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Published on: February 10, 2022
Systems of Care Factors Should Be Considered in Regionalization of Congenital Cardiac Surgery
Petros V Anagnostopoulos1, Randi S Cartmill1, Qiuyu Yang1
1Department of Surgery, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin.
Background:
Regionalization of care has been proposed to optimize outcomes in congenital cardiac surgery (CCS). We hypothesized that hospital infrastructure and systems of care factors could also be considered in regionalization efforts.
Methods:
Observed-to-expected (O/E) mortality ratio and hospital volumes were obtained between 2015 and 2018 from public reporting data. Using a resource dependence framework, we examined factors obtained from American Hospital Association, Children's Hospital Association, and hospital websites. Linear regression models were estimated with volume only, then with hospital factors, stratified by procedural complexity. Robust regression models were reestimated to assess the impact of outliers.
Results:
We found wide variation in the volume of congenital cardiac surgeries performed (89-3920) and in the surgical outcomes (O/E ratio range, 0.3-3.1). Six outlier hospitals performed few high-complexity cases with high mortality. Univariate analysis including all cases indicated that higher volume predicted lower O/E ratio (β = -0.02; SE = 0.008; P = .011). However, this effect was driven by the most complex cases. Models stratified by The Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery category show that volume is a significant predictor only in category 5 cases (β = -1.707; SE = 0.663; P = .012). Robust univariate regression accounting for outliers found no effect of volume on O/E ratio (β = 0.005; SE = 0.002; P = .975). Elimination of outliers through robust multivariate regression decreased the volume-outcome relationship and found a modest relationship between health plan ownership and outcomes.
Conclusions:
Systems of care factors should be considered in addition to volume in designing regionalization in CCS. Patient-level data sets will better define these factors.
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