估算社会照护的终身成本:基于三个地理区域关联行政数据的贝叶斯方法

Estimating Lifetime Costs of Social Care: A Bayesian Approach Using Linked Administrative Datasets from Three Geographical Areas

Health Economics · 2014
被引 4
人大 A-

中文导读

利用英格兰三个地区的关联行政数据,通过贝叶斯方法估算65岁人群的终身社会照护成本,发现区域间成本差异显著,对保险产品设计有参考价值。

Abstract

We estimated lifetime costs of publicly funded social care, covering services such as residential and nursing care homes, domiciliary care and meals. Like previous studies, we constructed microsimulation models. However, our transition probabilities were estimated from longitudinal, linked administrative health and social care datasets, rather than from survey data. Administrative data were obtained from three geographical areas of England, and we estimated transition probabilities in each of these sites flexibly using Bayesian methods. This allowed us to quantify regional variation as well as the impact of structural and parameter uncertainty regarding the transition probabilities. Expected lifetime costs at age 65 were £20,200-27,000 for men and £38,700-49,000 for women, depending on which of the three areas was used to calibrate the model. Thus, patterns of social care spending differed markedly between areas, with mean costs varying by almost £10,000 (25%) across the lifetime for people of the same age and gender. Allowing for structural and parameter uncertainty had little impact on expected lifetime costs, but slightly increased the risk of very high costs, which will have implications for insurance products for social care through increasing requirements for capital reserves.

社会护理终身成本贝叶斯方法行政数据链接区域差异