Evaluation of the Effectiveness, Safety, and Patient Satisfaction of Artificial Intelligence-Based Patient Education and Counseling for Both Recipients and Donors in the Preoperative and Postoperative Phases of Organ Transplantation

Abstract

Introduction Effective patient education is critical in organ transplantation, particularly for living donor groups, where informed decision-making impacts both donors and recipients. AI-driven solutions, such as OpenAI's ChatGPT, can enhance education by providing real-time responses. This study assessed the effectiveness, safety, and satisfaction of an AI-supported patient education system integrated with WhatsApp and a Customer Relationship Management (CRM) system. Methods A prospective observational study was conducted at our transplant center between October 1, 2023, and July 31, 2024. Eligible participants included adults (18-65 years) who were either recipients or living donor candidates for kidney and liver transplantation. AI-generated responses were retrospectively evaluated by transplant physicians for accuracy and safety using a 5-point Likert scale. Patient satisfaction was assessed using the validated Turkish Short Assessment of Patient Satisfaction (SAPS) form. Results A total of 196 patients submitted 1281 questions, categorized into nine thematic groups. The most common inquiries pertained to post-transplant social life and work resumption (25.2%). AI responses demonstrated high safety (92% scoring >= 4) and accuracy (80% scoring >= 4). The highest accuracy was for surgical technique-related questions (4.7/5), while general questions had the lowest (4.2/5). Patient satisfaction was overwhelmingly positive, with 99.5% expressing satisfaction. Conclusion The AI-supported system provided accurate and safe preoperative and postoperative education for transplant patients, demonstrating high satisfaction. AI integration into clinical workflows presents a promising advancement, though challenges related to accuracy and ethics remain. Future research should explore AI's role in image recognition and triage to optimize transplant patient care.