Abstract

Background

In a recent survey, medical students expressed eagerness to acquire competencies in the use of artificial intelligence (AI) in medicine. It is time that undergraduate medical education takes the lead in helping students develop these competencies. We propose a solution that integrates competency-driven AI instruction in medical school curriculum.

Methods

We applied constructivist and backwards design principles to design online learning assignments simulating the real-world work done in the healthcare industry. Our innovative approach assumed no technical background for students, yet addressed the need for training clinicians to be ready to practice in the new digital patient care environment. This modular 4-week AI course was implemented in 2019, integrating AI with evidence-based medicine, pathology, pharmacology, tele-monitoring, quality improvement, value-based care, and patient safety.

Results

This educational innovation was tested in 2 cohorts of fourth year medical students who demonstrated an improvement in knowledge with an average quiz score of 97% and in skills with an average application assignment score of 89%. Weekly reflections revealed how students learned to transition from theory to practice of AI and how these concepts might apply to their upcoming residency training programs and future medical practice.

Conclusions

We present an innovative product that achieves the objective of competency-based education of students regarding the role of AI in medicine. This course can be integrated in the preclinical years with a focus on foundational knowledge, vocabulary, and concepts, and in clinical years with a focus on application of core knowledge to real-world scenarios.

Details

Title

Grounded in reality: artificial intelligence in medical education

Author

Krive, Jacob¹

; Isola, Miriam¹

; Chang, Linda²; Patel, Tushar³; Anderson, Max⁴; Sreedhar, Radhika⁵

¹ Department of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago , Chicago, Illinois, USA
² Department of Family and Community Medicine, University of Illinois College of Medicine Rockford , Rockford, Illinois, USA
³ Department of Pathology, University of Illinois College of Medicine , Chicago, Illinois, USA
⁴ Department of Medical Education, University of Illinois College of Medicine , Chicago, Illinois, USA
⁵ Department of Medicine, University of Illinois College of Medicine , Chicago, Illinois, USA

Publication year

2023

Publication date

Jul 2023

Publisher

Oxford University Press

e-ISSN

25742531

Source type

Scholarly Journal

Language of publication

English

DOI

https://doi.org/10.1093/jamiaopen/ooad037

ProQuest document ID

3168347463

© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. This work is published under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.