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Ann Thorac Surg 1999;67:441-445
© 1999 The Society of Thoracic Surgeons

Original Articles

Variation in hospital rates of intraaortic balloon pump use in coronary artery bypass operations

William A. Ghali, MD, MPHa, Arlene S. Ash, PhDa, Ruth E. Hall, MSca, Mark A. Moskowitz, MDa

a Health Care Research Unit, Evans Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA

Accepted for publication July 6, 1998.

Address reprint requests to Dr Ghali, Faculty of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary, Alberta, Canada, T2N 4N1
e-mail: wghali{at}ucalgary.ca


   Abstract
Top
 Abstract
Introduction
 Material and methods
 Results
 Comment
 Acknowledgments
 References
 
Background. Little is known about regional patterns of intraaortic balloon pump (IABP) use in coronary artery bypass graft (CABG) operations. Our objectives were (1) to identify clinical variables associated with IABP use, and (2) to examine risk-adjusted rates of IABP use for 12 Massachusetts hospitals performing CABG operations.

Methods. We used hospital discharge data to identify 6944 CABG surgical cases. Logistic regression was used to identify clinical variables associated with IABP use, and the resulting multivariate model was then used to risk adjust hospital rates of IABP use.

Results. The IABP was used in 13.4% of the CABG surgical cases. The clinical variables independently associated with IABP use were cardiogenic shock, same admission angioplasty, prior CABG operation, cardiac arrest, congestive heart failure, recent myocardial infarction, and urgent admission status. Risk-adjusted rates of IABP use varied widely across hospitals from 7.8% to 20.8% (p < 0.0001).

Conclusions. Hospital rates of IABP use vary considerably in Massachusetts. This practice variation may be related to the persistent uncertainty regarding the precise clinical indications for the IABP in this patient population.


   Introduction
Top
 Abstract
 Introduction
Material and methods
 Results
 Comment
 Acknowledgments
 References
 
Coronary artery bypass graft (CABG) operations have been the focus of several studies evaluating outcomes of care. Many of these studies have demonstrated regional and between-hospital variability in postoperative outcomes that are not explained by adjusting for patients’ baseline clinical characteristics [1–4]. Such variation in outcomes across providers raises the possibility of differences in quality of care across regions and hospitals. These findings have prompted calls [5, 6] for more research focusing on process of care variables—rather than just outcomes—to identify factors that contribute to variation in outcomes across providers.

Intraaortic balloon pump (IABP) use in CABG operation is an important process variable that may vary across hospitals and affect patient outcomes. The IABP has established physiologic benefits in patients with compromised cardiac function [7], and underuse of this technology has the potential to produce poor patient outcomes. However, IABP use itself can lead to complications (eg, infection, hemorrhage, peripheral embolism, aortic rupture) in as many as 15% to 20% of cases [8, 9]. Overuse of the IABP therefore also has the potential to produce poor patient outcomes. Little is known about regional patterns of IABP use, and whether rates of use are consistent across providers—an important question considering the potential impact of this technology on patient outcomes.

Our objectives were (1) to identify clinical and sociodemographic variables associated with IABP use, and (2) to use a multivariate model to examine risk-adjusted rates of IABP use across Massachusetts hospitals performing CABG operations.


   Material and methods
Top
 Abstract
 Introduction
 Material and methods
Results
 Comment
 Acknowledgments
 References
 
Data source
We used a statewide database maintained by the Massachusetts Health Data Consortium to identify all CABG surgical cases in Massachusetts in the fiscal year 1994 (October 1, 1993, through September 30, 1994). The database contains one record for each hospital discharge in Massachusetts [10], and each inpatient record contains up to 15 International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnoses and 15 procedure codes [11]. The records also contain information on patient age, sex, race, payer (eg, Medicaid, Medicare, health maintenance organization [HMO]), length of stay, admission type (elective, urgent, emergent), and diagnosis related group (DRG) [12].

