Although Patient Health Records (PHRs) are vital tools for patients, enabling them to access and manage health information, it remains challenging for doctors and patients to gather a swift overview of a patient’s health status based on the extensive information included in the PHR. Our study introduces a generative pre-trained transformer-based language model to summarize health information documented in previously developed PHRs efficiently. By fine-tuning the model, we achieved results comparable to those of other studies in this domain, despite utilizing a smaller dataset. This data-to-text application represents a novel method that can be expected to promote enhanced information management in the medical field.