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Mortality Trends in Pediatric and Congenital Heart Surgery: An Analysis of The Society of Thoracic Surgeons Congenital Heart Surgery Database
Mortality Trends in Pediatric and Congenital Heart Surgery: An Analysis of The Society of Thoracic Surgeons Congenital Heart Surgery Database Jeffrey P. Jacobs, MD, Xia He, MS, John E. Mayer, Jr, MD, Erle H. Austin, III, MD, James A. Quintessenza, MD, Tom R. Karl, MD, Luca Vricella, MD, Constantine Mavroudis, MD, Sean M. O’Brien, PhD, Sara K. Pasquali, MD, MHS, Kevin D. Hill, MD, S. Adil Husain, MD, David M. Overman, MD, James D. St. Louis, MD, Jane M. Han, MSW, David M. Shahian, MD, Duke Cameron, MD, and Marshall L. Jacobs, MD Division of Cardiac Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland (JPJ, JAQ, TRK, LV, CM, DC, MLJ); Division of Cardiovascular Surgery, Department of Surgery, Johns Hopkins All Children’s Heart Institute, Johns Hopkins All Children’s Hospital and Florida Hospital for Children, Saint Petersburg, Tampa, and Orlando, Florida (JPJ, JAQ, TRK, LV, CM, DC, MLJ); Duke University, Durham, North Carolina (XH, SMO, KDH); Children’s Hospital Boston, Harvard Medical School, Boston, Massachusetts (JEM); Kosair Children’s Hospital, University of Louisville, Louisville, Kentucky (EHA); Discipline of Surgery, University of Queensland School of Medicine, Brisbane, Australia (TRK); C. S. Mott Children’s Hospital, University of Michigan, Ann Arbor, Michigan (SKP); University of Texas Health Sciences Center–San Antonio/University Health Systems, San Antonio, Texas (SAH); The Children’s Heart Clinic at Children’s Hospitals and Clinics of Minnesota, Minneapolis, Minnesota (DMO); Department of Surgery, University of Missouri-Kansas City School of Medicine, Kansas City, Missouri (JDSL); The Society of Thoracic Surgeons, Chicago, Illinois (JMH); and Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts (DMS)
Background. Previous analyses of The Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database have demonstrated a reduction over time of risk-adjusted operative mortality after coronary artery bypass grafting. The STS Congenital Heart Surgery Database (STS CHSD) was queried to assess multiinstitutional trends over time in discharge mortality and postoperative length of stay (PLOS). Methods. Since 2009, operations in the STS CHSD have been classified according to STAT (The Society of Thoracic Surgeons—European Association for CardioThoracic Surgery) Congenital Heart Surgery Mortality Categories. The five STAT Mortality Categories were chosen to be optimal with respect to minimizing variation within categories and maximizing variation between categories. For this study, all index cardiac operations from 1998 to 2014, inclusive, were grouped by STAT Mortality Category (exclusions: patent ductus arteriosus ligation in patients weighing less than or equal to 2.5 kg and operations that could not be assigned to a STAT Mortality Category). End points were discharge mortality and PLOS in survivors for the entire period and for 4-year epochs. The Cochran-Armitage trend test was used to test
Accepted for publication Jan 11, 2016. Presented at the Sixty-second Annual Meeting of the Southern Thoracic Surgical Association, Orlando, FL, Nov 4–7, 2015. Address correspondence to Dr Jacobs, Johns Hopkins All Children’s Hospital, 601 Fifth St S, Ste 607, St. Petersburg, FL 33701; email: [email protected].
Ó 2016 by The Society of Thoracic Surgeons Published by Elsevier
the null hypothesis that the mortality was the same across epochs, by STAT Mortality Category. Results. The analysis encompassed 202,895 index operations at 118 centers. The number of centers participating in STS CHSD increased in each epoch. Overall discharge mortality was 3.4% (6,959 of 202,895) for 1998 to 2014 and 3.1% (2,308 of 75,337) for 2011 to 2014. Statistically significant improvement in discharge mortality was seen in STAT Mortality Categories 2, 3, 4, and 5 (p values for STAT Mortality Categories 1 through 5 are 0.060, <0.001, 0.015, <0.001, and <0.001, respectively). PLOS in survivors was relatively unchanged over the same time intervals. Sensitivity analyses reveal that the finding of declining risk-stratified rates of discharge mortality over time is not simply attributable to the addition of more centers to the cohort over time. Conclusions. This 16-year analysis of STS CHSD reveals declining discharge mortality over time, especially for more complex operations. (Ann Thorac Surg 2016;-:-–-) Ó 2016 by The Society of Thoracic Surgeons
T
he Society of Thoracic Surgeons (STS) National Database was established in 1989 as an initiative to enhance the quality and safety of cardiothoracic surgery and to provide an accurate and valid basis for measuring performance in our specialty. The STS National Database has three components, each focusing on a different area of cardiothoracic surgery—Adult Cardiac Surgery, 0003-4975/$36.00 http://dx.doi.org/10.1016/j.athoracsur.2016.01.071
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General Thoracic Surgery, and Congenital Heart Surgery [1]. The STS Congenital Heart Surgery Database (CHSD) was founded in 1994 to support quality improvement and patient safety in pediatric and congenital cardiothoracic surgery [2]. Previous analyses of the STS Adult Cardiac Surgery Database have demonstrated a reduction over time of risk-adjusted operative mortality after coronary artery bypass grafting [3]. The purpose of this analysis is to describe congenital and pediatric cardiac surgical trends in multi-institutional outcomes achieved at centers participating in the STS CHSD.
Patients and Methods Data Source The STS CHSD was used for this study. STS CHSD is an audited comprehensive database of patients who have undergone congenital and pediatric cardiac surgical operations at centers in the United States and Canada. STS CHSD is a voluntary registry that contains preoperative, operative, and outcomes data for all patients undergoing congenital and pediatric cardiovascular operations at participating centers. STS CHSD uses the following age groupings: neonates (0 to 30 days), infants (31 days to 1 year), children (>1 year to <18 years), and adults (18 years). The Report of the 2010 STS Congenital Heart Surgery Practice and Manpower Survey, undertaken by the STS Workforce on Congenital Heart Surgery, estimated that 125 hospitals in the United States and 8 hospitals in Canada perform pediatric and congenital heart operations [4]. In 2014, the STS CHSD included 114 congenital heart surgery programs representing 119 of the 125 hospitals (95.2% penetration by hospital) in the United States and 3 of the 8 centers in Canada. Coding for this database is accomplished by clinicians and support staff using the International Pediatric and Congenital Cardiac Code [5, 6] and is entered into the contemporary version of the STS CHSD data collection form [7]. The definitions of all terms and codes from the STS CHSD used in this report have been standardized and published [7]. Evaluation of data quality in the STS CHSD includes intrinsic verification of data (eg, identification and correction of missing/out of range values and inconsistencies across fields), along with a formal process of audits at approximately 10% of all participating centers each year conducted by a panel of independent qualityassurance personnel and pediatric cardiac surgeons [8]. Audit of the STS CHSD has documented the following rates of completeness and accuracy for the specified fields of data [9]: Primary diagnosis (completeness, 100%; accuracy, 96.2%) Primary procedure (completeness, 100%; accuracy, 98.7%) Mortality status at hospital discharge (completeness, 100%; accuracy, 98.8%)
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Accounting for Case Mix Owing to the large number of different types of pediatric and congenital cardiac operations (ie, more than 200 individual procedure types, most often performed in various combinations), it is useful to stratify individual operations into groups or categories that are relatively homogeneous with respect to complexity or risk. This methodology, called complexity stratification (or risk stratification), has been used by STS CHSD since 2002. Risk stratification is a method of analysis in which the data are divided into relatively homogeneous groups (called strata). The data are analyzed and reported within each stratum. STS CHSD has used three methods of risk stratification [10–12]: 1. The Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery (STAT) Congenital Heart Surgery Mortality Categories (STAT Mortality Categories) 2. Aristotle Basic Complexity Levels 3. Risk Adjustment for Congenital Heart Surgery-1 Categories STS CHSD initially used the Aristotle Basic Complexity Levels and the Risk Adjustment for Congenital Heart Surgery-1 Categories to stratify procedures according to degree of complexity and risk. With the increasing availability of multiinstitutional clinical data, the empirically based STAT Mortality Score and STAT Mortality Categories were introduced in the STS CHSD in 2010. The STAT Mortality Categories [11, 12] are a tool for stratification based on the procedure-specific estimate of the risk of discharge mortality, which was developed from an analysis of 77,294 operations entered into the European Association for Cardio-Thoracic Surgery Congenital Heart Surgery Database (33,360 operations) and the STS CHSD (43,934 operations). 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 be optimal with respect to minimizing variation within categories and maximizing variation between categories. STAT Mortality Category 1 is associated with the lowest risk for mortality and STAT Mortality Category 5 is associated with the highest risk for mortality.
