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Assessing the Current Limitations of Large Language Models in Advancing Health Care Education.
JMIR Form Res
January 2025
Department of Physician Assistant Studies, Massachusetts College of Pharmacy and Health Sciences, 179 Longwood Avenue, Boston, MA, 02115, United States, 1 6177322961.
The integration of large language models (LLMs), as seen with the generative pretrained transformers series, into health care education and clinical management represents a transformative potential. The practical use of current LLMs in health care sparks great anticipation for new avenues, yet its embracement also elicits considerable concerns that necessitate careful deliberation. This study aims to evaluate the application of state-of-the-art LLMs in health care education, highlighting the following shortcomings as areas requiring significant and urgent improvements: (1) threats to academic integrity, (2) dissemination of misinformation and risks of automation bias, (3) challenges with information completeness and consistency, (4) inequity of access, (5) risks of algorithmic bias, (6) exhibition of moral instability, (7) technological limitations in plugin tools, and (8) lack of regulatory oversight in addressing legal and ethical challenges.
View Article and Find Full Text PDFHow to Provide Additional Oversight to Ensure That Remote Patient Monitoring for People With Diabetes is Being Used and Billed Appropriately.
J Diabetes Sci Technol
January 2025
Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA, USA.
An Office of the Inspector General (OIG) report on September 19, 2024, highlighted the need for additional oversight of remote patient monitoring (RPM), which is covered by Medicare. OIG noted that Medicare claims frequently lack crucial information that would facilitate proper oversight. While Medicare has published guidelines for reimbursement according to RPM billing codes, greater clarity is needed to avoid inadvertent improper billing practices.
View Article and Find Full Text PDF-cigarette use among adolescents in Latin America: A systematic review of prevalence and associated factors.
Prev Med Rep
January 2025
One Health Research Group, Faculty of Medicine, Universidad de las Américas, Quito, Ecuador.
Background: Electronic cigarettes, introduced as a safer tobacco alternative, have unintentionally exposed millions of youths to nicotine and harmful chemicals. Adolescence, a key period for forming lifelong habits, has seen rising e-cigarette use, particularly in developing regions like Latin America, warranting thorough investigation.
Objective: To describe the prevalence and factors associated with e-cigarette use among adolescents in Latin America.
Clinical supervision in positive behaviour support: A brief report on the perspectives of practitioners in Australia.
J Intellect Dev Disabil
December 2024
Disability and Community Inclusion, College of Nursing and Health Sciences, Flinders University, Adelaide, Australia.
Purpose: To examine current practices and recommendations regarding clinical supervision from the perspective of Positive Behaviour Support (PBS) practitioners in Australia.
Methods: A qualitative study design consisting of semi-structured interviews with 14 PBS practitioners.
Results: Positive supervision experiences revealed the importance of "a supportive relationship", "supporting reflective practice", and "different supervisors fulfilling different needs.
High-reward, high-risk technologies? An ethical and legal account of AI development in healthcare.
BMC Med Ethics
January 2025
Faculty of Law, University of Montreal, Ch de la Tour, Montreal, QC, H3T 1J7, Canada.
Background: Considering the disruptive potential of AI technology, its current and future impact in healthcare, as well as healthcare professionals' lack of training in how to use it, the paper summarizes how to approach the challenges of AI from an ethical and legal perspective. It concludes with suggestions for improvements to help healthcare professionals better navigate the AI wave.
Methods: We analyzed the literature that specifically discusses ethics and law related to the development and implementation of AI in healthcare as well as relevant normative documents that pertain to both ethical and legal issues.
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