DeCampli and Burke [1DeCampli W.M. Burke R.P. Interinstitutional comparison of risk-adjusted mortality and length of stay in congenital heart surgery.Ann Thorac Surg. 2009; 88: 151-157Abstract Full Text Full Text PDF PubMed Scopus (11) Google Scholar] conclude that the comprehensive Aristotle score (CCS) is a superior predictor of early mortality (in-hospital or out-of-hospital within 30 days of surgery) after congenital heart surgery compared with two other more basic mortality risk models: (1) the Risk Adjustment for Congenital Heart Surgery Score (RACHS) and (2) the basic Aristotle score (BCS). This finding is expected, given that CCS incorporates the effects of age and comorbidities. I also concur with the authors' recommendation that the inclusion of CCS scores in The Society of Thoracic Surgeons' Congenital Database is a critical future step. Doing so will allow its further refinement and validation as the basis for risk-adjusted mortality calculations, which are the cornerstone for benchmarking, as well as interinstitutional quality-of-care comparisons. The authors other reported finding is that CCS, combined with RACHS and age in a linear regression model, is a moderately good predictor of hospital length of stay (LOS) in general, but caution that this model accuracy is poor when used to predict LOS in individual patients. My commentary will focus exclusively on various aspects of this LOS prediction. Cardiopulmonary bypass (CPB) was equally frequent in approximately two thirds of cases at both institutions in the analysis. CPB, particularly its duration, is a useful surrogate of surgical complexity. Resource utilization, and in particular LOS, are usually increased in a correlated manner with surgical complexity. Thus, a reasonable question is why not incorporate CPB at least as a categorical (yes or no), or possibly better as a continuous variable (min), covariate in the LOS regression model. This is made more relevant by the fact that CPB may also serve as a way to minimize the confounding effects inherent in the heterogeneous mix of cases typical of congenital heart surgery programs, all of which are included in the analysis at hand. Alternatively, given that the authors report that CCS and RACHS are well correlated (correlation coefficient = 0.73), what is the anticipated benefit from including both in the LOS regression prediction model. It is in fact conceivable that the nonsignificant effect of institution (or location) on the LOS prediction (see Table 6 in article [1DeCampli W.M. Burke R.P. Interinstitutional comparison of risk-adjusted mortality and length of stay in congenital heart surgery.Ann Thorac Surg. 2009; 88: 151-157Abstract Full Text Full Text PDF PubMed Scopus (11) Google Scholar]) may have been a derivative of the inclusion of RACHS in the model. This contention is premised on the fact that RACHS was not equivalently distributed for the two institutions (see Table 2 in article [1DeCampli W.M. Burke R.P. Interinstitutional comparison of risk-adjusted mortality and length of stay in congenital heart surgery.Ann Thorac Surg. 2009; 88: 151-157Abstract Full Text Full Text PDF PubMed Scopus (11) Google Scholar]). For example, lower risk patients with RACHS equals 1 or 2, which constituted 42% of cases at institution 1 versus 52% at institution 2. These points together lead me to speculate that a regression model based on the three continuous variables CCS, age, and CPB (min), along with institution (1 or 2) could have lead to even better LOS prediction with a possible significant effect of institution. If true, the latter, would have agreed with the inter-institutional postoperative protocol differences described by the authors. Last, it seems unrealistic to expect that even an improved LOS regression model would ever be a reliable predictor of LOS on an individual patient basis. Thus, it seems misleading to highlight this as a significant limitation of such resource utilization models. I suggest that these models are in fact highly useful because of their predictive nature when applied to similar risk cohorts as opposed to individual patients [2Riordan C.J. Engoren M. Zacharias A. et al.Resource utilization in coronary artery bypass operation: does surgical risk predict cost?.Ann Thorac Surg. 2000; 69: 1092-1097Abstract Full Text Full Text PDF PubMed Scopus (35) Google Scholar]. When used in this manner, and given a certain hospital case mix, these prediction models will empower hospital administrators to objectively plan their resource allocation. Moreover, such resource utilization models may have a potential role in defining a more balanced reimbursement schedule based on case mix. Interinstitutional Comparison of Risk-Adjusted Mortality and Length of Stay in Congenital Heart SurgeryThe Annals of Thoracic SurgeryVol. 88Issue 1PreviewRisk Adjustment for Congenital Heart Surgery (RACHS) and basic Aristotle scores (BCS) have been shown to correlate with mortality and length of stay (LOS) after congenital heart surgery. Interinstitutional comparisons using these scores, as well as comprehensive Aristotle score (CCS), have not been demonstrated. Full-Text PDF