Study Population For this study, all index cardiac operations in STS CHSD from January 1998 through June 2014, inclusive, were eligible for inclusion. Index operations are defined as the first cardiac operation of a hospitalization. Patients weighing less than or equal to 2.5 kg undergoing isolated closure of a patent arterial duct were excluded. Operations that could not be assigned a STAT Mortality Category were also excluded. All remaining eligible index cardiac operations were grouped by STAT Mortality Category. The final study cohort included 202,895 index cardiac operations performed in 118 centers.
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Analytic Methodology Data collected included primary procedure of the index cardiac operation, discharge mortality, and postoperative length of stay (PLOS). End points were discharge mortality and PLOS in patients who survived to hospital discharge, for the entire period and for 4-year epochs. It should be noted that STS CHSD now uses operative mortality as an end point and not simply discharge mortality. Discharge mortality is used in this report because operative mortality data are not available in the earlier years of this analysis. Operative mortality is defined in all STS databases as (1) all deaths, regardless of cause, occurring during the hospitalization in which the operation was performed, even if after 30 days (including patients transferred to other acute care facilities); and (2) all deaths, regardless of cause, occurring after discharge from the hospital but before the end of the 30th postoperative day [13, 14]. Mortality and PLOS outcomes were summarized by STAT Mortality Category and year using frequencies and proportions for categorical variables and medians for continuous variables. Outcomes were compared across epochs, by STAT Mortality Category, using the CochranArmitage trend test, which was used to test the null hypothesis that the risk-stratified mortality was the same across epochs. With respect to the year-by-year assessment of outcomes, a sensitivity analysis was performed using data for the entire period but including only the 30 programs that participated in STS CHSD in 2003. A sensitivity analysis was also performed for the epoch analysis involving the 4-year epochs using only the 22 programs that participated in 1998 to 2002. Analyses were performed using SAS 9.3 software (SAS Institute Inc, Cary, NC). A p value of less than 0.05 was considered statistically significant.
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75,337) for the most recent 4-year epoch from 2011 to 2014. Figure 1 plots discharge mortality versus year of operation, stratified by STAT Mortality Category, for the years 1998 to 2014. Table 1 documents discharge mortality for all patients and PLOS for survivors, stratified by STAT Mortality Category, for the entire period and for 4-year analytic windows. The analysis by successive 4-year periods revealed statistically significant decline in discharge mortality across epochs for cases in STAT Mortality Categories 2, 3, 4, and 5 (p values for STAT Mortality Categories 1 through 5 are 0.060, <0.001, 0.015, <0.001, and <0.001, respectively).
Sensitivity Analysis A sensitivity analysis was performed for the year-by-year analysis involving the entire period using only the 30 programs that participated in 2003. Figure 2 plots discharge mortality versus year of operation for these 30 programs, stratified by STAT Mortality Category, for the years 1998 to 2014. An additional sensitivity analysis was performed for the epoch analysis involving the 4-year epochs using only the 22 programs that participated in 1998 to 2002. For these 22 programs, Table 2 documents discharge mortality for all patients and PLOS for survivors, stratified by STAT Mortality Category, for the entire period and for 4-year analytic windows. The sensitivity analysis by successive 4-year periods revealed statistically significant decline in discharge mortality across epochs for cases in STAT Mortality Categories 4 and 5 (p values for STAT Mortality Categories 1 through 5 are 0.142, 0.054, 0.099, <0.001, and <0.001, respectively). The increase in the p values relative to those pertaining to analysis of the entire cohort is partly attributable to the reduced sample sizes in all STAT Mortality Categories when analysis is limited to a subset of participants.
Institutional Review Board Approval The Duke Clinical Research Institute serves as the data warehouse and analytic center for all STS National Databases. Approval for the study was obtained from the Duke University Health System Institutional Review Board as well as the Quality Measurement Task Force of the STS Workforce on National Databases and the Access and Publications Task Force of the STS Workforce on Research Development. The Duke University Health System Institutional Review Board provided a waiver of informed consent. Although the STS data used in the analysis contain patient identifiers, they were originally collected for nonresearch purposes, and the risk to patients was deemed to be minimal [15].
Results Analysis of the Entire Cohort The entire cohort encompassed 202,895 index operations performed in 118 centers. The number of centers participating in STS CHSD increased in each epoch. Overall discharge mortality was 3.4% (6,959 of 202,895) for the entire interval from 1998 to 2014 and 3.1% (2,308 of
Comment This 16-year analysis of STS CHSD reveals declining discharge mortality over time, especially for operations in the STAT Mortality Categories that correspond to a higher risk of mortality. PLOS is relatively unchanged over the same time intervals. For the purpose of these analyses, cases were differentiated by means of risk stratification based on the STAT Mortality Categories. Because of the increased availability of robust clinical data, it is now possible to add a variety of specific patient characteristics to pediatric and congenital cardiac surgical risk models [16–18]. Although reporting center-level outcomes as risk-adjusted mortality rates using data currently collected in the STS-CHSD is possible, complete data pertaining to many of the individual patient characteristics that are covariates in the contemporary risk model are not available over the entire 16.5 years of this analysis; and consequently, risk-stratification based on STAT Mortality Categories is the best available option. As is discussed in more detail below, performing similar analysis using more robust methodologies of risk adjustment that include adjustment for individual
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Fig 1. Discharge mortality versus year of operation stratified by The Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery Congenital Heart Surgery (STAT) Mortality Categories: 1 (light blue), 2 (orange), 3 (gray), 4 (yellow), and 5 (dark blue) for the years 1998 to 2014, including all 118 programs.
procedures and patient characteristics will be possible in the future [16–18]. It is important to consider the finding that riskstratified rates of discharge mortality have decreased
over time, especially for more complex operations, but PLOS shows minimal or no change over the same time intervals. It is possible that the observed lack of change in PLOS (or actual small increase for STAT Mortality
Table 1. Discharge Mortality and Postoperative Length of Stay for All Patientsa Variable Participants in STS Congenital Heart Surgery Database, No. Discharge mortality, No. (%) STAT Mortality Category 1 2 3 4 5 Median postoperative length of stay for survivors STAT Mortality Category 1 2 3 4 5
1998–2002
2003–2006
2007–2010
2011–2014
1998–2014
22
64
97
112
118
28/3,327 (0.8) 80/3,917 (2.0) 42/1,286 (3.3) 240/2,335 (10.3) 187/650 (28.8)
78/12,858 (0.6) 210/12,844 (1.6) 145/5,058 (2.9) 712/9,123 (7.8) 352/1,908 (18.4)
140/22,711 (0.6) 386/22,423 (1.7) 247/9,355 (2.6) 1,229/16,427 (7.5) 575/3,336 (17.2)
118/22,167 (0.5) 313/23,151 (1.4) 225/9,553 (2.4) 1,140/17,204 (6.6) 512/3,262 (15.7)
364/61,063 (0.6) 989/62,335 (1.6) 659/25,252 (2.6) 3,321/45,089 (7.4) 1,626/9,156 (17.8)
3 5 7 10 20
4 5 8 10 21
4 6 8 11 25
4 6 8 12 27
4 6 8 11 25
a
Discharge mortality for all patients and postoperative length of stay for survivors, stratified by STAT Mortality Category, for 4-year analytic windows and for the entire period of analysis. STAT ¼ The Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery;
STS ¼ The Society of Thoracic Surgeons.