Derivation of study cohort
We identified CABG surgical cases by screening all hospital discharge abstracts for ICD-9-CM procedure codes representing CABG operations (36.10 through 36.19). This case selection criterion captured all patients who had a simple CABG procedure, as well as those who had a combined CABG plus valve procedure. Cases outside of DRGs 104 through 108 and 483 were excluded (n = 42) because the clinically dissimilar cases assigned to other DRGs usually involved hospitalizations with other noncardiac surgical procedures. Cases in DRG 483 (denoting tracheostomy) were reclassified to the DRG category (104 through 108) to which they would have been assigned had tracheostomy not occurred. All cases from a single Veterans Affairs hospital were also excluded because of important data inconsistencies. This case selection process yielded a study cohort of 6,944 CABG surgical cases performed in 12 hospitals. The volume of cases per hospital ranged from a low of 330 to a high of 946.

Definitions of study variables
The process variable of interest was IABP use, defined by the presence of ICD-9-CM procedure code 37.61. Because we could not distinguish between preoperative and postoperative IABP use in our database, the focus of this study is on overall hospital rates of IABP use. A number of other variables were assessed as potential correlates of IABP use. These were grouped into three categories: sociodemographic, comorbidity, and disease-specific variables.

The sociodemographic variables were age, sex, race (white versus other), and socioeconomic status (defined as "low" for cases in which care was free or the payer was Medicaid). Fifteen comorbidity variables (eg, diabetes, peripheral vascular disease, cerebrovascular disease, chronic lung disease) were defined using an ICD-9-CM coding algorithm derived by Deyo and colleagues [13]. We then used these comorbidity variables to assign a comorbidity score to each CABG surgical case. The score consisted of the 17-variable Charlson index [14], altered by removing two disease-specific variables (congestive heart failure and myocardial infarction), which were evaluated separately.

The disease-specific variables and corresponding ICD-9-CM code definitions were congestive heart failure (ICD-9-CM code 428), recent myocardial infarction (410.0x through 410.9x), prior CABG operation (v458.1), angioplasty on the same admission (procedure codes 36.01, 36.03, or 36.09), acquired ventricular septal defect (429.71), ruptured chordae tendinae (429.5 or 429.6), cardiogenic shock (785.51), and cardiac arrest (427.4, 427.5, 427.41, or 427.42). Combined CABG plus valve procedures were identified by patient assignments to DRGs 104 and 105. Urgent admission status (ie, urgent or emergent admission as opposed to elective) was determined from "admission type."

Analysis
We used {chi}2 and Fisher’s exact tests, when appropriate, to test potential associations between IABP use and each of the variables defined above. From the results of these bivariate analyses, we selected variables that appeared in at least 10 cases and showed even weak (p <= 0.15) associations with IABP use for presentation to a logistic regression model. In our multivariate analysis, we retained only variables significantly associated with IABP use (p <= 0.05).

We assessed the resulting multivariate model’s discrimination for predicting IABP use with the c statistic, which equals the area under the receiver operating characteristic curve. Model calibration was assessed using the Hosmer-Lemeshow test of goodness-of-fit across categories of predicted risk.

We then used the model to calculate risk-adjusted rates of IABP use for each of the 12 Massachusetts hospitals performing CABG operations as follows. First, we calculated the hospitals’ observed and expected rates of IABP use, and calculated each hospital’s ratio of observed-to-expected use. We then multiplied this ratio by the statewide rate of use to yield a risk-adjusted rate.

Because it is not clear whether higher or lower rates of IABP use are better (unlike mortality where lower is clearly better), we did not seek to identify outlier hospitals. Rather, we present the full range of IABP rates along with the extremal quotient (ratio of highest rate divided by lowest rate) and the coefficient of variation (ratio of the standard deviation of hospital rates divided by the average hospital rate) to quantify the degree of variation. We used a {chi}2 test with 11 degrees of freedom to assess the statistical significance of the differences in risk-adjusted IABP rates across hospitals. This was achieved by evaluating the increment in our logistic model’s -2 log likelihood {chi}2 statistic when dummy variables for the hospital were added to the model.


   Results
Top
 Abstract
 Introduction
 Material and methods
 Results
Comment
 Acknowledgments
 References
 
Table 1 presents the baseline characteristics of the 6,944 CABG surgical cases studied. Mean age was 66.0 years, and 62.8% were admitted urgently. The overall statewide rate of IABP use was 13.4%. The statewide in-hospital mortality rate was 3.9%.


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  		Table 1. Characteristics of the 1994 Coronary Artery Bypass Graft Surgical Cohort (n = 6,944).

