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Updated: Jul 9, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Risk-adjusted sequential probability ratio test control chart methods for monitoring operator and institutional
Michael E Matheny1, Lucila Ohno-Machado, Frederic S Resnic
1Decision Systems Group, Department of Radiology, Brigham and Women's Hospital, MA, USA. michael.matheny@vanderbilt.edu
Background:
The objective of this study was to evaluate risk-adjusted sequential probability ratio test control charts for the detection of significant discrepancies between institution or individual interventional cardiologist postprocedural mortality rates and national or local event rate expectations.
Methods:
Eight thousand nine hundred forty-two percutaneous coronary interventional procedures were performed by 27 operators between January 1, 2002, and November 30, 2006. The institution-based evaluation included all procedures, and the individual-based evaluations included 8750 procedures performed by 18 operators who had each done at least 100 PCI procedures. Risk-adjusted sequential probability ratio test control charts were developed to assess whether the odds ratios (ORs) for death were >2.0 for alpha = beta = 0.10. The American College of Cardiology 1.1 prediction model was used to risk-adjust both the institution and individuals, and an additional local model was used for individuals.
Results:
After national risk adjustment, the local institution did not show mortality of more than a 1.5 OR. Two operators had a >2.0 mortality OR after national risk adjustment, and one of those remained elevated after local risk adjustment. Of 18 operators, 10 had insufficient data to allow us to accept or reject the hypothesis of increased risk.
Conclusions:
The local institution performed within national expectations, but 1 operator was identified as having poor performance, which prompted an in-depth review of that operator's cases. The review revealed that the operator had an unusually high number of patients who presented with risk factors not included in the risk-adjustment models. This study highlights the utility of risk-adjusted sequential probability ratio test as a method for outcomes monitoring and quality control in interventional cardiology.
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