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Fig 2. Sensitivity analysis: Discharge mortality versus year of operation stratified by The Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery Congenital Heart Surgery (STAT) Mortality Categories: 1 (light blue), 2 (orange), 3 (gray), 4 (yellow), and 5 (dark blue) for the years 1998 to 2014, including only the 30 programs that participated in 2003.
Categories 4 and 5) simply indicates that those additional surviving patients in the later time periods (who may not have survived in earlier periods) required longer PLOS. Determining whether this theory is a correct explanation is not possible from our data. For many years, the focus of analysis of outcomes and improvement of quality for pediatric and congenital cardiac surgery has been limited to short-term mortality. The improvements in short-term mortality documented in this report, combined with the stability of PLOS, provides additional justification for increased emphasis on minimizing morbidity associated with pediatric and congenital cardiac surgery as well as longitudinal assessment of outcomes over time. Because the number of centers participating in STS CHSD increased in each epoch, sensitivity analyses were performed using only centers that participated at the beginning of this study. These sensitivity analyses reveal that the finding of declining risk-stratified rates of discharge mortality over time is not simply attributable to the addition of more centers to the cohort over time. This analysis was not designed to ascertain specific factors that might have influenced the trends that have been documented. Such factors likely include a wide spectrum of improvements to pediatric cardiac care in the domains of structure and process in the preoperative, intraoperative, and postoperative intervals, as well as the enhanced ability to benchmark outcomes at individual institutions to national aggregate outcomes.
Future Directions The new 2014 STS CHSD Mortality Risk Model [16–18] adjusts for individual procedures, which is an even more granular adjustment than adjustment based solely on the STAT Mortality Categories. This new 2014 STS CHSD Mortality Risk Model also includes adjustment for a number of patient-specific characteristics, including prematurity, chromosomal abnormalities, syndromes, noncardiac congenital anatomic abnormalities, and preoperative hemodynamic, respiratory, renal, and neurologic factors, among others. Incorporation of these patient-specific characteristics together with procedurespecific risk estimates will improve the analysis of outcomes over time. In the January 2014 upgrade of the STS CHSD, several procedure-specific factors were added to the data collection form. These new procedure-specific factors pertain to the previously published benchmark operations [19] and should eventually facilitate the development of procedure-specific risk models for these benchmark operations. These procedure-specific risk models may also improve the analysis of outcomes over time. In reality, meaningful evaluation and comparison of outcomes require consideration of both mortality and morbidity, but the latter is much harder to quantify. Discharge mortality is only one aspect of overall performance and should not be equated with the overall performance of a program. To complement the evaluation of quality of care in pediatric and congenital cardiac surgery
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Table 2. Discharge Mortality and Postoperative Length of Stay for Sensitivity Analysisa Variable Participants in STS Congenital Heart Surgery Database, No. Discharge mortality, No. (%) STAT Mortality Category 1 2 3 4 5 Median postoperative length of stay for survivors STAT Mortality Category 1 2 3 4 5
1998–2002
2003–2006
2007–2010
2011–2014
1998–2014
22
21
21
21
21
28/3,327 (0.8) 80/3,917 (2.0) 42/1,286 (3.3) 240/2,335 (10.3) 187/650 (28.8)
33/6,244 (0.5) 105/6,761 (1.6) 70/2,493 (2.8) 371/4,673 (7.9) 182/980 (18.6)
56/7,154 (0.8) 113/6,886 (1.6) 65/2,805 (2.3) 350/4,991 (7.0) 170/1,065 (16.0)
26/5,774 (0.5) 82/5,735 (1.4) 58/2,369 (2.4) 314/4,405 (7.1) 118/787 (15.0)
143/22,499 (0.6) 380/23,299 (1.6) 235/8,953 (2.6) 1,275/16,404 (7.8) 657/3,482 (18.9)
3 5 7 10 20
4 5 8 10 21
4 5 7 10 23
4 6 7 11 27
4 5 7 10 23
a Sensitivity analysis using only the 22 programs which participated in 1998–2002: Discharge mortality for all patients in these 22 programs and postoperative length of stay for survivors, stratified by STAT Mortality Category, for 4-year analytic windows and for the entire period of analysis.
STAT ¼ The Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery;
based on the analysis of risk-adjusted mortality, STS has also developed a tool to stratify procedures using empirically based statistical estimates of procedurespecific morbidity: the STAT Morbidity Categories [20], which encompass the occurrence of major postoperative complications and PLOS. Major postoperative complications and PLOS were both used because models that assume a perfect one-to-one relationship between postoperative complications and PLOS are not likely to fit the data as well. The STAT Morbidity Categories are an empirically based tool that statistically estimates the risk of morbidity associated with operations for pediatric and congenital heart disease [20]. Future initiatives to assess quality and improve outcomes using STS CHSD will adjust for mortality and morbidity based not only on the operation performed but also on patient-specific factors. In the future, when models have been developed that encompass other outcomes in addition to mortality, it may be possible to assess pediatric and congenital cardiac surgical performance using a multidomain composite metric that incorporates mortality and morbidity and adjusts for the operation performed and for patient-specific factors. Finally, although surgeons are intuitively interested in procedural outcomes, this approach runs the risk of defining a population of patients by the operation that is performed. It will be important to assess the outcomes of cohorts of patients over time from the initial diagnosis to adulthood in order to compare outcomes not only of individual procedures but also long-term therapeutic pathways, especially for those complex anatomic problems that often require more than one intervention. Our expectation is that this strategy of assessing short-term
STS ¼ The Society of Thoracic Surgeons.
and also long-term outcomes (of mortality and morbidity) and developing risk-adjustment methods for procedures, and also for therapeutic strategies for specific diagnostic cohorts of patients, will guide our discipline toward continuing improvements in outcomes for our patients.
Conclusions This 16-year analysis of STS CHSD reveals declining discharge mortality over time, especially for more complex operations. PLOS is relatively unchanged over the same time intervals. Author Interview: The Author Interview can be viewed in the online version of this article [http://dx. doi.org/10.1016/j.athoracsur.2016.01.071] on http:// www.annalsthoracicsurgery.org.
References 1. The Society of Thoracic Surgeons. STS National Database. Available at http://www.sts.org/national-database. Accessed September 28, 2015. 2. The Society of Thoracic Surgeons. STS Congenital Heart Surgery Database. Available at http://www.sts.org/nationaldatabase/database-managers/congenital-heart-surgerydatabas. Accessed September 28, 2015. 3. Shahian DM, Grover FL, Prager RL, et al. The Society of Thoracic Surgeons Voluntary Public Reporting Initiative: the first 4 years. Ann Surg 2015;262:526–35. 4. Jacobs ML, Daniel M, Mavroudis C, et al. Report of the 2010 Society of Thoracic Surgeons congenital heart surgery practice and manpower survey. Ann Thorac Surg 2011;92:762–9. 5. International Pediatric and Congenital Cardiac Code. Available at http://www.ipccc.net. Accessed December 30, 2013.
