抄録
In Japan, National healthcare expenditure in 2015 was 42,364.4 billion yen, 3.8% more than the previous year, which indicates a significant problem. As diabetes becomes severe, it costs a lot for dialysis and medication. As the population with diabetes is increasing and diabetes is a risk factor causing complications, it is necessary to undertake efforts to ensure that diabetes does not lead to severe illness. In this study, we construct a simulation with a Markov chain on diabetes, which will become an increasingly important issue in the future. First, we create state distribution using eGFR and urine protein. The initial distribution first uses eGFR and urine protein tested values. The final distribution uses the last inspection value existing as data. We calculate the average inspection period from the data and make it the unit period of the Markov chain. We calculate the transition probability matrix from the inspection data and observe the state transition by stationary distribution and simulation. This simulation clarifies the progressive severity of diabetes, making it easier to deal with stages leading to severe illness. Simulations are categorized according to patient attributes and implemented so that they can be applied in many cases.
https://ror.org/00vq1d511 
