Hospital variability in modifiable factors driving coronary artery bypass charges.

OBJECTIVE:Coronary artery bypass grafting is associated with significant interhospital variability in charges. Drivers of hospital charge variability remain elusive. We identified modifiable factors associated with statewide interhospital variability in hospital charges for coronary artery bypass grafting. METHODS:Charge data were used as a surrogate for cost. Society of Thoracic Surgeons data from Maryland institutions and charge data from the Maryland Health Care Commission were linked to characterize interhospital charge variability for coronary artery bypass grafting. Multivariable linear regression was used to identify perioperative factors independently related to coronary artery bypass grafting charges. Of the factors independently associated with charges, we analyzed which factors varied between hospitals. RESULTS:A total of 10,337 patients underwent isolated coronary artery bypass grafting at 9 Maryland hospitals from 2012 to 2016, of whom 7532 patients were available for analyses. Mean normalized charges for isolated coronary artery bypass grafting varied significantly among hospitals, ranging from $30,000 to $57,000 (P < .001). Longer preoperative length of stay, operating room time, and major postoperative morbidity including stroke, renal failure, prolonged ventilation, reoperation, and deep sternal wound infection were associated with greater hospital charges. Incidence of major postoperative events, except stroke and deep sternal wound infection, was variable between hospitals. In a univariate linear regression model, patient risk profile only accounted for approximately 10% of statistical variance in charges. CONCLUSIONS:There is significant charge variability for coronary artery bypass grafting among hospitals within the same state. By targeting variation in preoperative length of stay, operating room time, postoperative renal failure, prolonged ventilation, and reoperation, cardiac surgery programs can realize cost savings while improving quality of care for this resource-intense patient population.