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6. Franklin RC, Jacobs JP, Krogmann ON, et al. Nomenclature for congenital and paediatric cardiac disease: historical perspectives and The International Pediatric and Congenital Cardiac Code. Cardiol Young 2008;18(Suppl 2):70–80. 7. The Society of Thoracic Surgeons. STS Congenital Heart Surgery Database v3.0. Available at http://www.sts. org/sites/default/files/documents/pdf/CongenitalData SpecificationsV3_0_20090904.pdf. Accessed July 4, 2014. 8. Clarke DR, Breen LS, Jacobs ML, et al. Verification of data in congenital cardiac surgery. Cardiol Young 2008;18(Suppl 2): 177–87. 9. Jacobs JP, Jacobs ML, Mavroudis C, Tchervenkov CI, Pasquali SK. Executive summary: The Society of Thoracic Surgeons Congenital Heart Surgery Database—twentieth harvest—(January 1, 2010—December 21, 2013). The Society of Thoracic Surgeons (STS) and Duke Clinical Research Institute (DCRI), Duke University Medical Center, Durham, North Carolina, United States, Spring 2014 Harvest. 10. Jacobs JP, Jacobs ML, Lacour-Gayet FG, et al. Stratification of complexity improves the utility and accuracy of outcomes analysis in a multi-institutional congenital heart surgery database: application of the Risk Adjustment in Congenital Heart Surgery (RACHS-1) and Aristotle Systems in the Society of Thoracic Surgeons (STS) Congenital Heart Surgery Database. Pediatr Cardiol 2009;30:1117–30. 11. O’Brien SM, Clarke DR, Jacobs JP, et al. An empirically based tool for analyzing mortality associated with congenital heart surgery. J Thorac Cardiovasc Surg 2009;138:1139–53. 12. Jacobs JP, Jacobs ML, Maruszewski B, et al. Initial application in the EACTS and STS Congenital Heart Surgery Databases of an empirically derived methodology of complexity adjustment to evaluate surgical case mix and results. Eur J Cardiothorac Surg 2012;42:775–80.
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13. Jacobs JP, Mavroudis C, Jacobs ML, et al. What is operative mortality? Defining death in a surgical registry database: a report from the STS Congenital Database Task Force and the Joint EACTS-STS Congenital Database Committee. Ann Thorac Surg 2006;81:1937–41. 14. Overman D, Jacobs JP, Prager RL, et al. Report from The Society of Thoracic Surgeons National Database Work Force: clarifying the definition of operative mortality. World J Pediatr Congenit Heart Surg 2013;4:10–2. 15. Dokholyan RS, Muhlbaier LH, Falletta J, et al. Regulatory and ethical considerations for linking clinical and administrative databases. Am Heart J 2009;157:971–82. 16. O’Brien SM, Jacobs JP, Pasquali SK, et al. The Society of Thoracic Surgeons Congenital Heart Surgery Database mortality risk model: part 1-statistical methodology. Ann Thorac Surg 2015;100:1054–62. 17. Jacobs JP, O’Brien SM, Pasquali SK, et al. The Society of Thoracic Surgeons Congenital Heart Surgery Database mortality risk model: part 2-clinical application. Ann Thorac Surg 2015;100:1063–8; discussion 1068–70. 18. Pasquali SK, Jacobs ML, O’Brien SM, et al. Impact of patient characteristics on hospital-level outcomes assessment in congenital heart surgery. Ann Thorac Surg 2015;100:1071–6; discussion 1077. 19. Jacobs JP, O’Brien SM, Pasquali SK, et al. Richard E. Clark Paper: Variation in outcomes for benchmark operations: an analysis of the Society of Thoracic Surgeons Congenital Heart Surgery Database. Ann Thorac Surg 2011;92:2184–92. 20. Jacobs ML, O’Brien SM, Jacobs JP, et al. An empirically based tool for analyzing morbidity associated with operations for congenital heart disease. J Thorac Cardiovasc Surg 2013;145: 1046–57.e1.
DISCUSSION DR JOSEPH A. DEARANI (Rochester, MN): Congratulations, Dr Jacobs, on another outstanding retrospective analysis paper from The Society of Thoracic Surgeons (STS) Congenital Heart Surgery Database encompassing a time interval of more than 15 years. The major findings include progressive and significant improvement in early mortality and important improvement in all five of The Society of Thoracic Surgeons— European Association for Cardio-Thoracic Surgery Congenital Heart Surgery (STAT) Mortality Categories of severity of diseases, particularly the more difficult STAT Mortality Categories of 2 to 5. The analysis starts with the beginning of the STS Congenital Heart Surgery Database a long time ago, 1998. This is the same year that you and I had just passed our boards and was the beginning of our professional careers as congenital heart surgeons. A lot has changed since that time. Institutional participation in the STS Congenital Heart Surgery Database has increased from 16 programs to approximately 125, which accounts for more than 95% of programs in North America. Although participation in the STS database is voluntary, improved participation may be due to the importance of being recognized as a “legitimate” program as well as making the program eligible for various national rankings that include U.S. News and World Report. Value and importance of participation in the database must be balanced with the increasing demands and cost of data entry now, with an increasing number of desired variables and the potential consequence of inaccuracy. With that said, 10% of programs supplying data are audited each year, although the detailed digging into individual charts is a bit less than that. Despite these challenges, the data appears to be complete and
accurate with respect to diagnosis, procedure, and discharge mortality. Your finding of progressive improvement in mortality outcomes since 1998 does not surprise me. I believe the cardiothoracic surgery community and the congenital community, in particular, has made a concerted effort to continuously educate and share all of the new and innovative procedures, practice algorithms, and lessons learned in our evolving practice at all of our major meetings, including this one, where we have come to expect excellent clinical science and postgraduate sessions in all three areas of our speciality, adult and pediatric cardiac, and general thoracic surgery. In fact, many of the procedures and techniques that every surgeon in this room does in his or her practice today were not learned during their residency; it was learned sometime thereafter. Our surgical community has found ways to ensure that all of us can do these procedures safely, and the database that you have just presented demonstrates that we are doing it better and better. We should be proud of this. I have three questions for you. Mortality has been the major focus of data analysis to date, and we are approaching all-time lows with mortality, with lesser rooms for improvement. So should we have plans to expand this analysis to examine postoperative morbidity? Number two, similarly, most all of the STS congenital database papers today have either been descriptive or have focussed on early results. Are there plans to address longitudinal outcomes? Finally, public reporting is becoming an increasing requirement, almost an expectation, in all areas of medicine and surgery. Although there is room for further improvement in data acquisition and analysis and there needs to be a reduction in “gaming” of these issues, in principle, I believe it is important for us, that is,
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the medical community, to take control of our own data, risk stratify accordingly, and present it to the public in a meaningful and understandable way as opposed to a nonmedical source, such as the government, to misinterpret it and present it in an inaccurate way that will most certainly create more confusion and concern through the eyes of the public. In light of your recent discussion, maybe you just want to briefly comment on that. Thank you very much. DR JACOBS: Thank you, Dr Dearani. I very much appreciate your discussion. Your kind words of support mean a lot. Compliments from the Chair of the Division of Cardiovascular Surgery at the Mayo Clinic in Rochester, Minnesota, and a friend and colleague for nearly 20 years are especially meaningful. Let me answer each of your three questions in order: First, regarding your comments on morbidity: You are absolutely correct that “Mortality has been the major focus of data analysis to date, and we are approaching all-time lows with mortality, with lesser rooms for improvement.” Therefore, we definitely should expand this analysis to examine postoperative morbidity. We do need to focus not just on mortality, but also to focus on morbidity in our analysis of outcomes. We currently have a funded R01 grant from the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH). Sara Pasquali, MD, from the University of Michigan is the Principal Investigator (PI), and I am The Society of Thoracic Surgeons Principal Investigator (PI). This grant aims to develop and validate a multidomain composite quality metric in congenital heart surgery that incorporates both mortality and
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morbidity, and then to examine the relationship between our composite measure of quality and cost. Joe, you are absolutely correct that we need to augment our analysis of mortality as an outcome with improved strategies to analyze morbidity as an outcome. Second, regarding your comments on longitudinal follow-up: It is a fact that efforts are ongoing to transform the STS database into a platform for longitudinal follow-up. Methodologies to facilitate this transformation will include (1) linking the STS databases to other sources of information that contain longitudinal data, (2) perhaps developing longitudinal follow-up modules within the STS database for specific cohorts of patients, such as those patients requiring device surveillance, and (3) even capitalizing on social media and Facebook to verify life status over time. Finally, regarding your comments on transparency and public reporting: Joe, I would just say that I agree completely with your assessment. Three fundamental principles include: (1) Variation in outcomes exist. (2) Patients and their families have the right to know the outcomes of the treatments that they will receive. (3) It is our professional responsibilities to share this information with them in a format that they can understand. Joe, I agree with you completely that “public reporting is becoming an increasing requirement, almost an expectation, in all areas of medicine and surgery . it is important for us, that is, the medical community, to take control of our own data, risk stratify accordingly, and present it to the public in a meaningful and understandable way.” Thank you.
