Perhaps machine learning systems trained on patients’ electronic health records and social media footprints could be used as decision aids when patients lack capacity or face overwhelming decisions.

Training should be implemented to respond to clinical staff members’ concerns about trans patients occupying sex-segregated spaces and to help mitigate anti-trans bias.

Despite challenges of decision making for unrepresented patients, few laws or policy statements offer solutions. This article offers 5 key things to do.

Following evidence-based approaches to evaluating and reporting suspicion of child maltreatment can help minimize bias and promote equity.

Intergenerational trauma has deep roots, which require clinicians to understand historical and cultural context when working with vulnerable children.

How society and medicine discussed and responded to child abuse changed dramatically in 1962. Since that time, the problem’s fuller scope has been revealed.

Protecting patients rather than informed consent should be the goal when the complexity of information overwhelms patients’ decision-making capacity.

Suspected child abuse cases can be identified and repeat hospitalizations of such cases prevented using multidisciplinary teams to evaluate pediatric burns.

One health system’s development and validation of inequity measures across patient groups demonstrates an approach that could be nationally scalable.

Dr Michael J. Oldani joins Ethics Talk to discuss his article: “Papal Doctrines’ Deep Trauma Legacies in Minoritized Communities.”