Updating an Empirically Based Tool for Analyzing Congenital Heart Surgery Mortality

2021 ◽  
Vol 12 (2) ◽  
pp. 246-281 ◽  
Author(s):  
Marshall L. Jacobs ◽  
Jeffrey P. Jacobs ◽  
Dylan Thibault ◽  
Kevin D. Hill ◽  
Brett R. Anderson ◽  
...  

Objectives: STAT Mortality Categories (developed 2009) stratify congenital heart surgery procedures into groups of increasing mortality risk to characterize case mix of congenital heart surgery providers. This update of the STAT Mortality Score and Categories is empirically based for all procedures and reflects contemporary outcomes. Methods: Cardiovascular surgical operations in the Society of Thoracic Surgeons Congenital Heart Surgery Database (January 1, 2010 – June 30, 2017) were analyzed. In this STAT 2020 Update of the STAT Mortality Score and Categories, the risk associated with a specific combination of procedures was estimated under the assumption that risk is determined by the highest risk individual component procedure. Operations composed of multiple component procedures were eligible for unique STAT Scores when the statistically estimated mortality risk differed from that of the highest risk component procedure. Bayesian modeling accounted for small denominators. Risk estimates were rescaled to STAT 2020 Scores between 0.1 and 5.0. STAT 2020 Category assignment was designed to minimize within-category variation and maximize between-category variation. Results: Among 161,351 operations at 110 centers (19,090 distinct procedure combinations), 235 types of single or multiple component operations received unique STAT 2020 Scores. Assignment to Categories resulted in the following distribution: STAT 2020 Category 1 includes 59 procedure codes with model-based estimated mortality 0.2% to 1.3%; Category 2 includes 73 procedure codes with mortality estimates 1.4% to 2.9%; Category 3 includes 46 procedure codes with mortality estimates 3.0% to 6.8%; Category 4 includes 37 procedure codes with mortality estimates 6.9% to 13.0%; and Category 5 includes 17 procedure codes with mortality estimates 13.5% to 38.7%. The number of procedure codes with empirically derived Scores has grown by 58% (235 in STAT 2020 vs 148 in STAT 2009). Of the 148 procedure codes with empirically derived Scores in 2009, approximately one-half have changed STAT Category relative to 2009 metrics. The New STAT 2020 Scores and Categories demonstrated good discrimination for predicting mortality in an independent validation sample (July 1, 2017-June 30, 2019; sample size 46,933 operations at 108 centers) with C-statistic = 0.791 for STAT 2020 Score and 0.779 for STAT 2020 Category. Conclusions: The updated STAT metrics reflect contemporary practice and outcomes. New empirically based STAT 2020 Scores and Category designations are assigned to a larger set of procedure codes, while accounting for risk associated with multiple component operations. Updating STAT metrics based on contemporary outcomes facilitates accurate assessment of case mix.

2020 ◽  
Vol 11 (5) ◽  
pp. 557-562 ◽  
Author(s):  
Peter Murin ◽  
Viktoria Weixler ◽  
Mi-Young Cho ◽  
Valentin Vadiunec ◽  
Oliver Miera ◽  
...  

Background: Duration of mechanical ventilation is an important variable used by German Diagnosis-Related Groups (G-DRG) system to establish cost weight values for reimbursement after congenital heart surgery. Infants are commonly ventilated after open heart surgery. As of year 2015, we strived to achieve early postoperative extubation. This work studies how this approach impacted reimbursement after infant open heart surgery. Methods: Data of infants who underwent surgery on cardiopulmonary bypass (CPB) from 2014 to 2018 were reviewed. Successful early extubation was defined as end of mechanical ventilation within 24 hours postoperatively, without reintubation at a later point. Mean cost weight values (case mix index [CMI]) of achieved DRGs were used for estimation of reimbursement. Evolutions over years of early extubation and of reimbursement were compared. Results: A total of 521 infants underwent operations on CPB. Of these, 161 (31%) procedures were of higher risk Society of Thoracic Surgery and the European Association for Cardio-Thoracic Surgery (STAT) categories 3 and 4. Early extubation was achieved in 205 (39%) patients. The rate increased from 14% (year 2014) to 57% (year 2018). Case mix index amounted to 8.87 ± 7.00 after early extubation, and 12.37 ± 7.85 after late extubation: P value <.0001. It was 8.77 ± 6.09 after early extubation in patients undergoing lower risk STAT categories 1 and 2 operations, and 8.09 ± 2.95 when categories 3 and 4 procedures were performed ( P = .18). An overall 14.4% decrease in hospital reimbursement per patient was observed. Conclusion: Early extubation could be progressively obtained in the majority of infants. This resulted in lower reimbursement. Surgical complexity was disregarded. The current G-DRG system appears to favor longer mechanical ventilation durations after infant open heart surgery.


2015 ◽  
Vol 100 (5) ◽  
pp. 1728-1736 ◽  
Author(s):  
Stephanie M. Fuller ◽  
Xia He ◽  
Jeffrey P. Jacobs ◽  
Sara K. Pasquali ◽  
J. William Gaynor ◽  
...  

