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151 Race and Insurance Status Are Associated With Higher Charges in Patients Having Pituitary Tumor Surgery in New York State.

INTRODUCTION
Cost of care can be influenced by factors unrelated to quality. We previously demonstrated that, for patients undergoing pituitary tumor surgery, hospital costs, charges, and length of stay (LOS) across New York State were significantly affected by surgeon volume and geographic location. To identify factors that may have gone unnoticed, we conducted further analysis to identify patient-related factors present in low- vs high-charging hospitals.


METHODS
We performed cost analysis on pituitary tumor surgery cases previously identified in the New York State inpatient database (SPARCS 2006-2012). Controlling for surgeon volume, hospital location, and LOS, a Bayesian model-based clustering method segregated hospitals into low, medium, and high charging; subsequent analysis of variance (ANOVA) and linear regression identified patient factors that were statistically different between these groups.


RESULTS
Two thousand seven hundred eighty-four surgeries were performed in New York (2006-2012), 63% of patients were white, and 66% were privately insured, with Medicare/Medicaid covering 32%. Among low (6), medium (31), and high charge hospitals (32), median charges were $10 740, $24 221, and $43 520, respectively. Mean percentages of white patients were 14%, 48%, and 54%; mean percentages of privately insured patients were 28%, 40% and 60%. The association between race, insurance status and hospital charges was significant using both one-way ANOVA (race, P = .047; insurance status P = .011) and linear regression (race, P = .035; insurance status, P = .003). Costs and LOS were not different between low-, medium-, and high-charging hospitals.


CONCLUSION
When studying patients having pituitary tumor surgery, high-charging hospitals had a statistically significant increased proportion of white and privately insured patients, even though the cost of providing the service and the LOS (an indirect proxy for quality) was no different from low-charging hospitals. Understanding the forces that influence hospital charges will be important to improve health care quality and cost effectiveness.