Assessing open heart surgery mortality in Catalonia (Spain) through a predictive risk model

Area of Science:

• Cardiovascular Surgery
• Health Services Research
• Biostatistics

Background:

• Assessing quality of care in open heart surgery is crucial.
• Hospital mortality rates can vary significantly due to differences in patient populations (case mix).
• Developing a robust risk stratification model is essential for accurate quality assessment.

Purpose of the Study:

• To develop and validate a risk stratification model for open heart surgery mortality in Catalonia, Spain.
• To enable risk-adjusted analysis of hospital mortality rates to evaluate quality of care.
• To identify key predictors of mortality in open heart surgery patients.

Main Methods:

• Prospective data collection of consecutive adult patients undergoing open heart surgery over 6.5 months.
• Development of a risk model using univariate and logistic regression on a 70% subsample.
• Validation of the model on the remaining 30% of the study population.

Main Results:

• The study included 1309 procedures across seven hospitals, with an overall crude mortality rate of 10.9%.
• Key risk factors identified included advanced age (>80 years) and undergoing a second reoperation.
• The developed risk score effectively stratified patients into five risk categories, with mortality increasing from 4.2% (low risk) to 54.4% (highest risk).
• After risk adjustment, no statistically significant differences in mortality were found among the participating hospitals, despite variations in crude rates and patient risk profiles.

Conclusions:

• A multicenter, prospective risk stratification model for open heart surgery was successfully developed.
• Risk-adjusted analysis revealed no significant differences in mortality rates among hospitals, suggesting comparable quality of care.
• Accurate data on surgical outcomes is vital for improving clinical practice and enhancing patient care quality.