JMIR Publications

ABSTRACT

Background:

While the global medical AI market is growing rapidly alongside the Fourth Industrial Revolution, the utilization of AI in actual medical settings remains in its early stages due to a shortage of skilled personnel and a lack of systematic education.

Objective:

This study aims to identify the essential medical AI competencies required of healthcare professionals by job category in the era of digital transformation, and to derive a standardized education system and policy support measures to effectively cultivate these competencies.

Methods:

After designing an initial model through a literature review, two rounds of Delphi surveys were conducted with a multidisciplinary panel of experts (N=9–10) covering fields such as medical informatics, healthcare management, and clinical medicine. The validity of the competency model and education system was verified by analyzing the Content Validity Ratio (CVR) and consensus.

Results:

The Delphi survey identified 16 core competencies that all job categories must possess in common; among these, 'medical data security' and 'basic principles of AI' demonstrated the highest importance. In addition, advanced competency models reflecting the specific characteristics of each job function were established, including physicians (clinical validity review), nurses (results interpretation and communication), medical technicians (data quality management), and medical administrators (data governance). Based on this, a five-stage standard education system—'Introduction-Basic-Advanced-Practice-Project'—based on blended learning was defined.

Conclusions:

This study is significant in that it departs from existing technology development-centered education and presents a practical competency model centered on 'application' and 'safety.' To disseminate the research results, policy recommendations were presented, including the introduction of a 'National Standard Medical AI Competency Certification System,' the establishment of 'Regional Medical AI Education Hubs,' and institutional linkages with existing continuing education and undergraduate education. Clinical Trial: Not applicable. This study was conducted in accordance with the Declaration of Helsinki. The study protocol was reviewed and granted an exemption from formal review by the Institutional Review Board (IRB) of the Korea Human Resource Development Institute for Health and Welfare (IRB No. 2025-EX-07), as it involved the secondary analysis of pre-existing, de-identified data collected during the “Medical AI In-service Education for Healthcare Professionals” program commissioned by the Ministry of Health and Welfare. Regarding the consent to participate, the requirement for informed consent was waived by the same IRB (Korea Human Resource Development Institute for Health and Welfare) because the research used anonymized data collected for educational consulting and quality improvement purposes, involving no additional participant recruitment or intervention.