Health care providers are being pressured to lower the cost of care. Because of the inherent cost variability in providing health care, as reimbursement falls, providers may not be able to cover all costs. Understanding the underlying causes of this wide variability is important in determining optimum pricing. Prior studies on the cost of coronary bypass surgery have determined which clinical variables affect cost, yet none have studied nonclinical variables that can influence the cost of coronary bypass surgery.
In a cohort of 882 consecutive patients with treatment classified in the diagnosis-related group (DRG) 107, we examined 55 clinical and nonclinical variables obtained from our prospective database. For explanatory purposes, we used multiple linear regression to determine the variables that were predictive of direct cost and the magnitude of contribution of each variable.
Eleven clinical and 4 nonclinical variables were predictive of direct cost. Nonclinical variables added significant cost-predictive information beyond that of the traditional clinical variables, and their magnitude of effect was equal to or greater than the traditional clinical variables.
Nonclinical patient characteristics add important predictive information concerning the cost of coronary bypass surgery to traditional clinical variables. These data will be important in developing contracting strategies, in the evaluation of individual physician performance, and in modifying national methods of reimbursement.