  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.
