Telemedicine Tools Emerging in Medical School

Artificial intelligence (AI) is transforming health care. The global impact of AI, for better or for worse, will be profound because it is widely applicable across all fields of medicine. Reform of modern medical education curricula is essential for the safe and effective integration of AI into our future health care system.

Undoubtably, AI has the potential to enhance many aspects of health care in the United States. Hailed by the National Academy of Medicine, “the emergence of AI as a tool for better health care offers unprecedented opportunities to improve patient and clinical team outcomes, reduce costs and impact population health” in the 2019 Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril.

Today’s clinicians have access to an immense volume of medical data and information. In fact, the wealth of medical information is so great that it far exceeds human interpretation capacity.

The tremendous value of AI lies in its ability enhance clinician decision-making by interpreting this uninterpretable information.

Despite recent promising examples of AI application in health care, the National Academy of Medicine cautions “we believe it is imperative to proceed with caution, else we may end up with user disillusionment and another AI winter, and/or further exacerbate existing health and technology driven disparities.”

Many concerning AI development and implementation issues have been highlighted in the literature, including biased data sets, poorly generalizable training and validation data sets, unintended consequences, risk/benefit considerations, and inadequate cost of care analysis. Such developmental miscalculations have dangerous health and health care economic implications. Unfortunately, today’s clinician has not been adequately trained to develop and interpret AI, limiting widespread safety assessment and utilization.

The American Medical Association published an article in 2019, Reimagining Medical Education in the Age of AI. The authors recommended an overhaul of medical school curricula with a focus on knowledge management and communication rather than information acquisition.

Such a transformation would resolve several significant issues pertaining to modern medical education and AI. Firstly, it would alleviate some of the psychological burden that medical students currently face as a result of “information overload and concerns about never knowing enough,” factors that have been linked to mental health deterioration among medical students and trainees.

Rather than focusing solely on information acquisition, learners should be taught to collaborate with the AI systems that interpret such information through stochastic and probability-based techniques compatible with AI system development and interpretation.

Across the country, we see the great benefits that AI can provide to our health care; however, medical curriculum reform has not yet caught up to this evolution in medical care.

Despite the continued integration and consideration of AI use in our health care system, one thing that must never leave sight of our care is humanism in medicine. No machine can disentangle the biopsychosocial complexities of our society.

Medicine will remain humanistic at its core. By learning to collaborate with AI, future clinicians will have more opportunity to focus on the non-analytical, humanistic, individualized patient care where currently, technology takes the forefront.

Adam Sturts, MSIV is a fourth-year medical student at Rowan University School of Osteopathic Medicine. This piece reflects the author’s views and not necessarily those of the publication.