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OBJECTIVES Outcomes evaluation is enhanced by assignment of operative procedures to appropriate categories based upon relative average risk. Formal risk modelling is challenging when a large number of operation types exist, including relatively rare procedures. Complexity stratification provides an alternative methodology. We report the initial application in the Congenital Heart Surgery Databases of the Society of Thoracic Surgeons (STS) and the European Association for Cardio-thoracic Surgery (EACTS) of an empirically derived system of complexity adjustment to evaluate surgical case mix and results. METHODS Complexity stratification is a method of analysis in which the data are divided into relatively homogeneous groups (called strata). A complexity stratification tool named the STS–EACTS Congenital Heart Surgery Mortality Categories (STAT Mortality Categories) was previously developed based on the analysis of 77 294 operations entered in the Congenital Heart Surgery Databases of EACTS (33 360 operations) and STS (43 934 patients). Procedure-specific mortality rate estimates were calculated using a Bayesian model that adjusted for small denominators. Operations were sorted by increasing risk and grouped into five categories (the STAT Mortality Categories) that were designed to minimize within-category variation and maximize between-category variation. We report here the initial application of this methodology in the EACTS Congenital Heart Surgery Database (47 187 operations performed over 4 years: 2006–09) and the STS Congenital Heart Surgery Database (64 307 operations performed over 4 years: 2006–09). RESULTS In the STS Congenital Heart Surgery Database, operations classified as STAT Mortality Categories 1–5 were (1): 17332, (2): 20114, (3): 9494, (4): 14525 and (5): 2842. Discharge mortality was (1): 0.54%, (2): 1.6%, (3): 2.4%, (4): 7.5% and (5): 17.8%. In the EACTS Congenital Heart Surgery Database, operations classified as STAT Mortality Categories 1–5 were (1): 19874, (2): 12196, (3): 5614, (4): 8287 and (5): 1216. Discharge mortality was (1): 0.99%, (2): 2.9%, (3): 5.0%, (4): 10.3% and (5): 25.0%. CONCLUSIONS The STAT Mortality Categories facilitate analysis of outcomes across the wide spectrum of distinct congenital heart surgery operations including infrequently performed procedures. [ABSTRACT FROM PUBLISHER]

Objective: The analysis of the second harvest of the STS Congenital Heart Surgery Database produced meaningful outcome data and several critical lessons relevant to congenital heart surgery outcomes analysis worldwide. Methods: This data harvest represents the first STS multi-institutional experience with software utilizing the nomenclature and database requirements adopted by the STS and EACTS (April 2000 Annals of Thoracic Surgery). Members of the STS Congenital Heart Committee analyzed the STS data. Results: This STS harvest includes data from 16 centers (12787 cases, 2881 neonates, 4124 infants). In 2002, the EACTS reported similar outcome data utilizing the same database definitions (41 centers, 12736 cases, 2245 neonates, 4195 infants). Lessons from the analysis include: (1) Death must be clearly defined. (2) The Primary Procedure in a given operation must be documented. (3) Inclusionary and exclusionary criteria for all diagnoses and procedures must be agreed upon. (4) Missing data values remain an issue for the database. (5) Generic terms in the nomenclature lists, that is terms ending in Not Otherwise Specified (NOS), are redundant and decrease the clarity of data analysis. (6) Methodology needs to be developed and implemented to assure and verify data completeness and data accuracy. ‘Operative Mortality’ and ‘Mortality Assigned to this Operation’ were defined by the STS and EACTS; these definitions were not utilized uniformly. ‘Thirty Day Mortality’ was problematic because some centers did not track mortality after hospital discharge. Only ‘Mortality Prior to Discharge’ was consistently reported. Designation of Primary Procedure for a given operation determines its location for analysis. Until Complexity Scores lead to automated methodology for choosing the Primary Procedure, the surgeon must designate the Primary Procedure. Inclusionary and exclusionary criteria for all diagnoses and procedures have been developed in an effort to define acceptable concomitant diagnoses and procedures for each analysis. Improvements in data completeness can be achieved using a variety of techniques including developing more functional techniques of data entry at individual institutions and software improvements. Future versions of the STS Congenital Database will request that the coding of diagnoses and procedures avoid the terms ending in NOS. Conclusions: Lessons from this data harvest should improve congenital heart surgery outcome analysis. [Copyright &y& Elsevier]