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Case volume and mortality in pediatric cardiac surgery patients in California, 1998-2003
Lianna G Bazzani1, James P Marcin
1University of Texas School of Public Health, Houston, USA.
Insights
The relationship between pediatric cardiac surgery volume and mortality has weakened. A new model shows higher volume is linked to lower mortality, particularly at the highest-volume hospital.
Area of Science:
- Pediatric Cardiac Surgery
- Health Services Research
- Hospital Quality Metrics
Background:
- Previous studies indicated an inverse relationship between pediatric cardiac surgery case volume and in-hospital mortality.
- This association has been observed to be diminishing for coronary artery bypass grafting (CABG) due to potential improvements in training and quality initiatives.
- It remains unclear if a similar trend is occurring for pediatric cardiac surgery patients.
Purpose of the Study:
- To investigate the current association between pediatric cardiac surgery case volume and in-hospital mortality.
- To determine if the previously reported volume-mortality relationship has changed in contemporary pediatric cardiac surgery.
- To develop and test an updated model for assessing the volume-mortality relationship.
Main Methods:
- Utilized the state of California's patient discharge data from 1998-2003.
- Replicated methodologies from four prior studies on pediatric cardiac surgery volume and mortality.
- Developed a novel model incorporating elements of previous models to analyze the volume-mortality association.
Main Results:
- A weaker and less consistent volume-mortality relationship was found compared to previous reports.
- The updated model revealed a statistically significant association between higher annual surgical volume and lower in-hospital mortality (OR=0.86 per 100-patient increase).
- Post hoc analyses indicated this association was primarily driven by the performance of the single highest-volume hospital.
Conclusions:
- The volume-mortality relationship in pediatric cardiac surgery has evolved, rendering older models less descriptive of a clear association.
- An updated model using a continuous volume definition demonstrates an association, but it is heavily influenced by the largest-volume hospital's data.
- Findings suggest a shift in the volume-outcome relationship, emphasizing the impact of high-volume centers and potentially specific institutional practices.
Background:
Previous reports have found an inverse relationship between pediatric cardiac surgery case volume and in-hospital mortality. This association has been noted recently to be decreasing for coronary artery bypass grafting, possibly because of improved training programs, quality improvement activities, or other innovations to improve outcomes. It is unknown whether the volume-mortality association among pediatric cardiac surgery patients is decreasing similarly.
Methods And Results:
We used data from the state of California's patient discharge data set from the years 1998-2003 to replicate 4 previous research studies of pediatric cardiac surgery volume and mortality. The total number of pediatric surgeries varied from 12,801 to 13,971 depending on the selection criteria applied. Using this larger and more contemporary data set, we found a weaker and less consistent volume-mortality relationship than had been reported previously. We also developed a new model, which incorporated elements of the old models, and found a statistically significant relationship with higher volume and lower mortality (odds ratio=0.86 per 100-patient increase in annual volume; 95% CI, 0.81 to 0.92). Post hoc analyses show that this relationship was related to the performance of the single largest-volume hospital.
Conclusions:
With the use of data from California, the volume-mortality relationship among pediatric cardiac surgery patients has changed since previous research, such that the old models no longer describe a clear or consistent association. With the use of a continuous definition of volume and an updated model, an association is observed but is dependent on highly leveraged covariate patterns found in the largest-volume hospital.
