多指标可加模型及在医疗费用预测中的应用

Multi-index Additive Model and Its Application in Medical Cost Forecast

对医疗费用的建模分析与合理预测是医疗保险费用厘定的基础与根本.医疗费用中的高维附加信息在长期预测中具有重要作用.然而,传统的统计建模方法不适用于处理高维纵向数据下的医疗费用.本文提出部分线性多指标可加模型,对具有高维特征的纵向医疗费用数据进行拟合与预测,并且使用两种不同的降维估计方法进行模型估计,并将该模型应用于一组含高维协变量的纵向医疗费用数据中进行实例分析.结果表明该模型以及两种不同的降维方法均对纵向医疗费用进行了很好的拟合.

Modeling analysis and reasonable prediction of medical costs are the basis and foundation for the determination of medical insurance costs.High-dimensional additional information in medical costs plays an important role in long-term prediction.This paper proposes a partial linear multi-indicator additive model to fit and predict longitudinal medical cost data with high-dimensional features and uses two different dimensionality reduction estimation methods to estimate the model and applies the model to a set of high-dimensional dimensions.The longitudinal medical cost data of the variable is used for case analysis.