This paper challenges historically preconceived notions surrounding a minor’s ability to make medical decisions, arguing that federal health law should be reformed to allow minors with capacity as young as age 12 to consent to their own Centers for Diseases Control and Prevention (CDC)-approved COVID-19 vaccinations. This proposal aligns with and expands upon current exceptions to limitations on adolescent decision-making. This analysis reviews the historic and current anti-vaccination sentiment, examines legal precedence and rationale, outlines supporting ethical arguments regarding adolescent decision-making, and offers rebuttals to anticipated ethical counterarguments.

This article argues that the Supreme Court’s decision in Dobbs is likely to impact medical decision-making by pregnant patients in a variety of contexts. Of particular concern are situations where a patient declines treatment recommended for its potential benefit to the fetus and situations where treatment is withheld due to potential risk to the fetus. The Court’s elevation of fetal interests, combined with a history of courts using abortion jurisprudence to guide their reasoning in compelled treatment cases, means that Dobbs has the potential to limit patient autonomy in a wide array of clinical settings. The article calls on professional medical associations to issue ethical guidance affirming the duty to respect the medical self-determination of pregnant patients.

The end of Roe v. Wade has significant implications for the autonomy of pregnant patients at the end of life. At least thirty states restrict the choice to withhold/withdraw life-sustaining treatments from pregnant patients without decisional capacity, invalidating prior advance directives and prohibiting others from choosing these options for the patient. Many restrictions are based on the Roe framework, applying after “viability” or similar considerations of fetal development or prospect for live birth. Scholars have also relied on the abortion framework, arguing that the restrictions impose an undue burden. The end of Roe will free states from having to craft limited restrictions designed to work around prior abortion jurisprudence. Similarly, advocates will no longer be able to draw support from the abortion framework, forcing them to rely instead on cases supporting rights to autonomy/bodily integrity in medical decision-making.

When is it justified to use opaque artificial intelligence (AI) output in medical decision-making? Consideration of this question is of central importance for the responsible use of opaque machine learning (ML) models, which have been shown to produce accurate and reliable diagnoses, prognoses, and treatment suggestions in medicine. In this article, I discuss the merits of two answers to the question. According to the Explanation View, clinicians must have access to an explanation of why an output was produced. According to the Validation View, it is sufficient that the AI system has been validated using established standards for safety and reliability. I defend the Explanation View against two lines of criticism, and I argue that within the framework of evidence-based medicine mere validation seems insufficient for the use of AI output. I end by characterizing the epistemic responsibility of clinicians and point out how a mere AI output cannot in itself ground a practical conclusion about what to do.

Capacity evaluation has become a widely used assessment device in clinical practice to determine whether patients have the cognitive ability to render their own medical decisions. Such evaluations, which might be better thought of as “capacity challenges,” are generally thought of as benign tools used to facilitate care. This paper proposes that such challenges should be reconceptualized as significant medical interventions with their own set of risks, side effects, and potentially deleterious consequences. As a result, a cost–benefit analysis should be implemented prior to imposing such capacity challenges, and efforts should be made to minimize such challenges in situations where they are unlikely to alter the course of treatment.

How should we respond to patients who do not wish to take on the responsibility and burdens of making decisions about their own care? In this paper, we argue that existing models of decision-making in modern healthcare are ill-equipped to cope with such patients and should be supplemented by an “appointed fiduciary” model where decision-making authority is formally transferred to a medical professional. Healthcare decisions are often complex and for patients can come at time of vulnerability. While this does not undermine their capacity, it can be excessively burdensome. Most existing models of decision-making mandate that patients with capacity must retain ultimate responsibility for decisions. An appointed fiduciary model provides a formalized mechanism through which those few patients who wish to defer responsibility can hand over decision-making authority. By providing a formal structure for deferring to an appointed fiduciary, the confusions and risks of the informal transfers that can occur in practice are avoided. Finally, we note how appropriate governance and law can provide safeguards against risks to the welfare of patients and medical professionals.

The objective of this study was to determine how clinicians make use of the modern multiplex PCR assays (MPAs) to manage patients hospitalized for community-acquired pneumonia (CAP). We studied the use of MPAs in 1648 patients hospitalized for CAP over a 3-year period at the moment of the setup of the new PCR assay. We observed that the use of MPAs for the identification of multiple respiratory pathogens marks a radical change in the investigation of CAP etiology. Surprisingly, the contribution of MPAs to the medical decision-making process varies drastically according to the units of care.

To examine the association between reasoning through medical treatment decisions and cognition in a sample of patients with brain metastasis. The association between reasoning and cognition was examined using data from 41 patients with diagnosed brain metastasis. All diagnoses were made by a board-certified radiation oncologist and were verified histologically. In total, 41 demographically matched, cognitively healthy controls were also included to aid in classifying patients with brain metastasis according to reasoning status (i.e., intact or impaired). Results indicate that measures of episodic memory and processing speed were associated with reasoning. Using these two predictors, actuarial equations were constructed that can be used to help screen for impaired reasoning ability in patients’ with brain metastasis. The equations presented in this study have clinical significance as they can be used to help identify patients at risk for possessing a diminished ability to reason through medical treatment decisions and, thus, are in need of a more comprehensive evaluation of their medical decision-making capacity. (JINS, 2015, 21, 412–418)