Background. Previous analyses of The Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database have demonstrated a reduction over time of risk-adjusted operative mortality after coronary artery bypass grafting. The STS Congenital Heart Surgery Database (STS CHSD) was queried to assess multiinstitutional trends over time in discharge mortality and postoperative length of stay (PLOS). Methods. Since 2009, operations in the STS CHSD have been classified according to STAT (The Society of Thoracic Surgeons—European Association for CardioThoracic Surgery) Congenital Heart Surgery Mortality Categories. The five STAT Mortality Categories were chosen to be optimal with respect to minimizing variation within categories and maximizing variation between categories. For this study, all index cardiac operations from 1998 to 2014, inclusive, were grouped by STAT Mortality Category (exclusions: patent ductus arteriosus ligation in patients weighing less than or equal to 2.5 kg and operations that could not be assigned to a STAT Mortality Category). End points were discharge mortality and PLOS in survivors for the entire period and for 4-year epochs. The Cochran-Armitage trend test was used to test
Accepted for publication Jan 11, 2016. Presented at the Sixty-second Annual Meeting of the Southern Thoracic Surgical Association, Orlando, FL, Nov 4–7, 2015. Address correspondence to Dr Jacobs, Johns Hopkins All Children’s Hospital, 601 Fifth St S, Ste 607, St. Petersburg, FL 33701; email: [email protected].
Ó 2016 by The Society of Thoracic Surgeons Published by Elsevier
the null hypothesis that the mortality was the same across epochs, by STAT Mortality Category. Results. The analysis encompassed 202,895 index operations at 118 centers. The number of centers participating in STS CHSD increased in each epoch. Overall discharge mortality was 3.4% (6,959 of 202,895) for 1998 to 2014 and 3.1% (2,308 of 75,337) for 2011 to 2014. Statistically significant improvement in discharge mortality was seen in STAT Mortality Categories 2, 3, 4, and 5 (p values for STAT Mortality Categories 1 through 5 are 0.060, <0.001, 0.015, <0.001, and <0.001, respectively). PLOS in survivors was relatively unchanged over the same time intervals. Sensitivity analyses reveal that the finding of declining risk-stratified rates of discharge mortality over time is not simply attributable to the addition of more centers to the cohort over time. Conclusions. This 16-year analysis of STS CHSD reveals declining discharge mortality over time, especially for more complex operations. (Ann Thorac Surg 2016;-:-–-) Ó 2016 by The Society of Thoracic Surgeons
T
he Society of Thoracic Surgeons (STS) National Database was established in 1989 as an initiative to enhance the quality and safety of cardiothoracic surgery and to provide an accurate and valid basis for measuring performance in our specialty. The STS National Database has three components, each focusing on a different area of cardiothoracic surgery—Adult Cardiac Surgery, 0003-4975/$36.00 http://dx.doi.org/10.1016/j.athoracsur.2016.01.071
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General Thoracic Surgery, and Congenital Heart Surgery [1]. The STS Congenital Heart Surgery Database (CHSD) was founded in 1994 to support quality improvement and patient safety in pediatric and congenital cardiothoracic surgery [2]. Previous analyses of the STS Adult Cardiac Surgery Database have demonstrated a reduction over time of risk-adjusted operative mortality after coronary artery bypass grafting [3]. The purpose of this analysis is to describe congenital and pediatric cardiac surgical trends in multi-institutional outcomes achieved at centers participating in the STS CHSD.
Patients and Methods Data Source The STS CHSD was used for this study. STS CHSD is an audited comprehensive database of patients who have undergone congenital and pediatric cardiac surgical operations at centers in the United States and Canada. STS CHSD is a voluntary registry that contains preoperative, operative, and outcomes data for all patients undergoing congenital and pediatric cardiovascular operations at participating centers. STS CHSD uses the following age groupings: neonates (0 to 30 days), infants (31 days to 1 year), children (>1 year to <18 years), and adults (18 years). The Report of the 2010 STS Congenital Heart Surgery Practice and Manpower Survey, undertaken by the STS Workforce on Congenital Heart Surgery, estimated that 125 hospitals in the United States and 8 hospitals in Canada perform pediatric and congenital heart operations [4]. In 2014, the STS CHSD included 114 congenital heart surgery programs representing 119 of the 125 hospitals (95.2% penetration by hospital) in the United States and 3 of the 8 centers in Canada. Coding for this database is accomplished by clinicians and support staff using the International Pediatric and Congenital Cardiac Code [5, 6] and is entered into the contemporary version of the STS CHSD data collection form [7]. The definitions of all terms and codes from the STS CHSD used in this report have been standardized and published [7]. Evaluation of data quality in the STS CHSD includes intrinsic verification of data (eg, identification and correction of missing/out of range values and inconsistencies across fields), along with a formal process of audits at approximately 10% of all participating centers each year conducted by a panel of independent qualityassurance personnel and pediatric cardiac surgeons [8]. Audit of the STS CHSD has documented the following rates of completeness and accuracy for the specified fields of data [9]: Primary diagnosis (completeness, 100%; accuracy, 96.2%) Primary procedure (completeness, 100%; accuracy, 98.7%) Mortality status at hospital discharge (completeness, 100%; accuracy, 98.8%)
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Accounting for Case Mix Owing to the large number of different types of pediatric and congenital cardiac operations (ie, more than 200 individual procedure types, most often performed in various combinations), it is useful to stratify individual operations into groups or categories that are relatively homogeneous with respect to complexity or risk. This methodology, called complexity stratification (or risk stratification), has been used by STS CHSD since 2002. Risk stratification is a method of analysis in which the data are divided into relatively homogeneous groups (called strata). The data are analyzed and reported within each stratum. STS CHSD has used three methods of risk stratification [10–12]: 1. The Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery (STAT) Congenital Heart Surgery Mortality Categories (STAT Mortality Categories) 2. Aristotle Basic Complexity Levels 3. Risk Adjustment for Congenital Heart Surgery-1 Categories STS CHSD initially used the Aristotle Basic Complexity Levels and the Risk Adjustment for Congenital Heart Surgery-1 Categories to stratify procedures according to degree of complexity and risk. With the increasing availability of multiinstitutional clinical data, the empirically based STAT Mortality Score and STAT Mortality Categories were introduced in the STS CHSD in 2010. The STAT Mortality Categories [11, 12] are a tool for stratification based on the procedure-specific estimate of the risk of discharge mortality, which was developed from an analysis of 77,294 operations entered into the European Association for Cardio-Thoracic Surgery Congenital Heart Surgery Database (33,360 operations) and the STS CHSD (43,934 operations). 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 be optimal with respect to minimizing variation within categories and maximizing variation between categories. STAT Mortality Category 1 is associated with the lowest risk for mortality and STAT Mortality Category 5 is associated with the highest risk for mortality.
