Early identification of divergent performance in congenital cardiac surgery

Heterogeneous caseload and poorly quantified risk stratification make it difficult to monitor outcomes in congenital cardiac surgery. Reliance on formal statistical hypothesis testing may lead to substantial delays before a pattern of poor outcome can be established. Here, we report alternative methods for alerting surgeons to potential problems at an earlier stage.

Graphical methods developed for monitoring adult cardiac surgery have been adapted for use in congenital cardiac surgery. To illustrate their potential, we have retrospectively examined mortality data for a single surgeon involving 315 cases. Partial risk adjustment has been carried out according to patient's age and the open/closed categorization of the surgical procedure. Additional information has been derived by ranking procedures in order of their complexity and displaying the proportion of the surgeon's cases in each complexity stratum.

The display of a surgeon's mortality data adjusted for age and open/closed category provides an easily understood chart of performance and allows one to identify periods when performance appears divergent, relative to the surgeon's own overall standards. Cases carried out during such periods can then be scrutinized by alternative methods. One such method is to examine caseload complexity during the periods of apparent divergent performance compared with other periods.

These methods, while in no way representing formal statistical tests, provide a means that can alert surgeons to potential problems and help to identify sequences of cases that might benefit from further scrutiny.