be subject to conflicting conditions between different national frameworks as well as between different legal and ethical frameworks within a single member state. These circumstances have made the compliance management process in European healthgrid very challenging. In this paper we are presenting an approach to tackle these issues by relying on several technologies contained in the semantic web stack. Our work suggests a direct mapping from high level legislation on privacy and data protection to operational level privacy aware controls. Additionally we suggest an architecture for the enforcement of these controls on access control models adopted by healthgrids security infrastructures.

Background Artificial Intelligence (AI) is emerging as a pivotal technology with vast promises for healthcare. However, integrating AI into clinical and public health settings must be cautiously approached to ensure that it does not inadvertently exacerbate existing health system problems. The healthcare workers, already under severe stress, could view AI as a threat to job security rather than as a support mechanism. Moreover, past experiences with digital transformations, such as Electronic Health Records, have shown that technological integration can sometimes increase rather than decrease the burden on healthcare workers, leading to burnout and dissatisfaction, and thus worsening the healthcare workforce crisis. Furthermore, equity and ethical considerations are paramount in the deployment of AI in healthcare. Data privacy, patient consent, and algorithmic bias must be addressed to ensure that AI applications are designed to support and enhance human decision-making that is sensitive to the social determinants of health and accountable to equity and social inclusion, to the needs and rights of the healthcare workforce, and the dignity of the patients and populations. While AI presents significant opportunities for health systems and healthcare workers, there is a lack of knowledge, evidence-based policies, and ethical frameworks that support equitable and human-centred approaches to AI implementation. Objectives This round table workshop aligns three major public health challenges: the integration of AI in health systems, the global healthcare workforce crisis, and the improvement of equity and equality. It critically explores capacity building for AI, equity in AI implementation, and regulatory measures for ethical and responsible AI deployment, addressing the following major questions: What are the critical impacts of AI on the healthcare workforce? How can the healthcare workforce be effectively upskilled and supported to adapt to the changes brought by AI technologies? What regulatory frameworks and governance models are necessary to ensure AI’s safe and ethical implementation in healthcare, that is also sensitive to equity, gender equality and the needs of minority groups? Finally, what actionable steps and leadership can public health take to implement AI technologies while addressing the healthcare workforce needs, equity issues, and ethical guidelines? The panellists will illuminate these questions from different disciplinary approaches, helping us to disentangle complexity and to build capacity for evidence-based and socially inclusive AI policies. The workshop contributes to better understand the risks and benefits of AI. It seeks to advance knowledge exchange of good practice experiences and effective implementation. Key messages • The effects of AI on the healthcare workforce must be monitored and strategies adapted to mitigate the healthcare workforce crisis and to upskill and empower healthcare workers. • There is a need for human-centred and ethically responsive AI implementation and governance measures that support equity, gender equality, and diversity in healthcare settings. Speakers/Panelists Abi Sriharan Schulich School of Business York University, York, Canada Kasia Czabanowska Maastricht University, Maastricht, Netherlands Bernadette Kumar Migration Health Unit, Norwegian Institute of Public Health, Oslo, Norway Marius-Ionuț Ungureanu Babeș-Bolyai University, Cluj-Napoca, Romania Farhang Tahzib Faculty of Public Health, Haywards heath, UK

Traditional imaging techniques are limited by their preoperative nature, limited image resolution, and the need for radiologist interpretation. Multiple advanced imaging technologies have been developed, which may enhance surgical precision and patient outcomes. Near-infrared fluorescence (NIRF) imaging, particularly with indocyanine green (ICG) dye, enables perfusion assessments and may help prevent anastomotic leaks. Additionally, NIRF can augment the identification of tumour growth patterns and lymphatic networks, thereby improving resection margin accuracy. Combining NIRF with radioisotope tracers allows for deep tissue navigation with high-precision dissection. In advanced disease, radioisotope scans may also enable prompt identification and excision of distally affected lymph nodes. Hyperspectral imaging (HSI) provides molecular-level information without the need for harmful contrast agents. HSI tissue vascularisation data may help shorten procedure times and reduce perioperative morbidity. Furthermore, when combined with neural networks, the technology can improve tumour detection and tissue differentiation. Extended reality (XR) has multiple applications within surgical imaging. Augmented reality (AR) allows for intraoperative image overlays, thereby improving surgical navigation. Additionally, virtual reality (VR) may help users to visualise three-dimensional anatomical reconstructions, with applications in surgical training and patient consent. Artificial intelligence (AI) systems offer enhanced perioperative information to surgeons, such as the prediction of both disease progression and patient response to treatment. These benefits are compounded when paired with imaging modalities, such as HSI and XR. Overall, advanced imaging technologies offer an exciting future for surgical practice and improved patient outcomes. Further work, including standardised protocols and ethical frameworks, is required.