Effect on comprehension of an AI patient-friendly hospital discharge letter: a quasi-RCT

Abstract Background During transition from hospital to home care, discharge letters serve as a bridge of information between hospital physicians, general practitioners, and patients. However, the complexity of these letters often hinders patient comprehension, leading to medication errors and adverse outcomes. We assessed the effect on patients’ comprehension and satisfaction of using AI to transform discharge letters into patient-friendly versions. Methods An online quasi-randomized controlled parallel-group trial was conducted in Italy. A synthetic discharge letter for a chronic obstructive pulmonary disease patient was drafted. GPT-4 rephrased the letter into an easier-to-understand version. Participants were assigned to receive either the original or AI-generated letter and completed comprehension assessments and satisfaction survey. Results Out of 460, 166 participants received the original letter, and 175 the AI version. The AI group showed significantly higher comprehension scores (median 4;IQR 2-4 vs. 2; IQR1-2, p < 0.001) and outperformed the control group in understanding diagnosis, medications, and antibiotic instructions. Perceived satisfaction was higher in the AI group across all measures (p < 0.001). Health literacy was a good predictor of comprehension in both arms (p = 0.013; p = 0.015). Subgroup analysis revealed the AI letter nearly bridged the comprehension gap between non-healthcare individuals and healthcare professionals receiving the original letter. Conclusions AI-optimized discharge letters improved patient understanding, and satisfaction compared to traditional letters. The study underscores the influence of sociodemographic factors like healthcare experience and health literacy on comprehension, advocating for adaptive communication strategies. These findings contribute to discussions about integrating AI in healthcare to develop patient-centered communication approaches. Key messages • AI-generated patient-friendly discharge letters significantly improved comprehension and satisfaction compared to traditional letters. • Integrating AI in healthcare communication can help bridge comprehension gaps and promote patient-centered care.