In this paper, we will explain critical illness insurance calculations with stochastic interest rates. The survival model is multiple states, while the interest rate is the Cox-Ingersoll-Ross stochastic interest rate model. In determining the survival model, we use the prevalence and mortality rates of certain critical diseases, such as neoplasms, endocrine diseases, and diseases of the digestive system. Furthermore, the Monte Carlo simulation will be used to simulate the possibility of interest rate pathways in determining critical illness insurance premiums.
This paper describes the construction of morbidity-mortality table if the dataset is only available at ages interval. The table used to measure the interaction between morbidity and mortality on the eleven chronical diseases (ECD). The probabilistic framework is based on the multiple-states Markov model. The transition intensities are assumed constant in each age interval. This paper finds high probability someone stays in state ECD and higher probability someone dies because of ECD than other causes.
In this paper we will discuss the dynamic model of Indonesian National Health Insurance (JKN) participation number. In this model, we divide JKN participation types into three categories: PBPU, PBI and PPU. The dynamic model is built using ordinary differential equation (ODE) system from a multiple states model that describes the transition of JKN participation types from time to time. The parameters of the model are estimated from data that is refined by an exponential smoothing time series method. As a result, the estimated number of JKN participation for each type until 2045 is obtained.
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