Bandit-supported care planning for older people with complex health and care needs

• Published in: 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS) pp. 1 - 5
• Main Authors: Kim, Gi-Soo, Hong, Young Suh, Hoon Lee, Tae, Paik, Myunghee Cho, Kim, Hongsoo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 11.06.2023
• Subjects: Adaptation models; Aging; Artificial intelligence; Circuits and systems; Data models; Medical services; Planning
• DOI: 10.1109/AICAS57966.2023.10168530

Long-term care service for old people is in great demand in most of the aging societies. The number of nursing homes residents is increasing while the number of care providers is limited. Due to the care worker shortage, care to vulnerable older residents cannot be fully tailored to the unique needs and preference of each individual. This may bring negative impacts on health outcomes and quality of life among institutionalized older people. To improve care quality through personalized care planning and delivery with limited care workforce, we propose a new care planning model assisted by artificial intelligence. We apply bandit algorithms which optimize the clinical decision for care planning by adapting to the sequential feedback from the past decisions. We evaluate the proposed model on empirical data acquired from the Systems for Person-centered Elder Care (SPEC) study, a ICT-enhanced care management program.