The value of adding laboratory data to coronary artery bypass grafting registry data to improve models for
Edward L Hannan1, Feng Qian1, Michael Pine2
1Department of Health Policy, Management, and Behavior, University at Albany, State University of New York, Albany, New York.
Insights
Adding laboratory data to coronary artery bypass grafting (CABG) registries did not significantly change mortality predictions. However, alkaline phosphatase (ALKP), aspartate aminotransferase (AST), and prothrombin time (PT) are important predictors of mortality.
Area of Science:
- Cardiovascular Surgery
- Health Services Research
- Clinical Informatics
Background:
- Current clinical databases for coronary artery bypass grafting (CABG) mortality risk adjustment lack comprehensive laboratory data.
- Existing models are used in select states and by professional societies.
Purpose of the Study:
- To assess the impact of incorporating laboratory data into statistical models for CABG risk-adjusted mortality rates.
- To compare model performance with and without supplementary laboratory variables.
Main Methods:
- Linked New York CABG registry data (2008-2010) with laboratory results for 15 hospitals.
- Developed and compared statistical models for risk-adjusted mortality with and without laboratory data.
- Evaluated differences in model discrimination, calibration, and identification of outlier hospitals.
Main Results:
- Model discrimination was similar: c-statistic of 0.785 (registry) vs. 0.797 (registry/laboratory).
- High correlation (0.90) observed between hospital mortality rates from both models.
- Three laboratory variables (alkaline phosphatase, aspartate aminotransferase, prothrombin time) were significant predictors of mortality.
Conclusions:
- Incorporating laboratory data did not substantially alter overall risk-adjusted mortality predictions or outlier status.
- Laboratory variables like ALKP, AST, and PT are significant independent predictors of CABG mortality.
- These laboratory variables warrant consideration for inclusion in future CABG clinical databases.
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.
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