2024 Volume 15 Issue 1 Pages 43-52
This study employs a stochastic simulation model to examine the level of care adjustments required to increase the 5‐year survival rate, with the aim of extending the healthy life expectancy of individuals certified as requiring long‐term care under long‐term care insurance. To achieve this, we began by creating a hypothetical dataset comprising of 10,000 individuals, serving as a reference group for probabilistic 5‐year care needs. Additionally, a data set was generated in which the survival rate after five years was 1% higher than that of the normal group after adjusting for mortality in each year, and this was designated as the treatment group. To eliminate the risk of data instability and mitigate uncertainty‐related outliers, we generated the hypothetical data sets 100 times each and compared the results using descriptive statistics between the reference and treatment groups. The results suggest that, in order to improve the 5‐year survival rate by 1% in each level of care, the population within each level of care needs to increase by a maximum of approximately 2.1% after five years. To contribute to the establishment of a social security system that enables safe and secure living for the elderly, it is necessary to develop a prediction model using prognostic variables such as age and gender, and to evaluate its external validity, including empirical validation. Once its external validity is confirmed, the model can be applied to various studies, such as assessing the impact of specific long‐term care services on individuals requiring care and their cost‐effectiveness. Furthermore, we believe that this research will lead to better living conditions for seniors and the curbing of social security costs.
