Modeling Hospital Costs Using the Generalized Gamma Additive Model

The Generalized Gamma (GG) is a flexible distribution in statistical literature with the special cases of exponential, gamma, Weibull and lognormal distributions. This paper proposes the GG additive model for modeling hospital claim costs. Compares to other models, the GG is more flexible and has a better performance in modeling positive skewed data. The proposed model is fitted to the hospital costs data from the Nationwide Inpatient Sample of the Healthcare Cost and Utilization Project (NIS-HCUP), a nationwide survey of hospital costs conducted by the U.S. Agency for Healthcare Research and Quality (AHRQ). The results show that the claim coasts affected by the given explanatory variables and based on the AIC and BIC criterion, The GG has a better fit for the given data compared to the Gamma, Weibull and log-normal models.