The researchers used three data models from patients undergoing surgery at the Aurora-based University of Colorado Hospital between 2013 and 2015.
Here are the key research insights to know:
1. Out of 6,840 patients, 230 had an SSI.
2. The model identified the infections with 80 percent sensitivity and 90 percent specificity.
3. “We identified a model that accurately identified SSIs. The framework presented can be easily implemented by other American College of Surgeons National Surgical Quality Improvement Program-participating hospitals to develop models for enhancing surveillance of SSIs,” the researchers concluded.
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