Study Population For this study, all index cardiac operations in STS CHSD from January 1998 through June 2014, inclusive, were eligible for inclusion. Index operations are defined as the first cardiac operation of a hospitalization. Patients weighing less than or equal to 2.5 kg undergoing isolated closure of a patent arterial duct were excluded. Operations that could not be assigned a STAT Mortality Category were also excluded. All remaining eligible index cardiac operations were grouped by STAT Mortality Category. The final study cohort included 202,895 index cardiac operations performed in 118 centers.
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Analytic Methodology Data collected included primary procedure of the index cardiac operation, discharge mortality, and postoperative length of stay (PLOS). End points were discharge mortality and PLOS in patients who survived to hospital discharge, for the entire period and for 4-year epochs. It should be noted that STS CHSD now uses operative mortality as an end point and not simply discharge mortality. Discharge mortality is used in this report because operative mortality data are not available in the earlier years of this analysis. Operative mortality is defined in all STS databases as (1) all deaths, regardless of cause, occurring during the hospitalization in which the operation was performed, even if after 30 days (including patients transferred to other acute care facilities); and (2) all deaths, regardless of cause, occurring after discharge from the hospital but before the end of the 30th postoperative day [13, 14]. Mortality and PLOS outcomes were summarized by STAT Mortality Category and year using frequencies and proportions for categorical variables and medians for continuous variables. Outcomes were compared across epochs, by STAT Mortality Category, using the CochranArmitage trend test, which was used to test the null hypothesis that the risk-stratified mortality was the same across epochs. With respect to the year-by-year assessment of outcomes, a sensitivity analysis was performed using data for the entire period but including only the 30 programs that participated in STS CHSD in 2003. A sensitivity analysis was also performed for the epoch analysis involving the 4-year epochs using only the 22 programs that participated in 1998 to 2002. Analyses were performed using SAS 9.3 software (SAS Institute Inc, Cary, NC). A p value of less than 0.05 was considered statistically significant.
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75,337) for the most recent 4-year epoch from 2011 to 2014. Figure 1 plots discharge mortality versus year of operation, stratified by STAT Mortality Category, for the years 1998 to 2014. Table 1 documents discharge mortality for all patients and PLOS for survivors, stratified by STAT Mortality Category, for the entire period and for 4-year analytic windows. The analysis by successive 4-year periods revealed statistically significant decline in discharge mortality across epochs for cases in STAT Mortality Categories 2, 3, 4, and 5 (p values for STAT Mortality Categories 1 through 5 are 0.060, <0.001, 0.015, <0.001, and <0.001, respectively).
Sensitivity Analysis A sensitivity analysis was performed for the year-by-year analysis involving the entire period using only the 30 programs that participated in 2003. Figure 2 plots discharge mortality versus year of operation for these 30 programs, stratified by STAT Mortality Category, for the years 1998 to 2014. An additional sensitivity analysis was performed for the epoch analysis involving the 4-year epochs using only the 22 programs that participated in 1998 to 2002. For these 22 programs, Table 2 documents discharge mortality for all patients and PLOS for survivors, stratified by STAT Mortality Category, for the entire period and for 4-year analytic windows. The sensitivity analysis by successive 4-year periods revealed statistically significant decline in discharge mortality across epochs for cases in STAT Mortality Categories 4 and 5 (p values for STAT Mortality Categories 1 through 5 are 0.142, 0.054, 0.099, <0.001, and <0.001, respectively). The increase in the p values relative to those pertaining to analysis of the entire cohort is partly attributable to the reduced sample sizes in all STAT Mortality Categories when analysis is limited to a subset of participants.
Institutional Review Board Approval The Duke Clinical Research Institute serves as the data warehouse and analytic center for all STS National Databases. Approval for the study was obtained from the Duke University Health System Institutional Review Board as well as the Quality Measurement Task Force of the STS Workforce on National Databases and the Access and Publications Task Force of the STS Workforce on Research Development. The Duke University Health System Institutional Review Board provided a waiver of informed consent. Although the STS data used in the analysis contain patient identifiers, they were originally collected for nonresearch purposes, and the risk to patients was deemed to be minimal [15].
Results Analysis of the Entire Cohort The entire cohort encompassed 202,895 index operations performed in 118 centers. The number of centers participating in STS CHSD increased in each epoch. Overall discharge mortality was 3.4% (6,959 of 202,895) for the entire interval from 1998 to 2014 and 3.1% (2,308 of
Comment This 16-year analysis of STS CHSD reveals declining discharge mortality over time, especially for operations in the STAT Mortality Categories that correspond to a higher risk of mortality. PLOS is relatively unchanged over the same time intervals. For the purpose of these analyses, cases were differentiated by means of risk stratification based on the STAT Mortality Categories. Because of the increased availability of robust clinical data, it is now possible to add a variety of specific patient characteristics to pediatric and congenital cardiac surgical risk models [16–18]. Although reporting center-level outcomes as risk-adjusted mortality rates using data currently collected in the STS-CHSD is possible, complete data pertaining to many of the individual patient characteristics that are covariates in the contemporary risk model are not available over the entire 16.5 years of this analysis; and consequently, risk-stratification based on STAT Mortality Categories is the best available option. As is discussed in more detail below, performing similar analysis using more robust methodologies of risk adjustment that include adjustment for individual
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Fig 1. Discharge mortality versus year of operation stratified by The Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery Congenital Heart Surgery (STAT) Mortality Categories: 1 (light blue), 2 (orange), 3 (gray), 4 (yellow), and 5 (dark blue) for the years 1998 to 2014, including all 118 programs.
procedures and patient characteristics will be possible in the future [16–18]. It is important to consider the finding that riskstratified rates of discharge mortality have decreased
over time, especially for more complex operations, but PLOS shows minimal or no change over the same time intervals. It is possible that the observed lack of change in PLOS (or actual small increase for STAT Mortality
Table 1. Discharge Mortality and Postoperative Length of Stay for All Patientsa Variable Participants in STS Congenital Heart Surgery Database, No. Discharge mortality, No. (%) STAT Mortality Category 1 2 3 4 5 Median postoperative length of stay for survivors STAT Mortality Category 1 2 3 4 5
1998–2002
2003–2006
2007–2010
2011–2014
1998–2014
22
64
97
112
118
28/3,327 (0.8) 80/3,917 (2.0) 42/1,286 (3.3) 240/2,335 (10.3) 187/650 (28.8)
78/12,858 (0.6) 210/12,844 (1.6) 145/5,058 (2.9) 712/9,123 (7.8) 352/1,908 (18.4)
140/22,711 (0.6) 386/22,423 (1.7) 247/9,355 (2.6) 1,229/16,427 (7.5) 575/3,336 (17.2)
118/22,167 (0.5) 313/23,151 (1.4) 225/9,553 (2.4) 1,140/17,204 (6.6) 512/3,262 (15.7)
364/61,063 (0.6) 989/62,335 (1.6) 659/25,252 (2.6) 3,321/45,089 (7.4) 1,626/9,156 (17.8)
3 5 7 10 20
4 5 8 10 21
4 6 8 11 25
4 6 8 12 27
4 6 8 11 25
a
Discharge mortality for all patients and postoperative length of stay for survivors, stratified by STAT Mortality Category, for 4-year analytic windows and for the entire period of analysis. STAT ¼ The Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery;
STS ¼ The Society of Thoracic Surgeons.
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Fig 2. Sensitivity analysis: Discharge mortality versus year of operation stratified by The Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery Congenital Heart Surgery (STAT) Mortality Categories: 1 (light blue), 2 (orange), 3 (gray), 4 (yellow), and 5 (dark blue) for the years 1998 to 2014, including only the 30 programs that participated in 2003.
