Mortality Prediction in Cardiac Surgery Patients: Comparison of two Risk Stratification models for Patient Safety

Background:

Safe surgery is the second global Patient Safety challenge. Analysis of patient safety has gained increasing importance as public and health authorities demand more data on risk, prognosis and performance outcome of specific procedures, particularly for resource intensive operations such as Coronary Artery Bypass Graft & Valve Surgery. Mortality rates are one of the most important predictors of quality of services. It is obvious that a simple comparison of post operative mortality reflects the actual quality of service of a hospital and of an individual surgeon.

The mortality of surgery can be   reduced by doing risk assessment and corrective measure before and after the surgery. Hence there is a great need for a reliable risk stratification model.

Objective:

To assess the validity, performance and applicability of Parsonnet Risk Stratification model in Cardiac Surgery against EURO model in different operative sub-groups and to compare the Predicted and Observed Mortality between the two models. The data on risk profile prescribed by the two models was collected for those who underwent cardiac surgery during the year 2008. The mortality outcome was correlated with the predictive risk criteria of the two models.

Methods: A retrospective study was conducted by taking the data from medical records of the patients.
Results:

The analysis of the data shows that outcome quality of Parsonnet Model was 1.38% compared to 1.2% of EURO Model against the International benchmark of 1.02% (t=-0.0456.).  The study finds that EURO SCORE Model is a better predictor of mortality than Parsonnet model which can be primarily attributed to the redundancy of parameters in the Parsonnet model.

Conclusions:

Hence it is concluded that the risk stratification models would act as an indicator of quality for patient safety, would facilitate proper and timely allocation of limited resources, would be a suitable model of fundamental importance for benchmarking, can be used for audit purposes, would remove the bias factor and would form a basis for surgeon and patient on decision making by weighing the risks and benefits so as to clarify expectations.