title: The value of adding laboratory data to coronary artery bypass grafting registry data to improve models for risk-adjusting provider mortality rates.
abstract: BACKGROUND
  Clinical databases are currently being used for calculating provider risk-adjusted mortality rates for coronary artery bypass grafting (CABG) in a few states and by the Society for Thoracic Surgeons. These databases contain very few laboratory data for purposes of risk adjustment.
  
  
  METHODS
  For 15 hospitals, New York's CABG registry data from 2008 to 2010 were linked to laboratory data to develop statistical models comparing risk-adjusted mortality rates with and without supplementary laboratory data. Differences between these two models in discrimination, calibration, and outlier status were compared, and correlations in hospital risk-adjusted mortality rates were examined.
  
  
  RESULTS
  The discrimination of the statistical models was very similar (c = 0.785 for the registry model and 0.797 for the registry/laboratory model, p =0.63). The correlation between hospital risk-adjusted mortality rates by use of the two models was 0.90. The registry/laboratory model contained three additional laboratory variables: alkaline phosphatase (ALKP), aspartate aminotransferase (AST), and prothrombin time (PT). The registry model yielded one hospital with significantly higher mortality than the statewide average, and the registry/laboratory model yielded no outliers.
  
  
  CONCLUSIONS
  The clinical models with and without laboratory data had similar discrimination. Hospital risk-adjusted mortality rates were essentially unchanged, and hospital outlier status was identical. However, three laboratory variables, ALKP, AST, and PT, were significant independent predictors of mortality, and they deserve consideration of addition to CABG clinical databases.
authors.affiliation: Department of Health Policy, Management, and Behavior, University at Albany, State University of New York, Albany, New York. Electronic address: elh03@health.state.ny.us.
authors.forename: Edward L
authors.initials: EL
authors.lastname: Hannan
authors.affiliation: Department of Health Policy, Management, and Behavior, University at Albany, State University of New York, Albany, New York.
authors.forename: Feng
authors.initials: F
authors.lastname: Qian
authors.affiliation: Michael Pine Associates, Chicago, Illinois.
authors.forename: Michael
authors.initials: M
authors.lastname: Pine
authors.affiliation: Michael Pine Associates, Chicago, Illinois.
authors.forename: Donald E
authors.initials: DE
authors.lastname: Fry
authors.affiliation: Michael Pine Associates, Chicago, Illinois.
authors.forename: Kay
authors.initials: K
authors.lastname: Whitman
authors.affiliation: Department of Health Policy, Management, and Behavior, University at Albany, State University of New York, Albany, New York; New York State Department of Health, Albany, New York.
authors.forename: Barbara A
authors.initials: BA
authors.lastname: Dennison
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D064790:Clinical Laboratory Services / Q000706:statistics & numerical data*; D001026:Coronary Artery Bypass / Q000401:mortality*; D016208:Databases, Factual; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D012042:Registries; D020379:Risk Adjustment / Q000706:statistics & numerical data*; D055815:Young Adult