OBJECTIVES: Healthcare costs in the U.S. are the highest worldwide and are rapidly increasing. As a result of this upward trend, employers and health insurance companies are trying to contain the cost of healthcare. This study aimed to understand and identify several factors associated with medical reimbursement amount for Commercial and Medicare health insurance members in Southeastern Pennsylvania and surrounding counties. METHODS: Using privately insured Commercial and Medicare health plan enrollment and claims data from 2011 and 2012 for 2 million participants, this study empirically examined the impact of socio-demographic, enrollment, census data, rate relativity, utilization, risk scores and chronic diseases on medical reimbursement amount using risk adjustment and risk predictive models. The dependent variables - medical reimbursement amount, was measured separately as concurrent, prospective, and change variable (taking first difference) at each plan participant level. Regression analysis was used to examine individually and cumulatively how much variation was explained by different independent variables for Commercial and Medicare separately using adjusted R-squared. Socio-demographic variables included age, gender, and derived 2010 census variables at the ZIP code level. Separate risk scores were derived for Commercial and Medicare using DxCG’s all medical predicting concurrent medical risk. RESULTS: Among both Commercial and Medicare members, utilization (including services by inpatient, outpatient and professional) was the predominant predictor of medical reimbursement amount. Risk scores and number of chronic diseases are predictive but not as significant as utilization in terms of explanatory power. Socio-demographic variables are important predictors but only explain a small portion of the variation. CONCLUSIONS: This study examined several factors associated with medical reimbursement amount. Further research is needed to help understand what other factors are important which may help shed light on potential options for ‘bending the cost curve’.