 
Correlates of intraaortic balloon pump use
Table 2 shows bivariate associations between individual clinical variables and IABP use. Among the sociodemographic variables assessed, only age and sex were significantly associated with IABP use. A number of disease-specific variables were also significantly associated with IABP use: urgent admission status, recent myocardial infarction, congestive heart failure, prior CABG operation, same admission angioplasty, cardiac arrest, cardiogenic shock, ruptured chordae tendinae, and acquired ventricular defect. Intraaortic balloon pump use varied significantly (p < 0.001) according to patients’ modified Charlson comorbidity index scores, but there was no trend in IABP use as comorbidity scores increased. Patients treated with the IABP were more likely to die than patients who did not receive this treatment (16.4% in-hospital mortality for IABP cases versus 1.9% for cases with no IABP; p < 0.001).


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  		Table 2. Bivariate Associations of Intraaortic Balloon Pump Use in Coronary Artery Bypass Graft Operations

 
On multivariate analysis (Table 3), only seven variables were retained as significant (p <= 0.05) correlates of IABP use. These variables were all from our predefined category of "disease-specific variables." The Charlson comorbidity index score, modeled either as a continuous or a categorical variable, did not enter this model, nor did a number of other significant variables from the bivariate analysis (Table 2 versus Table 3). The seven clinical variables independently associated with IABP use were cardiogenic shock (odds ratio [OR] = 19.5), same admission angioplasty (OR = 4.4), prior CABG operation (OR = 2.6), cardiac arrest (OR = 2.4), congestive heart failure (OR = 2.2), recent myocardial infarction (OR = 1.8), and urgent admission status (OR = 1.7). The resulting logistic regression model predicts well, with good discrimination (c = 0.74) and calibration (Hosmer-Lemeshow test, p = 0.08). On the Hosmer-Lemeshow test, the rates of actual IABP use in the highest and lowest predicted risk groupings were 37.9% and 4.0%, respectively (an almost tenfold risk difference).


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  		Table 3. Multivariate Model Predicting Intraaortic Balloon Pump Use in Coronary Artery Bypass Graft Operationsa

 
Hospital rates of intraaortic balloon pump use
Figure 1 presents unadjusted and adjusted rates of IABP use in the 12 Massachusetts hospitals studied. Hospital rates of IABP use varied widely from a low of 7.0% to a high of 24.9% in the unadjusted analysis, and from 7.8% to 20.8%, adjusted. The difference in adjusted rates of IABP use across hospitals was statistically significant ({chi}2 = 144.2 with 11 degrees of freedom; p < 0.0001). The extremal quotient for the difference across hospitals is 2.7, and the coefficient of variation is considerable at 0.354, or 35.4%.



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  		Fig 1. Unadjusted and adjusted rates of intraaortic balloon pump (IABP) use in 12 Massachusetts hospitals performing coronary artery bypass graft operations.

 
Risk adjustment of hospital rates of IABP use was in fact necessary, because model-predicted rates of IABP use varied significantly (p < 0.001) across hospitals, ranging from a low of 11.5% to a high of 15.9%. Reflected in these predicted rates is variation across hospitals in the prevalence of individual predictor variables. For example, the prevalence of cardiogenic shock varied from 0.3% in one hospital to 5.5% in another (p < 0.001 for the difference in prevalence across hosptials). Likewise, the prevalence of congestive heart failure varied across hospitals from 13.9% to 26.0% (p < 0.001). Similar interhospital variation was seen for each of the risk variables included in our risk adjustment model (p < 0.004 for all variables listed in Table 3).


   Comment
Top
 Abstract
 Introduction
 Material and methods
 Results
 Comment
Acknowledgments
 References
 
We have identified a number of clinical variables that correlate with IABP use in CABG operations, and despite adjusting for these variables have found wide variation in hospital rates of IABP use. This is an important finding because IABP use is a process variable with the potential to have both a positive and negative impact on patients’ clinical outcomes after CABG operations.

The multivariate correlates of IABP use (Table 3) all fall within our predefined category of disease-specific variables. This suggests that it is clinical parameters relating to cardiac disease that have the greatest influence on clinicians’ decisions to use the IABP. Interestingly, burden of comorbidity (measured by the Charlson comorbidity index [13, 14]) was not independently associated with IABP use.

