A significant association between care process and outcomes was found, supporting the use of broad, guideline-based performance metrics as a means of assessing and helping improve hospital quality.

Background Treatments for non–ST-segment elevation myocardial infarction (NSTEMI) reduce ischemic events but increase bleeding. Baseline prediction of bleeding risk can complement ischemic risk prediction for optimizing NSTEMI care; however, existing models are not well suited for this purpose. Methods and Results We developed (n=71,277) and validated (n=17,857) a model that identifies 8 independent baseline predictors of in-hospital major bleeding among community-treated NSTEMI patients enrolled in the CRUSADE Quality Improvement Initiative. Model performance was tested by c statistics in the derivation and validation cohorts and according to post-admission treatment (i.e., invasive and antithrombotic therapy). The CRUSADE bleeding score (range 1–100 points) was created by assigning weighted integers corresponding to the coefficient of each variable. The rate of major bleeding increased by bleeding risk score quintiles: 3.1% very low risk (≤20); 5.5% low risk (21–30); 8.6% moderate risk (31–40); 11.9% high risk (41–50); and 19.5% very high risk (>50) (Ptrend<0.001). The c statistics for the major bleeding model (derivation=0.72 and validation=0.71) and risk score (derivation=0.71 and validation=0.70) were similar. The c statistics for the model among treatment subgroups were: ≥2 antithrombotics=0.72; <2 antithrombotics=0.73; invasive approach=0.73; conservative approach=0.68. Conclusion The CRUSADE bleeding score quantifies risk for in-hospital major bleeding across all post-admission treatments, enhancing baseline risk assessment for NSTEMI care.

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