大規模言語モデルを活用したナレッジトランスレーションツールが理学療法士のガイドライン遵守に与える影響：質的フォーカスグループ調査

Clinical practice guidelines support healthcare professionals in making evidence-based decisions, yet guideline adherence among physical therapists remains inconsistent. To address this gap, a prototype digital knowledge translation tool powered by a large language model (LLM) was developed, with content based on two exemplary high-quality German national guidelines.

To (1) explore the experiences of German physical therapists using the tool, (2) assess their perspectives on its utilization in clinical practice, and (3) compare perceptions between outpatient and inpatient settings.

Six focus group interviews were conducted: three in a university hospital inpatient setting and three in outpatient physical therapy practices. Discussions were analyzed using qualitative content analysis with inductive and deductive coding.

Twenty physical therapists (11 inpatient, 9 outpatient) participated. Overall experiences were positive, though prolonged response times were criticized. Utilization was thought to depend on time availability and workplace digitization. The tool's potential assisting with clinical questions was highlighted. No considerable differences in experiences across settings were noted. Inpatient therapists envisioned using the tool between sessions for personal knowledge enhancement, whereas outpatient therapists anticipated utilization during sessions for patient education.

LLM-based knowledge translation tools may contribute to improving guideline adherence among physical therapists. Successful implementation requires assessment of digital infrastructure, relevance to clinical needs, and users' digital literacy. Further research should evaluate the quality of LLM-generated summaries to ensure validity and trustworthiness, and optimize the tools' usability regarding speed and content. Development should also prompt ethical considerations about their role in clinical decision-making and patient care.