Author(s):  
Dimitris Bertsimas ◽  
Daisy Zhuo ◽  
Jordan Levine ◽  
Jack Dunn ◽  
Zdzislaw Tobota ◽  
...  

Background: We have previously shown that the machine learning methodology of optimal classification trees (OCTs) can accurately predict risk after congenital heart surgery (CHS). We have now applied this methodology to define benchmarking standards after CHS, permitting case-adjusted hospital-specific performance evaluation. Methods: The European Congenital Heart Surgeons Association Congenital Database data subset (31 792 patients) who had undergone any of the 10 “benchmark procedure group” primary procedures were analyzed. OCT models were built predicting hospital mortality (HM), and prolonged postoperative mechanical ventilatory support time (MVST) or length of hospital stay (LOS), thereby establishing case-adjusted benchmarking standards reflecting the overall performance of all participating hospitals, designated as the “virtual hospital.” These models were then used to predict individual hospitals’ expected outcomes (both aggregate and, importantly, for risk-matched patient cohorts) for their own specific cases and case-mix, based on OCT analysis of aggregate data from the “virtual hospital.” Results: The raw average rates were HM = 4.4%, MVST = 15.3%, and LOS = 15.5%. Of 64 participating centers, in comparison with each hospital's specific case-adjusted benchmark, 17.0% statistically (under 90% confidence intervals) overperformed and 26.4% underperformed with respect to the predicted outcomes for their own specific cases and case-mix. For MVST and LOS, overperformers were 34.0% and 26.4%, and underperformers were 28.3% and 43.4%, respectively. OCT analyses reveal hospital-specific patient cohorts of either overperformance or underperformance. Conclusions: OCT benchmarking analysis can assess hospital-specific case-adjusted performance after CHS, both overall and patient cohort-specific, serving as a tool for hospital self-assessment and quality improvement.


2015 ◽  
Vol 100 (3) ◽  
pp. 1063-1070 ◽  
Author(s):  
Jeffrey P. Jacobs ◽  
Sean M. O’Brien ◽  
Sara K. Pasquali ◽  
J. William Gaynor ◽  
John E. Mayer ◽  
...  

2008 ◽  
Vol 18 (S2) ◽  
pp. 163-168 ◽  
Author(s):  
Marshall Lewis Jacobs ◽  
Jeffrey Phillip Jacobs ◽  
Kathy J. Jenkins ◽  
Kimberlee Gauvreau ◽  
David R. Clarke ◽  
...  

AbstractMeaningful evaluation of quality of care must account for variations in the population of patients receiving treatment, or “case-mix”. In adult cardiac surgery, empirical clinical data, initially from tens of thousands, and more recently hundreds of thousands of operations, have been used to develop risk-models, to increase the accuracy with which the outcome of a given procedure on a given patient can be predicted, and to compare outcomes on non-identical patient groups between centres, surgeons and eras.In the adult cardiac database of The Society of Thoracic Surgeons, algorithms for risk-adjustment are based on over 1.5 million patients undergoing isolated coronary artery bypass grafting and over 100,000 patients undergoing isolated replacement of the aortic valve or mitral valve. In the pediatric and congenital cardiac database of The Society of Thoracic Surgeons, 61,014 operations are spread out over greater than 100 types of primary procedures. The problem of evaluating quality of care in the management of pediatric patients with cardiac diseases is very different, and in some ways a great deal more challenging, because of the smaller number of patients and the higher number of types of operations.In the field of pediatric cardiac surgery, the importance of the quantitation of the complexity of operations centers on the fact that outcomes analysis using raw measurements of mortality, without adjustment for complexity, is inadequate. Case-mix can vary greatly from program to program. Without stratification of complexity, the analysis of outcomes for congenital cardiac surgery will be flawed. Two major multi-institutional efforts have attempted to measure the complexity of pediatric cardiac operations: the Risk Adjustment in Congenital Heart Surgery-1 method and the Aristotle Complexity Score. Both systems were derived in large part from subjective probability, or expert opinion. Both systems are currently in wide use throughout the world and have been shown to correlate reasonably well with outcome.Efforts are underway to develop the next generation of these systems. The next generation will be based more on objective data, but will continue to utilize subjective probability where objective data is lacking. A goal, going forward, is to re-evaluate and further refine these tools so that, they can be, to a greater extent, derived from empirical data. During this process, ideally, the mortality elements of both the Aristotle Complexity Score and the Risk Adjustment in Congenital Heart Surgery-1 methodology will eventually unify and become one and the same. This review article examines these two systems of stratification of complexity and reviews the rationale for the development of each system, the current use of each system, the plans for future enhancement of each system, and the potential for unification of these two tools.


2015 ◽  
Vol 100 (3) ◽  
pp. 1054-1062 ◽  
Author(s):  
Sean M. O’Brien ◽  
Jeffrey P. Jacobs ◽  
Sara K. Pasquali ◽  
J. William Gaynor ◽  
Tara Karamlou ◽  
...  

2016 ◽  
Vol 102 (5) ◽  
pp. 1580-1587 ◽  
Author(s):  
Sara K. Pasquali ◽  
Amelia S. Wallace ◽  
J. William Gaynor ◽  
Marshall L. Jacobs ◽  
Sean M. O’Brien ◽  
...  

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