LAUSR

Abstract The burden of elder care is increasing rapidly due to an aging society. Elder care services are expensive and becoming more so in the US. Financing elder care services with available financial products is an important task in healthcare management. In this article, a Continuous-Time Markov Chain (CTMC) model is proposed to capture health risk transitions. The transition probabilities among care stages and length of stay (LOS) at each care stage are estimated using historical data for elders with a specific health condition. Financial decision support is formulated as an optimization problem with maximum service-level fulfillment rate of an elder given his/her health profile and financing options. A case study is conducted using a heart transplant monitoring dataset. The patterns of optimal financing decisions are investigated. The results show a clear advantage to making financing decisions based on an elderly person’s personal health profile.