AI meets CME: A next-generation platform for opioid prescribing education
Description
The implementation and advancement of artificial intelligence (AI) into the field of medicine has had a profound impact, leading to a momentous change in how physicians practice and interact with patients. This integration of technology and setting has not been confined just to in- / out-patient-related facilities but has rapidly expanded into multiple medical disciplines, including research and education. Utilizing prompt engineering, what once was only capable of well-funded institutions with large teams that spanned multiple specialties, can now be accomplished by a necessary few, closing the gap and allowing for unique opportunities for medical students and researchers alike. One such opportunity being DO student led adult programing that combines both research and education. Given that all graduating medical students are required to take, at a minimum, two continuing medical education (CME) credit hour courses over opioid prescribing relating to chronic pain, and only 20% of current med schools have pain programming; students, sought to bridge this gap with the creation of a 2 CME credit curriculum at DMU utilizing already established elective courses. A prompt was engineered to analyze the entire CDC 2022 Clinical Practice Guideline for Prescribing Opioids and group CDC recommendations that fulfilled Iowa’s Opioid Prescriber requirements. From this, 12 recommendations were formed and grouped into 4 separate modules with one lecture per module. An additional prompt was engineered to cross reference each module with each individual elective lecture and assign relevant slides to a module lecture. Slides were then optimized with original content, finalized and await approval.
Citation Information
Mulder, Lane C.; Suda, Parik G.; Starcevic, Milica; Boge, Justin; and Duric, Vanja, "AI meets CME: A next-generation platform for opioid prescribing education" (2026). Office of Research DMU Research Symposium. 23.
https://digitalcommons.dmu.edu/researchsymposium/2025rs/2025abstracts/23
AI meets CME: A next-generation platform for opioid prescribing education
The implementation and advancement of artificial intelligence (AI) into the field of medicine has had a profound impact, leading to a momentous change in how physicians practice and interact with patients. This integration of technology and setting has not been confined just to in- / out-patient-related facilities but has rapidly expanded into multiple medical disciplines, including research and education. Utilizing prompt engineering, what once was only capable of well-funded institutions with large teams that spanned multiple specialties, can now be accomplished by a necessary few, closing the gap and allowing for unique opportunities for medical students and researchers alike. One such opportunity being DO student led adult programing that combines both research and education. Given that all graduating medical students are required to take, at a minimum, two continuing medical education (CME) credit hour courses over opioid prescribing relating to chronic pain, and only 20% of current med schools have pain programming; students, sought to bridge this gap with the creation of a 2 CME credit curriculum at DMU utilizing already established elective courses. A prompt was engineered to analyze the entire CDC 2022 Clinical Practice Guideline for Prescribing Opioids and group CDC recommendations that fulfilled Iowa’s Opioid Prescriber requirements. From this, 12 recommendations were formed and grouped into 4 separate modules with one lecture per module. An additional prompt was engineered to cross reference each module with each individual elective lecture and assign relevant slides to a module lecture. Slides were then optimized with original content, finalized and await approval.
