Camillo Lamanna, MMathPhil, MBBS and Lauren Byrne, MBBS
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.
AMA J Ethics. 2018;20(9):E902-910. doi:
10.1001/amajethics.2018.902.
Trafficking-specific ICD-10-CM codes account for physical, social, and psychological dimensions of trafficked patients’ experiences. Data collected by clinicians can also motivate improvements in health policy, resource allocation, and prevention.
AMA J Ethics. 2018;20(12):E1143-1151. doi:
10.1001/amajethics.2018.1143.
Health care reform expanded health insurance to millions, but current community benefit policies must be used by organizations hoping to address social determinants.
AMA J Ethics. 2019;21(3):E248-258. doi:
10.1001/amajethics.2019.248.
Where people live and work influences how long and how well they live. Supporting community investments can diminish risk, improve outcomes, and reduce costs.
AMA J Ethics. 2019;21(3):E262-268. doi:
10.1001/amajethics.2019.262.
Researchers and clinicians face ethical and policy-based challenges in disclosing, preventing and treating psychosis. Which diagnostic labels should be considered to motivate more effective public and professional dialogue about psychosis risk?
AMA J Ethics. 2016;18(6):624-632. doi:
10.1001/journalofethics.2016.18.6.msoc1-1606.
The DSM-5 Task Force’s handling of the ethical controversy over the bereavement exclusion demonstrates the need for more inclusive deliberative processes.
AMA J Ethics. 2017;19(2):192-198. doi:
10.1001/journalofethics.2017.19.2.pfor2-1702.
Many pregnant undocumented immigrants are ineligible for public insurance covering prenatal care. National and state policies can either help or hinder patients’ access to health care that is universally recommended by professional guidelines.
AMA J Ethics. 2019;21(1):E93-99. doi:
10.1001/amajethics.2019.93.
Michael Anderson, PhD and Susan Leigh Anderson, PhD
Two concerns (unknowability of how output is derived from input and overreliance on clinical decision support systems) are main sources of ethical questions about AI in health care.
AMA J Ethics. 2019;21(2):E125-130. doi:
10.1001/amajethics.2019.125.