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The impact of surgical volume on hospital ranking using the standardized infection ratio
Shangyuan Ye1,2, Daniel Li3, Tingting Yu1
1Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA, 02215, USA.
Abstract:
The Centers for Medicare and Medicaid Services require hospitals to report on quality metrics which are used to financially penalize those that perform in the lowest quartile. Surgical site infections (SSIs) are a critical component of the quality metrics that target healthcare-associated infections. However, the accuracy of such hospital profiling is highly affected by small surgical volumes which lead to a large amount of uncertainty in estimating standardized hospital-specific infection rates. Currently, hospitals with less than one expected SSI are excluded from rankings, but the effectiveness of this exclusion criterion is unknown. Tools that can quantify the classification accuracy and can determine the minimal surgical volume required for a desired level of accuracy are lacking. We investigate the effect of surgical volume on the accuracy of identifying poorly performing hospitals based on the standardized infection ratio and develop simulation-based algorithms for quantifying the classification accuracy. We apply our proposed method to data from HCA Healthcare (2014-2016) on SSIs in colon surgery patients. We estimate that for a procedure like colon surgery with an overall SSI rate of 3%, to rank hospitals in the HCA colon SSI dataset, hospitals that perform less than 200 procedures have a greater than 10% chance of being incorrectly assigned to the worst performing quartile. Minimum surgical volumes and predicted events criteria are required to make evaluating hospitals reliable, and these criteria vary by overall prevalence and between-hospital variability.
Insights
Hospital quality metrics for surgical site infections (SSIs) are unreliable with low patient volumes. Small surgical volumes increase uncertainty, impacting accurate hospital profiling and financial penalties for healthcare-associated infections.
Area of Science:
- Healthcare quality measurement
- Infectious disease epidemiology
- Health services research
Background:
- Hospitals face financial penalties based on quality metrics, including surgical site infections (SSIs).
- Accurate hospital profiling is challenged by low surgical volumes, leading to uncertainty in standardized infection rates.
- Current exclusion criteria for low-volume hospitals are not well-validated.
Purpose of the Study:
- To investigate how surgical volume impacts the accuracy of identifying poorly performing hospitals using the standardized infection ratio (SIR).
- To develop simulation-based algorithms for quantifying classification accuracy.
- To determine minimal surgical volumes needed for reliable hospital performance evaluation.
Main Methods:
- Simulation-based algorithms were developed to quantify classification accuracy.
- The proposed method was applied to colon surgery data from HCA Healthcare (2014-2016).
- Analysis focused on the relationship between surgical volume and the probability of misclassification into the lowest performance quartile.
Main Results:
- Hospitals performing fewer than 200 colon surgery procedures had a >10% chance of incorrect classification in the worst quartile.
- This estimation is based on an overall SSI rate of 3% for colon surgery.
- The study highlights significant uncertainty in SIR-based rankings for low-volume hospitals.
Conclusions:
- Minimum surgical volumes and predicted events criteria are essential for reliable hospital performance evaluation.
- These criteria must account for overall infection prevalence and variability between hospitals.
- Current quality metric systems may inaccurately penalize low-volume hospitals due to statistical uncertainty.
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