PRECISE Framework: GPT-based Text For Improved Readability, Reliability, and Understandability of Radiology Reports For Patient-Centered Care
This addresses patient engagement in healthcare by making radiology reports more accessible, though it is incremental as it applies an existing AI model to a specific medical domain.
The study tackled the problem of unclear radiology reports by developing the PRECISE framework using GPT-4 to generate chest X-ray reports at a sixth-grade reading level, testing it on 500 reports and showing significant improvements in readability, reliability, and understandability.
This study introduces and evaluates the PRECISE framework, utilizing OpenAI's GPT-4 to enhance patient engagement by providing clearer and more accessible chest X-ray reports at a sixth-grade reading level. The framework was tested on 500 reports, demonstrating significant improvements in readability, reliability, and understandability. Statistical analyses confirmed the effectiveness of the PRECISE approach, highlighting its potential to foster patient-centric care delivery in healthcare decision-making.