Variability in cost of coronary bypass surgery in New York State: potential for cost savings.
OBJECTIVE
Previous analyses of variability in bypass resource use have not focused on hospital-level variation or adequately explored the influence of patient risk. We combined a clinical database with claims data to fully characterize patient level and hospital level variability in bypass surgery cost and length of stay in New York State and explored the extent to which lower cost is associated with worse quality of care.


METHODS
By use of 1992 clinical and claims data, we identified by multivariable regression which patient characteristics influence bypass cost and length of stay. Hospital was then incorporated as a random variable in mixed linear models to determine its impact on resource use. The relationship between risk-adjusted in-hospital mortality and cost was then explored.


RESULTS
In the 21 hospitals for which cost data were available, mean leveled cost (exclusive of professional fees and noncomparable costs) was $15,713, with a mean length of stay of 14 days (n = 12,087). One fifth of the variation in resource use was explained by baseline patient risk. After adjustment for patient risk, hospital explained an additional 42% of variation in cost and an additional 8% of variation in length of stay. Among hospitals, risk-adjusted cost varied almost 3-fold and risk-adjusted length of stay varied 50%. There was no association between cost and in-hospital mortality.


CONCLUSIONS
As of 1992, there was considerable interhospital variability in bypass surgery cost after patient baseline risk was accounted for. This suggests that reductions in bypass cost could be achieved by normalizing clinical practice.
Cowper
Patricia A
PA
Outcomes Research and Assessment Group, Duke Clinical Research Institute, Durham, NC 27715, USA. cowpe001@mc.duke.edu
DeLong
Elizabeth R
ER
Peterson
Eric D
ED
Hannan
Edward L
EL
Ray
Kevin T
KT
Racz
Michael
M
Mark
Daniel B
DB
D000368:Aged; D002302:Cardiac Output; D001026:Coronary Artery Bypass / Q000191:economics* / Q000401:mortality; D003365:Costs and Cost Analysis; D005260:Female; D006295:Health Resources / Q000191:economics / Q000706:statistics & numerical data; D017721:Hospital Costs / Q000706:statistics & numerical data*; D017052:Hospital Mortality; D006801:Humans; D007902:Length of Stay / Q000191:economics / Q000706:statistics & numerical data*; D016014:Linear Models; D008297:Male; D009518:New York / Q000453:epidemiology; D012044:Regression Analysis; D018570:Risk Assessment; D012720:Severity of Illness Index