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The past decade has been characterized by increased scrutiny of outcomes of surgical and percutaneous coronary interventions (PCIs). This increased scrutiny has led to the development of regional, state, and national databases for outcome assessment and for public reporting. This report describes the initial development of a regional, collaborative, cardiovascular consortium and the progress made so far by this collaborative group. In 1997, a group of hospitals in the state Michigan agreed to create a regional collaborative consortium for the development of a quality improvement program in interventional cardiology. The project included the creation of a comprehensive database of PCIs to be used for risk assessment, feedback on absolute and risk-adjusted outcomes, and sharing of information. To date, information from nearly 20,000 PCIs have been collected. A risk prediction tool for death in the hospital and additional risk prediction tools for other outcomes have been developed from the data collected, and are currently used by the participating centers for risk assessment and for quality improvement. As the project enters into year 5, the participating centers are deeply engaged in the quality improvement phase, and expansion to a total of 17 hospitals with active PCI programs is in process. In conclusion, the Blue Cross Blue Shield of Michigan Cardiovascular Consortium is an example of a regional collaborative effort to assess and improve quality of care and outcomes that overcome the barriers of traditional market and academic competition.

Background Risk-adjustment models for percutaneous coronary intervention (PCI) mortality have been recently reported, but application in bedside prediction of prognosis for individual patients remains untested. Methods and Results Between July 1, 1997 and September 30, 1999, 10 796 consecutive procedures were performed in a consortium of 8 hospitals. Predictors of in-hospital mortality were identified by use of multivariate logistic regression analysis. The final model was validated by use of the bootstrap technique. Additional validation was performed on an independent data set of 5863 consecutive procedures performed between October 1, 1999, and August 30, 2000. An additive risk-prediction score was developed by rounding coefficients of the logistic regression model to the closest half-integer, and a visual bedside tool for the prediction of individual patient prognosis was developed. In this patient population, the in-hospital mortality rate was 1.6%. Multivariate regression analysis identified acute myocardial infarction, cardiogenic shock, history of cardiac arrest, renal insufficiency, low ejection fraction, peripheral vascular disease, lesion characteristics, female sex, and advanced age as independent predictors of death. The model had excellent discrimination (area under the receiver operating characteristic curve, 0.90) and was accurate for prediction of mortality among different subgroups. Near-perfect correlation existed between calculated scores and observed mortality, with higher scores associated with higher mortality. Conclusions Accurate predictions of individual patient risk of mortality associated with PCI can be achieved with a simple bedside tool. These predictions could be used during discussions of prognosis before and after PCI.

Despite the known benefits of cardiac rehabilitation in patients with coronary artery disease, referral rates to rehabilitation programs remain low. We determined the incidence and determinants of cardiac rehabilitation referral rates for patients undergoing percutaneous coronary intervention (PCI).The incidence and predictors of referral to cardiac rehabilitation were assessed among 145,661 consecutive patients undergoing PCI and surviving to hospital discharge across 31 hospitals in the Blue Cross Blue Shield of Michigan Cardiovascular Consortium between 2003 and 2008. The 6-year cardiac rehabilitation referral rate was 60.2%. Younger age, male gender, white race, and presentation with acute or severe disease (ie, acute myocardial infarction [AMI] in the previous 24 hours and ST-elevation myocardial infarction) were associated with increased referral to rehabilitation (all P.0001). Most medical comorbidities were associated with decreased referral. Referral rates for cardiac rehabilitation were below the rates of other AMI quality-of-care indicators and more variable across hospital sites. Race-specific referral rates differed significantly in the lowest referring hospitals (P.0001) but not in the highest referring hospitals (P = .16). Women had a 0.7% relative decrease in referral as compared to men (P = .0188) in the highest referring hospitals but a 26.7% relative decrease in referral in the lowest referring hospitals (P = .02).Over one third of patients undergoing PCI are not referred for cardiac rehabilitation. Referral rates are below the rates of other AMI quality-of-care performance measures and more variable across sites. Racial and gender disparities in referral to rehabilitation exist but are concentrated at the lowest referring hospitals.