ArticleHealthcare informatics research2025
Consensus on the Potential of Large Language Models in Healthcare: Insights from a Delphi Survey in Korea.
Article in Healthcare informatics research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
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Authors and funding
2 authors.
Funding
Abstract
objectivesGiven the rapidly growing expectations for large language models (LLMs) in healthcare, this study systematically collected perspectives from Korean experts on the potential benefits and risks of LLMs, aiming to promote their safe and effective utilization.
methodsA web-based mini-Delphi survey was conducted from August 27 to October 14, 2024, with 20 selected panelists. The expert questionnaire comprised 84 judgment items across five domains: potential applications, benefits, risks, reliability requirements, and safe usage. These items were developed through a literature review and expert consultation. Participants rated their agreement or perceived importance on a 5-point scale. Items meeting predefined thresholds (content validity ratio ≥0.49, degree of convergence ≤0.50, and degree of consensus ≥0.75) were prioritized.
resultsSeventeen participants (85%) responded to the first round, and 16 participants (80%) completed the second round. Consensus was achieved on several potential applications, benefits, and reliability requirements for the use of LLMs in healthcare. However, significant heterogeneity was found regarding perceptions of associated risks and criteria for safe usage of LLMs. Of the 84 total items, 52 met the criteria for statistical validity, confirming the diversity of expert opinions.
conclusionsExperts reached a consensus on certain aspects of LLM utilization in healthcare. Nonetheless, notable differences remained concerning risks and requirements for safe implementation, highlighting the need for further investigation. This study provides foundational insights to guide future research and inform policy development for the responsible introduction of LLMs into the healthcare field.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.