AI prioritizes connection with patients instead of solely focusing on generating reports

In the realm of healthcare, radiology leaders are exploring innovative ways to improve patient portals and anticipate questions, with the help of AI tools such as RadGPT. This technology, developed by Stanford University, generates concept-based explanations to make imaging findings more understandable for patients.

RadGPT has the potential to revolutionise patient-facing AI applications, extending beyond medical imaging to areas like pathology reports, cardiology studies, and orthopedic evaluations. By providing patients with a basic understanding of their results, RadGPT enables radiologists to devote more time to offering analysis, planning treatments, and building relationships.

The 21st Century Cures Act mandated transparency in radiology reports, but this has often resulted in confusion rather than empowerment for patients. RadGPT aims to address this issue by personalising educational content to match patients' literacy levels and preferences. This approach could lead to improved patient satisfaction, engagement, and outcomes.

However, the adoption of AI in healthcare is not without challenges. Balancing innovation and strict attention to safety, accuracy, and regulatory compliance is crucial. The technology must be rigorously tested, monitored, and designed with built-in safeguards to prevent misinterpretation.

Moreover, there are no standard protocols or best practices for implementing a program that leverages patient-facing AI tools. Successfully launching an initiative requires a holistic approach that positions AI to serve the entire care ecosystem.

Jordan Bazinsky, CEO of Intelerad, acknowledges the potential of RadGPT, but stresses that the goal is to enhance, not replace, communication between radiologists and patients. The technology is intended to be a tool that aids in bridging the gap in understanding between medical professionals and patients, ultimately leading to more informed and active participation in treatment decisions.

RadGPT's translation capabilities also demonstrate an opportunity to reimagine patient engagement through AI-powered communication tools. As the future of healthcare continues to evolve, solutions that advance both provider efficiency and patient confidence will be essential, not just for medical imaging, but as a model for the industry as a whole.