This study aims to model and quantify long-term care demands for dementia patients by analyzing their health state transitions and survival durations.Utilizing data from Korean Long-Term Care Insurance (K-LTCI) system provided by the National Health Insurance Service, we applied a multi-state modeling framework to examine the transition dynamics among care levels for individuals diagnosed with dementia.Transition probability matrices and state-specific life expectancies were estimated by sex, age group, and care level.The results indicate that individuals in relatively mild conditions exhibit a strong tendency to remain in the same state, while those in more severe states show lower stability and a markedly higher probability of transitioning to death.Furthermore, even within the same age and care level, substantial differences in life expectancy were observed by sex, with female beneficiaries consistently exhibiting longer survival durations.The estimated transition probabilities and life expectancy metrics derived from this study have practical implications for rate setting of dementia-specific insurance products, forecasting care demands for public LTCI schemes, and the design of personalized care strategies.Future research may extend this framework by integrating both care utilization and cost components, as well as differentiating between types of care (In-Home vs. Facility), thereby enabling the development of more refined predictive models.
Oh et al. (Tue,) studied this question.