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Updated: Jun 29, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Using risk-adjusted cumulative sum to evaluate surgeon, divisional, and institutional outcomes-a feasibility study
Kyle W Blackburn1, Laura E Cooper2, Andrea C Bafford3
1School of Medicine, Baylor College of Medicine, Waco, TX. Electronic address: https://twitter.com/KyleWBlackburn.
Background:
Few objective, real-time measurements of surgeon performance exist. The risk-adjusted cumulative sum is a novel method that can track surgeon-level outcomes on a continuous basis. The objective of this study was to demonstrate the feasibility of using risk-adjusted cumulative sum to monitor outcomes after colorectal operations and identify clinically relevant performance variations.
Methods:
The National Surgical Quality Improvement Program was queried to obtain patient-level data for 1,603 colorectal operations at a high-volume center from 2011 to 2020. For each case, expected risks of morbidity, mortality, reoperation, readmission, and prolonged length of stay were estimated using the National Surgical Quality Improvement Program risk calculator. Risk-adjusted cumulative sum curves were generated to signal observed-to-expected odds ratios of 1.5 (poor performance) and 0.5 (exceptional performance). Control limits were set based on a false positive rate of 5% (α = 0.05).
Results:
The cohort included data on 7 surgeons (those with more than 20 cases in the study period). Institutional observed versus expected outcomes were the following: morbidity 12.5% (vs 15.0%), mortality 2.5% (vs 2.0%), prolonged length of stay 19.7% (vs 19.1%), reoperation 11.1% (vs 11.3%), and 30-day readmission 6.1% (vs 4.8%). Risk-adjusted cumulative sum accurately demonstrated within- and between-surgeon performance variations across these metrics and proved effective when considering division-level data.
Conclusion:
Risk-adjusted cumulative sum adjusts for patient-level risk factors to provide real-time data on surgeon-specific outcomes. This approach enables prompt identification of performance outliers and can contribute to quality assurance, root-cause analysis, and incentivization not only at the surgeon level but at divisional and institutional levels as well.
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