AI Trains Doctors to Refute Medical Myths with Empathy, Improving Patient Care

Generative AI is helping medical students and doctors employ the Empathetic Refutational Interview (ERI) technique when addressing patients’ medical misconceptions. The ERI approach aims to refute misinformed beliefs while maintaining empathy and understanding for patients’ underlying motivations.

Key elements of the ERI technique: The ERI consists of four steps: eliciting concerns, affirming the patient’s perspective, offering a tailored refutation, and providing factual information:

• Eliciting concerns involves inviting the patient to share their thoughts, actively listening, and gently seeking to discover the roots of their beliefs and motivations.
• Affirming involves showing empathy for the patient’s position, acknowledging partial truths, and softly building trust while avoiding endorsement of false beliefs.
• Offering a tailored refutation entails providing a believable and acceptable alternative, addressing the patient’s underlying motivation, and going beyond simply reciting facts.
• Providing factual information involves adding further evidence to support the refutation, taking advantage of the patient’s heightened receptivity after completing the prior steps.

Applying Lewin’s model of change to the ERI: The author suggests adding a fifth step to the ERI, drawing from Kurt Lewin’s three-stage model of change (unfreezing, moving, and freezing):

• The proposed fifth step, “Empathetically Confirm Results,” aims to seal the deal and make a lasting impression on the patient by mirroring the empathy of the first four steps and bringing a polite, fitting conclusion to the medical recommendations.

Showcasing the ERI technique using generative AI: The author demonstrates how generative AI, specifically ChatGPT, can be used to train medical students and doctors in applying the ERI technique:

• By providing the AI with a description of the four-step process, it can generate sample dialogues between a patient and a doctor, showcasing how the ERI technique can be employed to address various medical misconceptions.
• The AI can also engage in interactive conversations, playing the role of either the doctor or the patient, allowing users to practice the ERI technique and receive feedback on their performance.

Broader implications: The use of generative AI to train medical professionals in empathetic communication techniques, such as the ERI, has the potential to improve doctor-patient relationships and healthcare outcomes:

• By leveraging AI’s availability, cost-effectiveness, and instant feedback capabilities, medical students and healthcare professionals can practice and refine their empathetic communication skills in a safe, accessible environment.
• Mastering techniques like the ERI can help doctors build trust, foster better patient adherence to medical recommendations, and ultimately provide higher-quality care.