Artificial/Augmented Intelligence

Keith Hansen, MD
President, South Dakota State Medical Association
August 1, 2025

At this year’s SDSMA Annual Leadership Conference, we had excellent discussions about the current state of artificial/augmented intelligence (AI) in healthcare, its rapid expansion, and its use in South Dakota. We were fortunate to listen to talks on this topic by healthcare leaders with expertise on AI from Avera Health, Monument Health, and Sanford Health. These talks reinforced the rapidly evolving field of AI and their application to health care especially in South Dakota and how much change has occurred in the last couple years.

AI holds promise in improving patient care, research and medical education. The AMA notes that “augmented intelligence” is a better term for AI in medical care, as it will never replace the physician and a physician will always be important and integral in interpreting information and applying it to the healthcare of the patient. One area where AI may be valuable is in precision medicine, which is healthcare targeted to the individual using psychosocial, biometric, genetic and phenotypic data to arrive at the “right treatment for the right patient at the right time.” AI is very helpful in evaluating and interpreting large amounts of data and making it readily available to the clinician to treat their patients, such as those with chronic diseases, like diabetes mellitus where AI could allow for the application of precision medicine and evidence based medical care. Psychosocial determinants of care include social determinants of health such as rural vs. urban, geographic location (such as whether the patient lives in a ‘food desert’), financial and insurance issues, age, mental health issues, and other issues. Biomarkers include laboratory tests and imaging such as the hemoglobin A1C level as a reflection of glucose control in diabetes mellitus. Genetic/genomic data includes large amounts of data such as sequencing the patient’s exome and genome – which one use is the selection of an appropriate therapy for the patient based on expected drug metabolism. The phenotypic evaluation depends on the complete history, past medical history, social history, family history and physical examination of the patient conducted by the physician. The history and physical examination can then be combined with the psychosocial, biometric and genomic data by AI to assist the physician with diagnosis, a personalized evidence-based treatment plan, prediction and assistance in prevention of short-and long-term complications, and enhancement of patient participation in their management plan. The use of AI in medical care will require a paradigm shift from the usual patient-physician interaction to the tripartite; patient-physician-AI interaction. AI also holds the promise of automating repetitive tasks such as documentation, pre-authorizations, billing and other tasks while also improving analysis of data and developing an evidence-based plan of management. There are a number of potential risks with AI, including patient privacy and safety.

With the rapidly increasing use of AI in medical care, the SDSMA Board of Directors is forming a special Committee on Artificial Intelligence to develop a white paper on important factors in the use of AI. This committee will also look at the adoption of association policy in this area. I look forward to the committee’s work guiding the ethical and effective integration of AI, ultimately benefitting both physicians and patients across our state.