GENERATIVE ARTIFICIAL INTELLIGENCE ADOPTION AND IMPLEMENTATION BARRIERS IN KOREAN MEDICINE PRACTICE: A NATIONWIDE SURVEY
Author(s)
anna kim, Dr1, MIJU SON, Dr2, Youngeun Kim, MS2, sumin seo, Dr2, Sang-Kyun Kim, Dr2.
1Korea Institute of Oriental Medicine, daejeon, Korea, Republic of, 2Korea Institute of Oriental Medicine, Daejeon, Korea, Republic of.
1Korea Institute of Oriental Medicine, daejeon, Korea, Republic of, 2Korea Institute of Oriental Medicine, Daejeon, Korea, Republic of.
OBJECTIVES: Generative artificial intelligence (AI) is increasingly being adopted in healthcare. However, evidence regarding its real-world use and implementation challenges in Korean medicine remains limited. This study aimed to investigate the current use, perceptions, barriers, and clinical needs related to generative AI among Korean medicine doctors (KMDs) in South Korea.
METHODS: A nationwide cross-sectional online survey was conducted among licensed KMDs in November 2025. Participants were recruited via text message through the Association of Korean Medicine. The survey assessed respondent characteristics, AI use patterns, perceptions, satisfaction, AI literacy, and perceived barriers to clinical implementation.
RESULTS: Among 404 respondents, 283 (70.0%) reported currently using generative AI in clinical practice. The most common applications were literature and information retrieval (73.9%), diagnostic support (44.9%), and preparation of patient education materials (33.9%). Despite widespread adoption, only 33.7% of respondents reported a high or very high level of AI understanding, with significantly lower self-rated understanding among older and more experienced clinicians. Although 343 respondents (84.9%) expressed positive expectations regarding AI in clinical practice, major barriers included concerns about AI accuracy and reliability (65.1%), patient data security (37.1%), and insufficient knowledge of AI use (34.2%).
CONCLUSIONS: Generative AI has been widely adopted among Korean medicine doctors despite persistent concerns regarding reliability, privacy, and limited AI literacy. These findings support the need for evidence-based, Korean medicine-specific AI systems supported by structured education and governance.
METHODS: A nationwide cross-sectional online survey was conducted among licensed KMDs in November 2025. Participants were recruited via text message through the Association of Korean Medicine. The survey assessed respondent characteristics, AI use patterns, perceptions, satisfaction, AI literacy, and perceived barriers to clinical implementation.
RESULTS: Among 404 respondents, 283 (70.0%) reported currently using generative AI in clinical practice. The most common applications were literature and information retrieval (73.9%), diagnostic support (44.9%), and preparation of patient education materials (33.9%). Despite widespread adoption, only 33.7% of respondents reported a high or very high level of AI understanding, with significantly lower self-rated understanding among older and more experienced clinicians. Although 343 respondents (84.9%) expressed positive expectations regarding AI in clinical practice, major barriers included concerns about AI accuracy and reliability (65.1%), patient data security (37.1%), and insufficient knowledge of AI use (34.2%).
CONCLUSIONS: Generative AI has been widely adopted among Korean medicine doctors despite persistent concerns regarding reliability, privacy, and limited AI literacy. These findings support the need for evidence-based, Korean medicine-specific AI systems supported by structured education and governance.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
RWD3
Topic
Health Technology Assessment, Real World Data & Information Systems
Disease
Alternative Medicine