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Evaluating ChatGPT's Performance in the EU*US eHealth Work Foundational Curriculum Using the HITCOMP Self-Assessment
Chun-Wei Liu1,2, Zu-Chun Lin1, Malcolm Koo1
1Dept. of Nursing, Tzu Chi University of Science and Technology, Hualien, Taiwan.
Abstract:
This study investigated the performance of OpenAI's Chat Generative Pre-trained Transformer (ChatGPT) in responding to the EU*US eHealth Work Foundational Curriculum. This curriculum, a collaborative effort between European and U.S. institutions, provides an extensive framework for eHealth learning. The assessment involved 321 questions from the online Health Information Technology Competencies (HITCOMP) self-assessment quiz. Using GPT-3.5 model, the study presented each question three times to assess ChatGPT's consistency. Findings revealed an accuracy of 70.7%, indicating a reasonable grasp of eHealth topics, although performance was uneven across the 21 modules. These results underscore ChatGPT's potential in health information technology education and highlight the need for further model enhancements to fully encompass eHealth competencies.
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