Prediction of Cost for Medical Care Insurance by Using Regression Models

Medical care is an essential part of every individual and will be utilized during their lifetime; to obtain the healthcare facilities, the expenditure plays a major role. An estimate of 514 million people was assured health insurance plans in India in the year 2021. As the number of in-patient days increases, there is an incremental rise in the medical expense. Insurance ensures protection and avoids risk of a financial loss, by aggregating a sum of money by an individual for a particular cause; therefore, medical insurance can offer financial security during a medical emergency. The objective of this paper is to build a regression-based machine learning model to analyse and predict medical expenses based on factors of age, smoking habits, BMI, gender, and region. In this research, several traditional regression models’ performances were studied for the healthcare insurance data. Random forest regressor performed the best among all the algorithms with the R-squared score of 0.8643297.