Related Experiment Video
Updated: Mar 28, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Risk Prediction Accuracy Differs for Emergency Versus Elective Cases in the ACS-NSQIP
Joseph A Hyder1, Gally Reznor, Elliot Wakeam
1*Department of Anesthesiology and Division of Respiratory and Critical Care Medicine, Mayo Clinic, Rochester, MN†Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN‡Center for Surgery and Public Health, Brigham and Women's Hospital, Boston, MA§Department of Surgery, University of Toronto, Toronto, Ontario, Canada¶Department of Medicine, Brigham and Women's Hospital, Boston, MA||Department of Surgery, Brigham and Women's Hospital, Boston, MA**Harvard Medical School, Boston, MA.
Background:
Accurate risk estimation is essential when benchmarking surgical outcomes for reimbursement and engaging in shared decision-making. The greater complexity of emergency surgery patients may bias outcome comparisons between elective and emergency cases.
Objective:
To test whether an established risk modelling tool, the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) predicts mortality comparably for emergency and elective cases.
Methods:
From the ACS-NSQIP 2011-2012 patient user files, we selected core emergency surgical cases also common to elective scenarios (gastrointestinal, vascular, and hepato-biliary-pancreatic). After matching strategy for Common Procedure Terminology (CPT) and year, we compared the accuracy of ACS-NSQIP predicted mortality probabilities using the observed-to-expected ratio (O:E), c-statistic, and Brier score.
Results:
In all, 56,942 emergency and 136,311 elective patients were identified as having a common CPT and year. Using a 1:1 matched sample of 37,154 emergency and elective patients, the O:E ratios generated by ACS-NSQIP models differ significantly between the emergency [O:E = 1.031; 95% confidence interval (CI) = 1.028-1.033] and elective populations (O:E = 0.79; 95% CI = 0.77-0.80, P < 0.0001) and the c-statistics differed significantly (emergency c-statistic = 0.927; 95% CI = 0.921-0.932 and elective c-statistic = 0.887; 95% CI = 0.861-0.912, P = 0.003). The Brier score, tested across a range of mortality rates, did not differ significantly for samples with mortality rates of 6.5% and 9% (eg, emergency Brier score = 0.058; 95% CI = 0.048-0.069 versus elective Brier score = 0.057; 95% CI = 0.044-0.07, P = 0.87, among 2217 patients with 6.5% mortality). When the mortality rate was low (1.7%), Brier scores differed significantly (emergency 0.034; 95% CI = 0.027-0.041 versus elective 0.016; 95% CI = 0.009-0.023, P value for difference 0.0005).
Conclusion:
ACS-NSQIP risk estimates used for benchmarking and shared decision-making appear to differ between emergency and elective populations.
More Related Videos
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
Related Concept Videos
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Relative Risk
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...
Receiver Operating Characteristic Plot
Accuracy and Errors in Hypothesis Testing
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...