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Ann Thorac Surg 2000;70:702-710
© 2000 The Society of Thoracic Surgeons

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Original articles: cardiovascular

Identification of risk factors for increased cost, charges, and length of stay for cardiac patients

^a Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, Colorado, USA
^b Department of Medicine, University of Colorado Health Sciences Center, Denver, Colorado, USA
^c Department of Surgery, University of Colorado Health Sciences Center, Denver, USA
^d Department of Mathematics, United States Air Force Academy, Colorado Springs, Colorado, USA
^e Department of Veterans Affairs Medical Center, Denver, Colorado, USA

Address reprint requests to Dr Shroyer, Division of Cardiac Research, Denver VA Medical Center, 1055 Clermont St (151R), Denver, CO 80220
e-mail: laurie.shroyer{at}med.va.gov

Background. In this study we explored different risk model options to provide clinicians with predictions for resource utilization. The hypotheses were that predictors of mortality are not predictive of resource consumption, and that there is a correlation between cost estimates derived using a cost-to-charge ratio or a product-line costing approach.

Methods. From March 1992 to June 1995, 2,481 University of Colorado Hospital patients admitted for ischemic heart disease were classified by diagnosis-related group code as having undergone or experienced coronary bypass procedures (CBP), percutaneous cardiovascular procedures (PCVP), acute myocardial infarction (AMI), and other cardiac-related discharges (Other). For each diagnosis-related group, Cox proportional hazards models were developed to determine predictors of cost, charges, and length of stay.

Results. The diagnosis groups differed in the clinical factors that predicted resource use. As the two costing methods were highly correlated, either approach may be used to assess relative resource consumption provided costs are reconciled to audited financial statements.

Conclusions. To develop valid prediction models for costs of care, the clinical risk factors that are traditionally used to predict risk-adjusted mortality may need to be expanded.

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