Healthcare cost prediction based on multifactorial linear regression

In general, healthcare spending mainly refers to medical insurance, which keeps raising from 1970 to 2020. Therefore, it is crucial to predict the costs accurately. Based on the multivariate linear regression, this paper constructs a quantitative model to investigate the cost of medical care. The data used for research were gathered from Massachusetts health insurance centre. To avoid overfitting effects and simplify the model, only parts of the variables were chosen for prediction model. In the research, the Y variable was changed into log(y), and all X variables were used to fit a linear regression model. According to the analysis, the healthcare cost has a significant relationship with smoking. These results shed light on guiding further research exploring the healthcare cost.