Enhancing Long-Term Care Efficiency: Embedded LLMs for Clinical Report Summarization and Caregiver Support

Long-term care facilities face a critical shortage of nursing staff and an increasing administrative burden, reducing time for direct patient care. Generative artificial intelligence offers a promising solution to automate administrative tasks and support caregivers. This paper evaluates the relevance of using a fine-tuned large language model (LLM) to address these challenges. Interviews with healthcare professionals identified key needs, leading to the selection of two use cases: caregiver-patient communication assistance and medical record summarization. To comply with privacy and security constraints, the model was deployed in an embedded scenario. Performance evaluations showed significant improvements in BLEU and ROUGE metrics for both use cases, demonstrating enhanced accuracy. This study demonstrates the feasibility of leveraging LLMs to streamline workflows, reduce administrative strain, and improve operational efficiency. This work highlights the potential for broader AI applications in long-term care, paving the way for better working conditions for caregivers and improved patient care quality.