Alden M. Landry, MD, MPH, Rose L. Molina, MD, MPH, Regan Marsh, MD, MPH, Emma Hartswick, Raquel Sofia Sandoval, Nora Osman, MD, and Leonor Fernandez, MD
Adapting content in response to new science is common, but educators can struggle to offer current questions that matter to students.
AMA J Ethics. 2021;23(2):E127-131. doi:
10.1001/amajethics.2021.127.
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.
Using crowdsourced information in health professions education can help motivate critical appraisal, question asking, and evidence evaluation skill development, especially among “digital natives.”
AMA J Ethics. 2018;20(11):E1033-1040. doi:
10.1001/amajethics.2018.1033.
Targeted dosing to treat pediatric inflammatory bowel disease is challenging because dosing guidelines are based on data gathered from adult subjects of clinical trials. Patients’ families and health care organizations also incur high costs and must try to balance potential benefits against risks of ongoing monitoring.
AMA J Ethics. 2018;20(9):E841-848. doi:
10.1001/amajethics.2018.841.
Emily L. Evans, PhD, MPH and Danielle Whicher, PhD, MHS
Clinical decision support systems leverage data generated in the course of standard clinical care to improve clinical practice. They need to ensure privacy and quality of patients’ data, but must also allow queries of electronic health records.
AMA J Ethics. 2018;20(9):E857-863. doi:
10.1001/amajethics.2018.857.
Social and behavioral data contained in electronic health records are essential for studying health disparities. Can researchers avoid bias when collecting, analyzing, and using such data?
AMA J Ethics. 2018;20(9):E873-880. doi:
10.1001/amajethics.2018.873.