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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.
ChatGPT demonstrates 70.7% accuracy on the EU*US eHealth Work Foundational Curriculum, showing potential for health information technology education. Further enhancements are needed for comprehensive eHealth competency coverage.
Area of Science:
- Health Informatics
- Artificial Intelligence in Education
Background:
- The EU*US eHealth Work Foundational Curriculum offers a comprehensive framework for eHealth learning.
- Assessing AI's capability in understanding and responding to complex health informatics curricula is crucial.
Purpose of the Study:
- To evaluate the performance of OpenAI's ChatGPT (GPT-3.5 model) in answering questions based on the EU*US eHealth Work Foundational Curriculum.
- To determine the accuracy and consistency of ChatGPT's responses to health information technology competencies.
Main Methods:
- Utilized 321 questions from the Health Information Technology Competencies (HITCOMP) self-assessment quiz.
- Presented each question to ChatGPT three times to evaluate response consistency.
- Analyzed the accuracy of ChatGPT's answers across 21 curriculum modules.
Main Results:
- Achieved an overall accuracy of 70.7% in responding to the eHealth curriculum questions.
- Demonstrated a reasonable understanding of eHealth topics but with performance variability across modules.
- GPT-3.5 model showed consistency in its responses when questions were repeated.
Conclusions:
- ChatGPT shows significant potential as a tool in health information technology education.
- Current performance indicates a need for further AI model development to fully cover eHealth competencies.
- The study highlights the evolving role of AI in specialized educational frameworks.
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