Reassuringly, sociodemographic variables were not independently associated with IABP use. This contrasts with published findings of lower use of cardiac procedures in women (versus men) [15, 16], blacks (versus whites) [17], and Medicaid (versus insured) patients [18]. Our findings thus indicate that once a patient has been selected for CABG operation, the IABP appears to be used equally regardless of patients’ age, sex, race, and socioeconomic status.

Most published articles reviewing clinical indications for IABP use distinguish between preoperative and intraoperative or postoperative indications [19–22]. There is little controversy about the clinical indications for intraoperative and postoperative IABP use. These are (1) inability to wean patients from cardiopulmonary bypass within 30 minutes of completing the operation, (2) poor hemodynamic status (systolic blood pressure <80 mm Hg, left ventricular end-diastolic pressure >20 mm Hg) despite inotropic therapy and vasodilators, (3) persistent requirements for inotropic therapy, and (4) arrhythmias attributable to cardiac ischemia.

In contrast, there is considerable disagreement regarding preoperative indications. Some authors [19, 20] advocate use of the IABP for the following indications: (1) acute myocardial infarction with new mechanical defect (ventricular septal defect or acute mitral regurgitation), (2) cardiogenic shock, (3) left main coronary artery stenosis, (4) impaired left ventricular function, and (5) preoperative unstable angina. Others [21, 22] have questioned the need for IABP use in patients with the latter three indications. In arguing against widespread preoperative IABP use, they report that many patients with left main coronary artery stenosis, poor ventricular function, and unstable angina do well without the IABP. The question of patient selection for preoperative IABP use remains unresolved. A recent retrospective analysis of patients undergoing CABG operation with ejection fraction of <25% suggests benefit from IABP use, but the study was not randomized, and controls differed considerably from IABP-treated patients [23]. A randomized controlled trial is needed to definitively assess the efficacy of preoperative IABP use for selected patients undergoing CABG operation.

This controversy about indications for IABP use may be responsible for the apparent practice variation in Massachusetts. Indeed, others [24] have found the largest surgical rate variations when procedural indications are unclear (ie, clear indications result in less variation). Wennberg [25] has stated that "variations occur because the profession lacks consensus on the correct way to practice medicine," and that clinical research should target those interventions for which there is greatest variation.

Our data do not clarify which rate of IABP use is right. Although IABP-treated patients were more likely to die and to experience postoperative complications (data not shown), this probably reflects the fact that patients who received the IABP were initially sicker. We also cannot tell whether the differences in rates of IABP use arise from preoperative or postoperative practice variation. This latter question needs to be examined in databases that distinguish between preoperative and intraoperative or postoperative IABP insertion.

Another important limitation of our study is our use of ICD-9-CM administrative data. Concerns with such data include the possibilities of undercoding of certain data elements and variable coding practices across hospitals. Furthermore, administrative data lack important clinical variables, which may explain at least some of the observed practice variation. For example, a greater proportion of the variation in hospital rates of IABP use might have been explained had we been able to adjust hospital IABP rates for clinical variables such as left ventricular ejection fraction or end-diastolic pressures. Reassuringly, despite these concerns, we were nonetheless able to develop and apply a clinically plausible multivariate model (Table 3) that is strongly predictive. We encourage investigators with access to more detailed regional clinical databases to see whether our findings can be replicated after adjustment for additional clinical variables such as ejection fraction.

Despite these limitations, this study identifies clinical correlates of IABP use and finds significant variation in hospital rates of IABP use. Further work is now needed to clarify the true extent of interhospital variation after adjustment for more detailed clinical variables, as well as the specific timing of practice variation (preoperative versus intraoperative or postoperative). More importantly, randomized controlled trials are needed to evaluate the true efficacy of elective IABP use in selected CABG surgical patients. Until such studies are done, clinicians will continue to struggle with the difficult question of which rate is right.


   Acknowledgments
Top
 Abstract
 Introduction
 Material and methods
 Results
 Comment
 Acknowledgments
References
 
We acknowledge the support of Hude Quan, MD, PhD, (University of Calgary) in data management and analysis. This project was supported by the Massachusetts Health Data Consortium, and by a grant from the Walnut Medical Charitable Trust. Doctor Ghali is supported by a Population Health Investigator grant from the Alberta Heritage Foundation for Medical Research.


   References
Top
 Abstract
 Introduction
 Material and methods
 Results
 Comment
 Acknowledgments
 References
 

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