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Published on: October 12, 2014
Mortality rates after heart transplantation: how to compare center-specific outcome data?
J M A Smits1, J De Meester, M C Deng
1Eurotransplant International Foundation, Leiden, The Netherlands. jsmits@eurotransplant.nl
Insights
Empirical Bayes (EB) methods provide a more accurate assessment of heart transplant center performance. These methods are recommended for identifying centers that significantly deviate from quality standards in transplant auditing.
Area of Science:
- Cardiology
- Transplantation Medicine
- Health Services Research
Background:
- Cardiac transplantation outcomes research traditionally focuses on patient and donor factors.
- The impact of transplant center variability on patient outcomes has been under-examined.
- This study aimed to evaluate heart transplant center performance variations within Eurotransplant.
Purpose of the Study:
- To assess the variability in heart transplantation outcomes across Eurotransplant centers.
- To provide a framework for auditing transplant center performance.
- To compare different statistical methods for evaluating center-specific effects.
Main Methods:
- Analysis of 1,401 adult heart transplantations performed in 45 centers over a 2-year period.
- Calculation of risk-adjusted center effects on 1-year mortality.
- Application of empirical Bayes (EB) methods to estimate center effects, adjusting for prognostic factors.
Main Results:
- Overall 1-year patient survival was 76%, with significant center-level variation (0%-100%).
- Empirical Bayes methods identified fewer outlying centers compared to standard risk-adjusted methods.
- EB methods provided a more precise estimation of true center effects after adjusting for case mix.
Conclusions:
- Empirical Bayes methods offer a more precise and realistic evaluation of heart transplant center performance.
- EB methods are superior to other risk-adjusted methods for auditing transplant centers.
- These methods should be preferred for identifying centers with significant deviations from quality standards.
Background:
Studies of outcome in cardiac transplantation have focused primarily on identifying patient- and donor-related factors associated with patient mortality. Less consideration has been given to the impact of the transplant center. This study was undertaken to assess variability in heart transplantation outcome in Eurotransplant centers to provide a framework for auditing.
Methods And Results:
In a 2-year period, 1,401 adult patients underwent heart transplantation in 45 centers. The 1-year patient survival rate was 76% (95% CI, 74%-78%) with a range of 0% to 100% at the center level. The risk-adjusted center effect on mortality was estimated by calculating a standardized difference between the observed number of deaths 1 year after transplantation and the expected number of deaths based on the case mix. By assessing within- and between-center variations with empirical Bayes (EB) methods, after adjustment for all registered prognostic factors, an improved estimate of the true center effect was obtained. Compared with the standard risk-adjusted center effect method, fewer outlying centers were identified with the EB method.
Conclusion:
EB methods, because they are known to incorporate more information from the data, enable a more precise and realistic portrayal of heart transplant centers' performances, compared with other risk-adjusted center effect methods. In the context of auditing procedures, EB methods should preferably be used for the identification of centers that deviate significantly from quality standards.
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