Nursing Care of People with Dementia for Toilet Use by Using Large Language Models

With the number of people with dementia (PwD) increasing worldwide, the need for support for caregivers is growing. However, the burden on caregivers is exceptionally high for care related to elimination. Because toileting is generally performed in private rooms, caregivers cannot share their knowledge with other caregivers. Therefore, this study focused on creating a care suggestion system that generates care methods based on expert knowledge by extracting highly relevant information using retrieval-augmented generation (RAG) and providing it to a generative pretrained transformer (GPT) using knowledge regarding toileting care for people with dementia (PwD). The documents containing knowledge of care for PwD and the questions were vectorized, and prompts were provided with documents that were similar to the questions. Three types were prepared: a case in which only GPT was used, a case in which all information was provided, and a case in which the proposed method was used. To evaluate the proposed method, an experiment was conducted with nurses with experience in dementia nursing or gerontological nursing care. Five items were set for the three types of responses generated, and each item was rated on a 5-point scale. The results indicated the usefulness of using RAGs to obtain suggestions for care methods.