Background: The National Surgical Quality Improvement Program (NSQIP) has proposed using procedure-based hierarchical models to predict adverse outcomes, but it is not clear whether this approach was used to develop the NSQIP "Surgical Risk Calculator". We therefore wished to demonstrate how procedure-based hierarchical models can be constructed and to describe their results.
Methods: NSQIP data from 2015 were used to construct statistical models predicting 30-day postoperative mortality and morbidity, using two-level logistic regression with preoperative patient-level variables as fixed effects and procedure-specific codes as a random intercept.