PRECISE Framework: GPT-based Text For Improved Readability, Reliability, and Understandability of Radiology Reports For Patient-Centered Care

TL;DR

The PRECISE framework employs GPT-4 to transform radiology reports into clearer, more accessible language at a sixth-grade level, significantly improving patient understanding and engagement in healthcare decisions.

Contribution

This paper presents a novel GPT-4 based framework that enhances radiology report readability and reliability for patient-centered care, validated on 500 reports.

Findings

Significant improvement in report readability and understandability

Enhanced patient engagement and trust in healthcare decisions

Framework demonstrated effectiveness across a large report dataset

Abstract

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.