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Physicians in northern Italy have learned some painful lessons about rationing care during an epidemic. As health care systems work out ethical allocation principles, it seems clear that only with transparency and inclusivity can public trust and cooperation be achieved.

The Covid-19 pandemic has already stressed health care systems throughout the world, requiring rationing of medical equipment and care. The authors discuss the ethical values relevant to health care rationing and provide six recommendations to guide fair allocation of scarce medical resources during the pandemic.

The article's abstract is not available.

Of all the medical care that will have to be rationed during the Covid-19 pandemic, the most problematic will be mechanical ventilation. One strategy for avoiding debilitating distress over these decisions is to use a triage committee to buffer bedside clinicians.

Allocation of very scarce medical interventions such as organs and vaccines is a persistent ethical challenge. We evaluate eight simple allocation principles that can be classified into four categories: treating people equally, favouring the worst-off, maximising total benefits, and promoting and rewarding social usefulness. No single principle is sufficient to incorporate all morally relevant considerations and therefore individual principles must be combined into multiprinciple allocation systems. We evaluate three systems: the United Network for Organ Sharing points systems, quality-adjusted life-years, and disability-adjusted life-years. We recommend an alternative system—the complete lives system—which prioritises younger people who have not yet lived a complete life, and also incorporates prognosis, save the most lives, lottery, and instrumental value principles.

Background Artificial intelligence-driven Clinical Decision Support Systems (AI-CDSS) are increasingly being integrated into healthcare for various purposes, including resource allocation. While these systems promise improved efficiency and decision-making, they also raise significant ethical concerns. This study aims to explore healthcare professionals’ perspectives on the ethical implications of using AI-CDSS for healthcare resource allocation. Methods We conducted semi-structured qualitative interviews with 23 healthcare professionals, including physicians, nurses, administrators, and medical ethicists in Turkey. Interviews focused on participants’ views regarding the use of AI-CDSS in resource allocation, potential ethical challenges, and recommendations for responsible implementation. Data were analyzed using thematic analysis. Results Participant responses are clustered around five pre-determined thematic areas: (1) balancing efficiency and equity in resource allocation, (2) the importance of transparency and explicability in AI-CDSS, (3) shifting roles and responsibilities in clinical decision-making, (4) ethical considerations in data usage and algorithm development, and (5) balancing cost-effectiveness and patient-centered care. Participants acknowledged the potential of AI-CDSS to optimize resource allocation but expressed concerns about exacerbating healthcare disparities, the need for interpretable AI models, changing professional roles, data privacy, and maintaining individualized care. Conclusions The integration of AI-CDSS into healthcare resource allocation presents both opportunities and significant ethical challenges. Our findings underscore the need for robust ethical frameworks, enhanced AI literacy among healthcare professionals, interdisciplinary collaboration, and rigorous monitoring and evaluation processes. Addressing these challenges proactively is crucial for harnessing the potential of AI-CDSS while preserving the fundamental values of equity, transparency, and patient-centered care in healthcare delivery.

Andrew Peterson and colleagues explore ways to protect vulnerable populations when making ethically fraught decisions about use of scarce resources

In 2024, new legislation introduced significant changes to the rules, procedures and institutions governing research ethics in Brazil. One of its objectives was to limit sponsors’ post-trial access (PTA) obligations. However, a presidential veto weakened this reform. This veto maintained the sponsors’ indefinite duty to provide the tested intervention until it becomes available in the National Health System. In Brazil, where courts often order the public funding for treatments not included in the health system’s lists and protocols, a substantial reduction in the sponsors’ PTA obligations would likely increase litigation seeking state-funded PTA. This dynamic adds an extra layer of complexity to the ethical analysis of the regulation of PTA in Brazil, as its distributive impact on the public health system must be considered. Therefore, any argument for reducing sponsors’ PTA obligations must go beyond simply demonstrating that sponsors do not owe participants an ethical obligation to provide them with indefinite access to the tested intervention or that such obligation discourages research. It must also make a compelling case for why the state, rather than sponsors, should bear the responsibility for funding PTA.

Severe staffing shortages have emerged as a prominent threat to maintaining usual standards of care during the COVID-2019 pandemic. In dire settings of crisis capacity, healthcare systems assume the ethical duty to maximise aggregate population-level benefit of existing resources. To this end, existing plans for rationing mechanical ventilators and intensive care unit beds in crisis capacity focus on selecting individual patients who are most likely to survive and prioritising these patients to receive scarce resources. However, staffing capacity is conceptually different from availability of these types of discrete resources, and the existing strategy of identifying and prioritising patients with the best prognosis cannot be readily adapted to fit this real-world scenario. We propose that two alternative approaches to staffing resource allocation offer a better conceptual fit: (1) prioritise the worst off: restrict access to acute care services and hospital admission for patients at relatively low clinical risk and (2) prioritise staff interventions with high near-term value: universally restrict selected interventions and treatments that require substantial staff time and/or energy but offer minimal near-term patient benefit. These strategies—while potentially resulting in care that deviates from usual standards–support the goal of maximising the aggregate benefit of scarce resources in crisis capacity settings triggered by staffing shortages. This ethical framework offers a foundation to support institutional leaders in developing operationalisable crisis capacity policies that promote fairness and support healthcare workers.