Categories 4 and 5) simply indicates that those additional surviving patients in the later time periods (who may not have survived in earlier periods) required longer PLOS. Determining whether this theory is a correct explanation is not possible from our data. For many years, the focus of analysis of outcomes and improvement of quality for pediatric and congenital cardiac surgery has been limited to short-term mortality. The improvements in short-term mortality documented in this report, combined with the stability of PLOS, provides additional justification for increased emphasis on minimizing morbidity associated with pediatric and congenital cardiac surgery as well as longitudinal assessment of outcomes over time. Because the number of centers participating in STS CHSD increased in each epoch, sensitivity analyses were performed using only centers that participated at the beginning of this study. These sensitivity analyses reveal that the finding of declining risk-stratified rates of discharge mortality over time is not simply attributable to the addition of more centers to the cohort over time. This analysis was not designed to ascertain specific factors that might have influenced the trends that have been documented. Such factors likely include a wide spectrum of improvements to pediatric cardiac care in the domains of structure and process in the preoperative, intraoperative, and postoperative intervals, as well as the enhanced ability to benchmark outcomes at individual institutions to national aggregate outcomes.
Future Directions The new 2014 STS CHSD Mortality Risk Model [16–18] adjusts for individual procedures, which is an even more granular adjustment than adjustment based solely on the STAT Mortality Categories. This new 2014 STS CHSD Mortality Risk Model also includes adjustment for a number of patient-specific characteristics, including prematurity, chromosomal abnormalities, syndromes, noncardiac congenital anatomic abnormalities, and preoperative hemodynamic, respiratory, renal, and neurologic factors, among others. Incorporation of these patient-specific characteristics together with procedurespecific risk estimates will improve the analysis of outcomes over time. In the January 2014 upgrade of the STS CHSD, several procedure-specific factors were added to the data collection form. These new procedure-specific factors pertain to the previously published benchmark operations [19] and should eventually facilitate the development of procedure-specific risk models for these benchmark operations. These procedure-specific risk models may also improve the analysis of outcomes over time. In reality, meaningful evaluation and comparison of outcomes require consideration of both mortality and morbidity, but the latter is much harder to quantify. Discharge mortality is only one aspect of overall performance and should not be equated with the overall performance of a program. To complement the evaluation of quality of care in pediatric and congenital cardiac surgery
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Table 2. Discharge Mortality and Postoperative Length of Stay for Sensitivity Analysisa Variable Participants in STS Congenital Heart Surgery Database, No. Discharge mortality, No. (%) STAT Mortality Category 1 2 3 4 5 Median postoperative length of stay for survivors STAT Mortality Category 1 2 3 4 5
1998–2002
2003–2006
2007–2010
2011–2014
1998–2014
22
21
21
21
21
28/3,327 (0.8) 80/3,917 (2.0) 42/1,286 (3.3) 240/2,335 (10.3) 187/650 (28.8)
33/6,244 (0.5) 105/6,761 (1.6) 70/2,493 (2.8) 371/4,673 (7.9) 182/980 (18.6)
56/7,154 (0.8) 113/6,886 (1.6) 65/2,805 (2.3) 350/4,991 (7.0) 170/1,065 (16.0)
26/5,774 (0.5) 82/5,735 (1.4) 58/2,369 (2.4) 314/4,405 (7.1) 118/787 (15.0)
143/22,499 (0.6) 380/23,299 (1.6) 235/8,953 (2.6) 1,275/16,404 (7.8) 657/3,482 (18.9)
3 5 7 10 20
4 5 8 10 21
4 5 7 10 23
4 6 7 11 27
4 5 7 10 23
a Sensitivity analysis using only the 22 programs which participated in 1998–2002: Discharge mortality for all patients in these 22 programs and postoperative length of stay for survivors, stratified by STAT Mortality Category, for 4-year analytic windows and for the entire period of analysis.
STAT ¼ The Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery;
based on the analysis of risk-adjusted mortality, STS has also developed a tool to stratify procedures using empirically based statistical estimates of procedurespecific morbidity: the STAT Morbidity Categories [20], which encompass the occurrence of major postoperative complications and PLOS. Major postoperative complications and PLOS were both used because models that assume a perfect one-to-one relationship between postoperative complications and PLOS are not likely to fit the data as well. The STAT Morbidity Categories are an empirically based tool that statistically estimates the risk of morbidity associated with operations for pediatric and congenital heart disease [20]. Future initiatives to assess quality and improve outcomes using STS CHSD will adjust for mortality and morbidity based not only on the operation performed but also on patient-specific factors. In the future, when models have been developed that encompass other outcomes in addition to mortality, it may be possible to assess pediatric and congenital cardiac surgical performance using a multidomain composite metric that incorporates mortality and morbidity and adjusts for the operation performed and for patient-specific factors. Finally, although surgeons are intuitively interested in procedural outcomes, this approach runs the risk of defining a population of patients by the operation that is performed. It will be important to assess the outcomes of cohorts of patients over time from the initial diagnosis to adulthood in order to compare outcomes not only of individual procedures but also long-term therapeutic pathways, especially for those complex anatomic problems that often require more than one intervention. Our expectation is that this strategy of assessing short-term
STS ¼ The Society of Thoracic Surgeons.
and also long-term outcomes (of mortality and morbidity) and developing risk-adjustment methods for procedures, and also for therapeutic strategies for specific diagnostic cohorts of patients, will guide our discipline toward continuing improvements in outcomes for our patients.
Conclusions This 16-year analysis of STS CHSD reveals declining discharge mortality over time, especially for more complex operations. PLOS is relatively unchanged over the same time intervals. Author Interview: The Author Interview can be viewed in the online version of this article [http://dx. doi.org/10.1016/j.athoracsur.2016.01.071] on http:// www.annalsthoracicsurgery.org.
References 1. The Society of Thoracic Surgeons. STS National Database. Available at http://www.sts.org/national-database. Accessed September 28, 2015. 2. The Society of Thoracic Surgeons. STS Congenital Heart Surgery Database. Available at http://www.sts.org/nationaldatabase/database-managers/congenital-heart-surgerydatabas. Accessed September 28, 2015. 3. Shahian DM, Grover FL, Prager RL, et al. The Society of Thoracic Surgeons Voluntary Public Reporting Initiative: the first 4 years. Ann Surg 2015;262:526–35. 4. Jacobs ML, Daniel M, Mavroudis C, et al. Report of the 2010 Society of Thoracic Surgeons congenital heart surgery practice and manpower survey. Ann Thorac Surg 2011;92:762–9. 5. International Pediatric and Congenital Cardiac Code. Available at http://www.ipccc.net. Accessed December 30, 2013.
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6. Franklin RC, Jacobs JP, Krogmann ON, et al. Nomenclature for congenital and paediatric cardiac disease: historical perspectives and The International Pediatric and Congenital Cardiac Code. Cardiol Young 2008;18(Suppl 2):70–80. 7. The Society of Thoracic Surgeons. STS Congenital Heart Surgery Database v3.0. Available at http://www.sts. org/sites/default/files/documents/pdf/CongenitalData SpecificationsV3_0_20090904.pdf. Accessed July 4, 2014. 8. Clarke DR, Breen LS, Jacobs ML, et al. Verification of data in congenital cardiac surgery. Cardiol Young 2008;18(Suppl 2): 177–87. 9. Jacobs JP, Jacobs ML, Mavroudis C, Tchervenkov CI, Pasquali SK. Executive summary: The Society of Thoracic Surgeons Congenital Heart Surgery Database—twentieth harvest—(January 1, 2010—December 21, 2013). The Society of Thoracic Surgeons (STS) and Duke Clinical Research Institute (DCRI), Duke University Medical Center, Durham, North Carolina, United States, Spring 2014 Harvest. 10. Jacobs JP, Jacobs ML, Lacour-Gayet FG, et al. Stratification of complexity improves the utility and accuracy of outcomes analysis in a multi-institutional congenital heart surgery database: application of the Risk Adjustment in Congenital Heart Surgery (RACHS-1) and Aristotle Systems in the Society of Thoracic Surgeons (STS) Congenital Heart Surgery Database. Pediatr Cardiol 2009;30:1117–30. 11. O’Brien SM, Clarke DR, Jacobs JP, et al. An empirically based tool for analyzing mortality associated with congenital heart surgery. J Thorac Cardiovasc Surg 2009;138:1139–53. 12. Jacobs JP, Jacobs ML, Maruszewski B, et al. Initial application in the EACTS and STS Congenital Heart Surgery Databases of an empirically derived methodology of complexity adjustment to evaluate surgical case mix and results. Eur J Cardiothorac Surg 2012;42:775–80.
