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Improving the Readability of Institutional Heart Failure-Related Patient Education Materials Using GPT-4:

Ryan C King1, Jamil S Samaan2, Joseph Haquang1

  • 1Department of Medicine, Division of Cardiology, University of California, Irvine Medical Center, 101 The City Dr S, Orange, CA, 92868, United States, 1 714-456-7890.

JMIR Cardio
|July 8, 2025
PubMed

Insights

Large language models like GPT-4 can simplify heart failure patient education materials, improving readability and comprehension for better self-management. This AI tool enhances educational content accuracy and comprehensiveness for heart failure patients.

Area of Science:

  • Medical Informatics
  • Health Literacy
  • Artificial Intelligence in Healthcare

Background:

  • Heart failure management requires patient adherence to lifestyle changes, emphasizing the need for clear Patient Education Materials (PEMs).
  • Existing cardiovascular PEMs often present information at a reading level exceeding recommended standards, hindering patient understanding.
  • Large Language Models (LLMs) show potential for enhancing the accessibility of health information.

Purpose of the Study:

  • To evaluate the readability of heart failure PEMs from leading cardiology institutions.
  • To assess GPT-4's capability in improving PEM readability while maintaining accuracy and comprehensiveness.

Main Methods:

  • Collected 143 heart failure PEMs from top US cardiology institutions.
  • Utilized GPT-4 to simplify PEMs using a standardized prompt.
  • Assessed readability using multiple metrics (Flesch Reading Ease, FKGL, etc.).
  • Evaluated revised PEMs for accuracy and comprehensiveness by a cardiologist.

Main Results:

  • GPT-4 significantly reduced the median Flesch-Kincaid Grade Level from 10.3 to 7.3 (p<.001).
  • The proportion of PEMs below a sixth-grade reading level increased from 9.1% to 23.1% after GPT-4 revision (p<.001).
  • No reduction in accuracy or comprehensiveness was observed; 23.1% of revised PEMs were deemed more comprehensive.

Conclusions:

  • GPT-4 effectively enhances the readability of heart failure PEMs.
  • LLMs may serve as valuable tools to supplement healthcare professional guidance for heart failure patients.
  • Further research is essential to validate the safety, efficacy, and impact of AI in improving patient health literacy.
Abstract

Keywords:
ChatGPTGPT-4artificial intelligencehealth literacyheart failurelarge language modelspatient educationreadability

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