Predictors of Cardiac Rehabilitation Referral in Coronary Artery Disease Patients: Results From the AHA’s Get With the Guidelines Program Todd M. Brown, MD; 1 Adrian F. Hernandez, MD, MHS; 2 Vera Bittner, MD, MSPH; 1 Christopher P. Cannon, MD; 3 Gray Ellrodt, MD; 4 Li Liang, PhD; 2 Eric D. Peterson, MD, MPH; 2 Ileana L. Piña, MD; 5 Monika M. Safford, MD; 1 Gregg C. Fonarow, MD 6 1 University of Alabama at Birmingham, Birmingham, AL; 2 Duke Clinical Research Institute, Durham, NC; 3 Brigham and Women’s Hospital, Boston, MA; 4 Berkshire Medical Center, Pittsfield, MA; 5 Case Western Reserve University, Cleveland, OH; 6 UCLA Medical Center, Los Angeles, CA Results DISCLOSURE INFORMATION The following relationships exist related to this presentation: The GWTG-CAD program is supported by the American Heart Association which received funding from the Merck-Schering Plough Partnership Table 1. Baseline Demographic and Clinical Characteristics in the Overall Population and in Those Referred and Not Referred to Cardiac Rehabilitation Overall Population (n=185,794) Not Referred to CR (n=115,231) Referred to CR (n=70,563) P-Value Age (years) Gender (%) Male Race (%) White African American Hispanic Body Mass Index (kg/m 2 ) Ejection Fraction (%) Diabetes (%) Hypertension (%) Dyslipidemia (%) Heart Failure (%) Admitting Diagnosis (%) Heart Failure with CAD STEMI Non-STEMI Unspecified MI Unstable Angina CAD 65.6 ± ± ± ± ± ± ± ± ± <0.001 All values listed as mean ± standard deviation or %. Wilcoxon two-sample test performed for continuous variables. Chi-square test performed for categorical variables. CAD=coronary artery disease, CR=cardiac rehabilitation, MI=myocardial infarction, STEMI=ST segment elevation myocardial infarction Table 3. Independent Predictors of Referral to Cardiac Rehabilitation in the Overall Population Variable Adjusted Odds Ratio (95% CI) Variable Adjusted Odds Ratio (95% CI) Age (per 10 years) Gender Male Female Race White Hispanic African American Admitting Diagnosis Heart Failure with CAD STEMI Non-STEMI CAD Unspecified MI Unstable Angina 0.93 ( ) Referent 0.89 ( ) Referent 0.93 ( ) 0.91 ( ) Referent 3.66 ( ) 3.55 ( ) 3.47 ( ) 3.26 ( ) 2.41 ( ) ST elevation/LBBB BMI (per 5 units) DC SBP (per 10 units) Teaching Hospital Co-morbidities Dyslipidemia Current Smoker COPD PAD Prior MI CRI Atrial Fibrillation Heart Failure Stroke or TIA Chronic Dialysis 1.26 ( ) 1.02 ( ) 0.98 ( ) 0.26 ( ) 1.20 ( ) 1.08 ( ) 0.93 ( ) 0.92 ( ) 0.91 ( ) 0.91 ( ) 0.90 ( ) 0.89 ( ) 0.87 ( ) 0.67 ( ) The variables listed above are the statistically significant factors predicting CR referral in the final, reduced multivariable model. BMI=body mass index, CAD=coronary artery disease, CI=confidence interval, COPD=chronic obstructive pulmonary disease, CRI=chronic renal insufficiency, DC=Discharge, LBBB=left bundle branch block, MI=myocardial infarction, PAD=peripheral arterial disease, SBP=systolic blood pressure, STEMI=ST segment elevation myocardial infarction, TIA=transient ischemic attack A significant number of Coronary Artery Disease (CAD) patients who qualify for Cardiac Rehabilitation (CR) are not referred despite proven reductions in mortality and national guideline recommendations. The patient specific factors associated with referral to CR are not well understood. Background To determine the patient specific factors which independently predict referral to CR in the AHA’s Get with the Guidelines (GWTG) CAD Program. Objective Study population: 185,794 patients in the AHA’s GWTG Program admitted for CAD between January 2000 and September 2007 who were discharged home alive. GWTG participating hospitals submit in-hospital clinical information using an internet-based tool. Data are abstracted by trained personnel. We calculated the proportion of patients referred to CR in the overall population, in those admitted with myocardial infarction, and in those who had a myocardial infarction, percutaneous coronary intervention, or coronary artery bypass graft surgery. To determine which factors independently predicted CR referral in the overall population, we performed multivariable logistic regression using the generalized estimating equations method to adjust for in-hospital clustering. Outcome variable: referral to CR  We considered missing values, failure to document whether referral was made, and documentation that CR was “not applicable” to be non-referred for this analysis. Predictors of CR referral:  The initial model included age, gender, race, body mass index, discharge systolic blood pressure, admitting diagnosis, ST segment elevation/LBBB on initial EKG, medical co-morbidities, insurance status, and hospital characteristics.  Non-statistically significant predictors (p>0.1) were removed to create the final, reduced model. Methods Conclusions Overall, only 38% of patients admitted to GWTG participating hospitals with a CAD-related diagnosis, 43% admitted with a myocardial infarction, and 46% with a myocardial infarction, percutaneous coronary intervention, or coronary artery bypass graft surgery were referred to CR. In the overall population, both patient and hospital factors were independently associated with lower odds of CR referral:  Patient: Demographics (older age, women, minorities) Medical conditions (poorly controlled blood pressure, a heart failure admitting diagnosis, most co-morbid diseases)  Hospital type (teaching hospitals) Table 2. Number and Percent of Patients Referred to Cardiac Rehabilitation Not Referred to CRReferred to CR Overall Population (n=185,794) Patients with MI (n=110,905) Patients with MI, PCI, or CABG (n=144,281) 115,231 (62%) 62,849 (57%) 78,275 (54%) 70,563 (38%) 48,046 (43%) 66,006 (46%) CABG=coronary artery bypass graft surgery, CR=cardiac rehabilitation, MI=myocardial infarction, PCI=percutaneous coronary intervention. Participation in the GWTG program is voluntary. The overall proportion of eligible patients who are referred to CR and the predictors of CR referral may not be the same in non-participating hospitals. We considered individuals with missing data for CR referral, lack of documentation of CR referral, and documentation that CR was “not applicable” as not being referred for the purpose of this analysis. This may have resulted in an underestimation of the proportion of eligible patients referred to CR. The GWTG program only collects in-hospital data. Therefore, we are unable to capture patients who are referred to CR following discharge from the hospital or assess what proportion of referred patients actually attend CR. Data on patient socioeconomic status was not available. Limitations