Primary Payer Status Is Associated With Mortality and Resource Utilization for Coronary Artery Bypass Grafting

Damien J. LaPar, MD, MSc; George J. Stukenborg, PhD; Richard A. Guyer, BA; Matthew L. Stone, MD; Castigliano M. Bhamidipati, DO, MSc;
Christine L. Lau, MD; Irving L. Kron, MD; Gorav Ailawadi, MD

Circulation. 2012; 126: S132-S139

Abstract
Background—Medicaid and uninsured populations are a significant focus of current healthcare reform. We hypothesized that outcomes after coronary artery bypass grafting (CABG) in the United States is dependent on primary payer status.

Methods and Results—From 2003 to 2007, 1 250 619 isolated CABG operations were evaluated using the Nationwide Inpatient Sample (NIS) database. Patients were stratified by primary payer status: Medicare, Medicaid, uninsured, and private insurance. Hierarchical multiple regression models were applied to assess the effect of primary payer status on postoperative outcomes. Unadjusted mortality for Medicare (3.3%), Medicaid (2.4%), and uninsured (1.9%) patients were higher compared with private insurance patients (1.1%, P<0.001). Unadjusted length of stay was longest for Medicaid patients (10.9±0.04 days) and shortest for private insurance patients (8.0±0.01 days, P<0.001). Medicaid patients accrued the highest unadjusted total costs ($113 380±386, P<0.001). Importantly, after controlling for patient risk factors, income, hospital features, and operative volume, Medicaid (odds ratio, 1.82; P<0.001) and uninsured (odds ratio, 1.62; P<0.001) payer status independently conferred the highest adjusted odds of in-hospital mortality. In addition, Medicaid payer status was associated with the longest adjusted length of stay and highest adjusted total costs (P<0.001).

Conclusions—Medicaid and uninsured payer status confers increased risk adjusted in-hospital mortality for patients undergoing coronary artery bypass grafting operations. Medicaid was further associated with the greatest adjusted length of stay and total costs despite risk factors. Possible explanations include delays in access to care or disparate differences in health maintenance.