Enhancing Patient Participation in Emergency Department through Patient-Friendly Clinical Notes Generated by Large Language Models

Background To achieve patient-centered care (PCC), it is essential to provide patients with sufficient information about their medical conditions and treatment processes to actively engage in their care. However, the busy and crowded nature of the emergency department (ED) setting, combined with differences in communication styles, varying levels of health literacy, and other barriers between clinicians and patients, makes effective communication and participation challenging. Recent studies have focused on applying large language model (LLM) technologies to create patient-friendly documents that present patients’ medical information in plain language with the goal of enhancing patient understanding and participation. Nevertheless, further research is needed to evaluate the impact of LLM-generated patient-friendly documents on improving patient participation, particularly in high-pressure settings like the ED. Objective This study aimed to develop patient-friendly clinical notes (PFCNs) generated by LLM, which transform clinicians’ clinical notes into patient-friendly documents for use in ED consultations, and to evaluate whether PFCNs could enhance patient participation. Methods A preliminary study was conducted to identify the contents, format, and scenarios of PFCNs in the ED setting by conducting individual interviews with patients (n = 9) and clinicians (n = 7). Based on these findings, we developed a system which generates PFCNs using the GPT-4o model, transforming clinicians’ clinical notes from ED consultations into patient-friendly documents through zero-shot learning. To evaluate the efficacy of PFCNs, we conducted a simulated ED consultation role-play with patients (n = 20) and clinicians (n = 10), who were provided with PFCNs. After the simulations, the participants completed the scales to assess the quality of the documents and patient participation questionnaires (PPQ) during pre- and post- simulations, followed by post-individual interviews to explore how PFCNs supported patient participation. Results We confirmed that the LLM successfully generated PFCNs (n = 120) suitable for patient comprehension, as indicated by a Patient Education Materials Assessment Tool (PEMAT) understandability score of 87.2 (> 70%) validated by both clinicians and patients. Compared to previous ED visits without PFCNs, patients who received the documents demonstrated a significantly higher PPQ scale ( P  < 0.05). In line with the quantitative results in patients’ participation, post-interview results revealed that PFCNs supported communication with clinicians, improved understanding of clinical information, provided emotional reassurance, and strengthened patient-clinician relationships. However, two key challenges were identified regarding the content and utility of the documents: (1) potential risks from inaccuracies in PFCNs and (2) differing perspectives between patients and clinicians on the documents. Based on these findings, we suggested practical strategies for implementing PFCNs in ED settings. Conclusions This study demonstrates that PFCNs enhanced patient participation in ED consultations, supporting patient communication, decision-making, and relationship-building with healthcare providers. These findings suggest that PFCNs not only promote patient-centered care by supporting active patient participation but also have the potential to improve ED consultation and workflow effectively.