The comparison of performance between thoracic surgical units

Managed care systems demand an increased effort in quality monitoring and improvement processes through the analysis of performance of health care providers. The performance can be assessed by analyzing the outcomes or the clinical processes. To date, outcome indicators are still the most widely used quality end points in our specialty. However, because patients are not randomly allocated to different physicians or hospitals, different case-mixes at different institutions may make the comparison of crude outcome rates misleading. Therefore, the selection of quality end points must account for the differences in the prevalence of risk factors, and clinical risk modeling must become the logical and necessary approach for provider profiling to prevent inappropriate clinical and administrative decisions and unethical risk-averse behaviors. Regression analyses are the analytic techniques most commonly used for risk modeling. However, the resultant models are useful only if they reliably predict outcomes for patients by determining significant risk factors associated with the outcome of interest. Recent evidence has shown that bootstrap resampling analysis can formalize the development of model building, removing much of the human biases associated with regression analysis, providing a balance between selecting risk factors that are not reliable (type I error) and overlooking variables that are reliable (type II error), and introducing a concrete measure of reliability of the risk factors. Regardless of the type of end point that will be used in the future for quality management purposes. data collection will always be of paramount importance. The costs for implementing and managing international multicentric databases (such as the European Thoracic Surgery Database or the STS Thoracic database) seem, therefore, justified by the benefits that could be derived from the quality improvement processes, which will be based on them.