Objective: To develop a risk stratification model to assess open heart surgery mortality in Catalonia (Spain) in order to use risk-adjusted hospital mortality rates as an approach to analyze quality of care.
Methods: Data were prospectively collected through a specific data-sheet during 6 1/2 months in consecutive adult patients subjected to open heart surgery. The dependent variable was surgical mortality, and independent variables included were presurgical (sociodemographic data, clinical antecedents, morphological and functional studies) and surgical. The model was built on a subsample (70% of study population) through univariate and logistic regression analysis and validated in the rest of the sample.
Results: The total sample was of 1309 procedures in seven hospitals; 47% of them were valve procedures. The overall crude mortality rate was 10.9% and varied among centers (range, 2.8-14.8%). Risk factors included in the model received a weight based on the logistic regression coefficient and a score was generated for each patient. The factors with the highest weight were patient older than 80 and second reoperation. Score was stratified in five categories of increasing risk. There was a good agreement between observed and predicted mortality rates in the validation group. Overall patient distribution was as follows: 52% low risk level, 16% fair, 13% high, 12% very high, and 6% extremely high risk level. Mortality rate increased from 4.2% in the low risk to 54.4% in the highest risk group. Case mix adjustment was performed through the risk score level. There were statistically significant differences in the risk profiles of patients admitted among centers. After adjustment by risk profiles, there were no differences in mortality by hospital.
Conclusion: A risk stratification model through a multicentric, prospective and exhaustive collection of data in all types of open heart procedures was developed. In spite of wide differences on crude rates and in the risk profiles of patients admitted, we did not find statistically significant differences in adjusted mortality rates among centers. Timely and accurate information about surgical outcomes can lead to improvements in clinical practice and quality of care.