D M Shahian1, G J Heatley, G A Westcott. 1. Department of Thoracic and Cardiovascular Surgery, Lahey Clinic Medical Center, Burlington, MA 01805, USA. David.M.Shahian@Lahey.ORG
Abstract
OBJECTIVE: This study investigates the relationship between the cost of coronary artery bypass graft surgery and both hospital size and case volume. METHODS: Retrospective administrative and cost data were obtained for all 12,774 patients who underwent isolated coronary bypass surgery at 12 Massachusetts hospitals during 1995 and 1996. Hospitals were stratified by number of operating beds into 3 groups (group I, <250 beds; group II, 250-450 beds; group III, >450 beds). Total (diagnosis-related groups 106 + 107) annual coronary bypass cases per hospital varied from 271 to 913 (mean 532). Univariate and multivariable analyses were used to study the relationship between the direct and total cost and a number of patient (age, sex, acuity class, payer) and hospital (bed capacity, annual case volume per diagnosis-related group, cardiothoracic residency) predictor variables. For each hospital, we also studied the relationship between changes in coronary bypass case volume and the corresponding changes in average cost from 1995 to 1996. RESULTS: Scatterplots revealed a broad range of mean direct cost of coronary bypass surgery among hospitals with comparable case volumes. When annual cases were analyzed as continuous variables, there was no linear relationship of case volume with direct or total cost of coronary bypass (r = -0.05 to +0.08) for any diagnosis-related group or year. When hospital bed capacity and case volume were grouped into strata and studied by analysis of variance, there was no evidence of an inverse relationship between these variables and cost. In multivariable analysis, patient acuity class and diagnosis-related group were the most important predictors of cost. Beds and case volume met inclusion criteria for most models but added little to the "explanation" of variability R(2), often less than 1%. Finally, substantial interhospital differences were noted in the magnitude and direction (direct vs inverse) of their 1995 to 1996 change in volume versus change in cost. CONCLUSIONS: Within the range of hospital size and case volume represented in this study, there is no evidence that either variable is related to the cost of performing coronary bypass surgery. Massachusetts hospitals appear to function on different segments of different average cost curves. It is not possible to predict the relative cost of coronary bypass grafting at a given hospital based primarily on volume.
OBJECTIVE: This study investigates the relationship between the cost of coronary artery bypass graft surgery and both hospital size and case volume. METHODS: Retrospective administrative and cost data were obtained for all 12,774 patients who underwent isolated coronary bypass surgery at 12 Massachusetts hospitals during 1995 and 1996. Hospitals were stratified by number of operating beds into 3 groups (group I, <250 beds; group II, 250-450 beds; group III, >450 beds). Total (diagnosis-related groups 106 + 107) annual coronary bypass cases per hospital varied from 271 to 913 (mean 532). Univariate and multivariable analyses were used to study the relationship between the direct and total cost and a number of patient (age, sex, acuity class, payer) and hospital (bed capacity, annual case volume per diagnosis-related group, cardiothoracic residency) predictor variables. For each hospital, we also studied the relationship between changes in coronary bypass case volume and the corresponding changes in average cost from 1995 to 1996. RESULTS: Scatterplots revealed a broad range of mean direct cost of coronary bypass surgery among hospitals with comparable case volumes. When annual cases were analyzed as continuous variables, there was no linear relationship of case volume with direct or total cost of coronary bypass (r = -0.05 to +0.08) for any diagnosis-related group or year. When hospital bed capacity and case volume were grouped into strata and studied by analysis of variance, there was no evidence of an inverse relationship between these variables and cost. In multivariable analysis, patient acuity class and diagnosis-related group were the most important predictors of cost. Beds and case volume met inclusion criteria for most models but added little to the "explanation" of variability R(2), often less than 1%. Finally, substantial interhospital differences were noted in the magnitude and direction (direct vs inverse) of their 1995 to 1996 change in volume versus change in cost. CONCLUSIONS: Within the range of hospital size and case volume represented in this study, there is no evidence that either variable is related to the cost of performing coronary bypass surgery. Massachusetts hospitals appear to function on different segments of different average cost curves. It is not possible to predict the relative cost of coronary bypass grafting at a given hospital based primarily on volume.