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13. Jacobs JP, Mavroudis C, Jacobs ML, et al. What is operative mortality? Defining death in a surgical registry database: a report from the STS Congenital Database Task Force and the Joint EACTS-STS Congenital Database Committee. Ann Thorac Surg 2006;81:1937–41. 14. Overman D, Jacobs JP, Prager RL, et al. Report from The Society of Thoracic Surgeons National Database Work Force: clarifying the definition of operative mortality. World J Pediatr Congenit Heart Surg 2013;4:10–2. 15. Dokholyan RS, Muhlbaier LH, Falletta J, et al. Regulatory and ethical considerations for linking clinical and administrative databases. Am Heart J 2009;157:971–82. 16. O’Brien SM, Jacobs JP, Pasquali SK, et al. The Society of Thoracic Surgeons Congenital Heart Surgery Database mortality risk model: part 1-statistical methodology. Ann Thorac Surg 2015;100:1054–62. 17. Jacobs JP, O’Brien SM, Pasquali SK, et al. The Society of Thoracic Surgeons Congenital Heart Surgery Database mortality risk model: part 2-clinical application. Ann Thorac Surg 2015;100:1063–8; discussion 1068–70. 18. Pasquali SK, Jacobs ML, O’Brien SM, et al. Impact of patient characteristics on hospital-level outcomes assessment in congenital heart surgery. Ann Thorac Surg 2015;100:1071–6; discussion 1077. 19. Jacobs JP, O’Brien SM, Pasquali SK, et al. Richard E. Clark Paper: Variation in outcomes for benchmark operations: an analysis of the Society of Thoracic Surgeons Congenital Heart Surgery Database. Ann Thorac Surg 2011;92:2184–92. 20. Jacobs ML, O’Brien SM, Jacobs JP, et al. An empirically based tool for analyzing morbidity associated with operations for congenital heart disease. J Thorac Cardiovasc Surg 2013;145: 1046–57.e1.
DISCUSSION DR JOSEPH A. DEARANI (Rochester, MN): Congratulations, Dr Jacobs, on another outstanding retrospective analysis paper from The Society of Thoracic Surgeons (STS) Congenital Heart Surgery Database encompassing a time interval of more than 15 years. The major findings include progressive and significant improvement in early mortality and important improvement in all five of The Society of Thoracic Surgeons— European Association for Cardio-Thoracic Surgery Congenital Heart Surgery (STAT) Mortality Categories of severity of diseases, particularly the more difficult STAT Mortality Categories of 2 to 5. The analysis starts with the beginning of the STS Congenital Heart Surgery Database a long time ago, 1998. This is the same year that you and I had just passed our boards and was the beginning of our professional careers as congenital heart surgeons. A lot has changed since that time. Institutional participation in the STS Congenital Heart Surgery Database has increased from 16 programs to approximately 125, which accounts for more than 95% of programs in North America. Although participation in the STS database is voluntary, improved participation may be due to the importance of being recognized as a “legitimate” program as well as making the program eligible for various national rankings that include U.S. News and World Report. Value and importance of participation in the database must be balanced with the increasing demands and cost of data entry now, with an increasing number of desired variables and the potential consequence of inaccuracy. With that said, 10% of programs supplying data are audited each year, although the detailed digging into individual charts is a bit less than that. Despite these challenges, the data appears to be complete and
accurate with respect to diagnosis, procedure, and discharge mortality. Your finding of progressive improvement in mortality outcomes since 1998 does not surprise me. I believe the cardiothoracic surgery community and the congenital community, in particular, has made a concerted effort to continuously educate and share all of the new and innovative procedures, practice algorithms, and lessons learned in our evolving practice at all of our major meetings, including this one, where we have come to expect excellent clinical science and postgraduate sessions in all three areas of our speciality, adult and pediatric cardiac, and general thoracic surgery. In fact, many of the procedures and techniques that every surgeon in this room does in his or her practice today were not learned during their residency; it was learned sometime thereafter. Our surgical community has found ways to ensure that all of us can do these procedures safely, and the database that you have just presented demonstrates that we are doing it better and better. We should be proud of this. I have three questions for you. Mortality has been the major focus of data analysis to date, and we are approaching all-time lows with mortality, with lesser rooms for improvement. So should we have plans to expand this analysis to examine postoperative morbidity? Number two, similarly, most all of the STS congenital database papers today have either been descriptive or have focussed on early results. Are there plans to address longitudinal outcomes? Finally, public reporting is becoming an increasing requirement, almost an expectation, in all areas of medicine and surgery. Although there is room for further improvement in data acquisition and analysis and there needs to be a reduction in “gaming” of these issues, in principle, I believe it is important for us, that is,
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the medical community, to take control of our own data, risk stratify accordingly, and present it to the public in a meaningful and understandable way as opposed to a nonmedical source, such as the government, to misinterpret it and present it in an inaccurate way that will most certainly create more confusion and concern through the eyes of the public. In light of your recent discussion, maybe you just want to briefly comment on that. Thank you very much. DR JACOBS: Thank you, Dr Dearani. I very much appreciate your discussion. Your kind words of support mean a lot. Compliments from the Chair of the Division of Cardiovascular Surgery at the Mayo Clinic in Rochester, Minnesota, and a friend and colleague for nearly 20 years are especially meaningful. Let me answer each of your three questions in order: First, regarding your comments on morbidity: You are absolutely correct that “Mortality has been the major focus of data analysis to date, and we are approaching all-time lows with mortality, with lesser rooms for improvement.” Therefore, we definitely should expand this analysis to examine postoperative morbidity. We do need to focus not just on mortality, but also to focus on morbidity in our analysis of outcomes. We currently have a funded R01 grant from the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH). Sara Pasquali, MD, from the University of Michigan is the Principal Investigator (PI), and I am The Society of Thoracic Surgeons Principal Investigator (PI). This grant aims to develop and validate a multidomain composite quality metric in congenital heart surgery that incorporates both mortality and
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morbidity, and then to examine the relationship between our composite measure of quality and cost. Joe, you are absolutely correct that we need to augment our analysis of mortality as an outcome with improved strategies to analyze morbidity as an outcome. Second, regarding your comments on longitudinal follow-up: It is a fact that efforts are ongoing to transform the STS database into a platform for longitudinal follow-up. Methodologies to facilitate this transformation will include (1) linking the STS databases to other sources of information that contain longitudinal data, (2) perhaps developing longitudinal follow-up modules within the STS database for specific cohorts of patients, such as those patients requiring device surveillance, and (3) even capitalizing on social media and Facebook to verify life status over time. Finally, regarding your comments on transparency and public reporting: Joe, I would just say that I agree completely with your assessment. Three fundamental principles include: (1) Variation in outcomes exist. (2) Patients and their families have the right to know the outcomes of the treatments that they will receive. (3) It is our professional responsibilities to share this information with them in a format that they can understand. Joe, I agree with you completely that “public reporting is becoming an increasing requirement, almost an expectation, in all areas of medicine and surgery . it is important for us, that is, the medical community, to take control of our own data, risk stratify accordingly, and present it to the public in a meaningful and understandable way.” Thank you.