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Ann Thorac Surg 2005;79:1961-1969
© 2005 The Society of Thoracic Surgeons
a Division of Cardiovascular Surgery, St. Vincent Mercy Medical Center, Toledo
b Division of Cardiovascular Surgery, St. Luke’s Hospital, Maumee USA
c Department of Surgery, Medical College of Ohio, Toledo, Ohio, USA
d Department of Anesthesiology, Medical College of Ohio, Toledo, Ohio, USA
e Department of Medicine, Medical College of Ohio, Toledo, Ohio, USA
Accepted for publication December 10, 2004.
* Address reprint requests to Dr Habib, Cardiopulmonary Research, St. Vincent Mercy Medical Center, 2213 Cherry St, ACC Bldg, Suite 309, Toledo, OH43608. (E-mail: robert_habib{at}mhsnr.org).
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Abstract |
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 Top Abstract IntroductionPatients and MethodsResultsCommentAcknowledgmentsReferences |
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METHODS: We retrospectively compared operative mortality and 3-year survival in coronary artery bypass grafting patients (2001 to 2003) at a low-volume hospital (n = 504; 160 per year [median]) versus a high-volume hospital (n = 1,410; 487 per year) served by the same high-volume surgeon team. Covariate risk adjustment was done via multivariate and propensity modeling.
RESULTS: The two hospital cohorts exhibited multiple demographic and risk factor differences. Unadjusted low-volume hospital vs high-volume hospital operative mortality was similar overall (2.38% vs 2.98%; p = 0.59) with nearly identical Society of Thoracic Surgeons observed-to-expected ratios (0.83 vs 0.82), irrespective of preoperative risk category. Hospital volume did not predict operative mortality (odds ratio, 95% confidence interval = 0.82; p = 0.602). At follow-up, a total of 28 low-volume hospital deaths (5.6%) and 135 high-volume hospital deaths (9.6%) occurred at similar surgery-to-death intervals (p = 0.7). Unadjusted 0 to 3-year survival was significantly worse for high-volume hospitals (risk ratio = 1.59; 1.06 to 2.39; p = 0.026). Yet procedure volume was not independently associated with worse midterm survival after covariate (risk ratio = 1.28; 0.84 to 1.96; p = 0.247) or propensity score (risk ratio = 1.11; 0.72 to 1.71; p = 0.648) adjustment.
CONCLUSIONS: Hospital and surgeon volume effects on coronary artery bypass grafting outcomes are interdependent, and therefore hospital coronary artery bypass grafting volume per se is not a reliable marker of quality. Instead, outcome quality markers should rely on thorough risk-adjustment based on detailed clinical databases, possibly including annual and cumulative surgeon volume.
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Introduction |
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TopAbstractIntroductionPatients and MethodsResultsCommentAcknowledgmentsReferences |
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Recently, related studies based on two large clinical databases have reached differing conclusions. Peterson and colleagues [1] analyzed results from 267,089 isolated CABG procedures (2001 to 2002) from 439 United States hospitals participating in The Society of Thoracic Surgeons (STS). They found that hospital volume is only modestly associated with CABG outcome and may not be an adequate marker of surgical quality [1]. Hannan and colleagues [2] and Wu and colleagues [3], reporting on the 1997 to 1999 New York State isolated CABG experience (N = 57,150), provided compelling data that high-volume hospitals continue to have lower in-hospital mortality [1], and the benefits are similar in low-risk versus moderate-to-high-risk CABG [3]. Importantly, both groups concur that hospital-volume outcome effects are confounded by a significant independent surgeon-volume effect [1–3].
To date, all studies exploring CABG volume effects on outcome have been limited to the consideration of early (in-hospital or 30-day) or operative mortality. Although obviously pertinent, it is not known whether the reported volume-outcome effects persist beyond the early postoperative period. The aims of this investigation were (1) to better define whether procedure volume effects are surgeon or institutional in origin, and (2) to explore whether procedure volume has longer term implications on outcome that extend beyond the early postoperative period. We compared operative (30-day) and midterm (3-year) mortality for two independent institutions served by the same team of high-volume surgeons: (1) a high-volume hospital (HVH) with a cardiac surgery program since 1975, and (2) a newer, smaller low-volume hospital (LVH) program started in 2001. We reasoned that this paradigm would allow us to objectively assess the impact of low versus high institutional CABG volume on outcome free of surgeon-volume confounding.
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Patients and Methods |
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TopAbstractIntroductionPatients and MethodsResultsCommentAcknowledgmentsReferences |
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All consecutive patients undergoing isolated CABG at LVH and HVH were analyzed. Patients were excluded if they had concomitant valve, other cardiac, or carotid surgery. The same perfusion team provided cardiopulmonary bypass services at LVH and HVH. With rare exception, normothermic bypass combined with cold blood cardioplegia was utilized for CABG at both hospitals. Off-pump CABG was similarly used at the two institutions (HVH versus LVH = 5.3% versus 4.2%; p = 0.34) with similar selective criteria. All patients had a valid United States social security number. The institutional review boards at both institutions approved research based on ongoing clinical cardiac surgery databases. The requirement for informed consent was waived.
Clinical Data and End Points
Clinical data on patients undergoing revascularization have been systematically abstracted and recorded in identical cardiac surgery databases at both hospitals. Both institutions participate in The STS national cardiac surgery database. The primary end points were all-cause operative mortality (30-day or in-hospital, whichever is longer) and 0 to 3-year mortality. The Social Security Death Index (conducted in August 2004) was used to determine timing of death used for mid-term survival analysis. Allowing for a 3-month lag, this corresponds to a follow-up between 5 and 41 months.
Statistical Analyses
Continuous data were expressed as mean ± standard deviation. Baseline variables were compared by using the Wilcoxon rank-sum test, t test, or the chi-square test as appropriate. Actual operative mortality (OM), risk-adjusted and observed-to-expected ratio of operative mortality data are reported as per the latest STS CABG risk model [19]. In addition, for LVH versus HVH, we used two tests to compare (1) overall OM and (2) OM for three STS risk-based sub-cohorts: (1) low risk (< 2%), (2) moderate risk (2% to 5%), and (3) high risk (> 5%). Effects of explanatory variables on OM were derived by logistic regression.
Low-volume hospital versus HVH midterm Kaplan-Meier [20] survival for the entire cohort and for the low, moderate, and high-risk cohorts were compared with (Breslow test) and without (log rank test) weighting. For the Breslow test, each test is weighted by the number of patients at risk in each of the comparison groups at any given time. Next, multivariable Cox proportional-hazards regression [21, 22] was done to assess the effects of explanatory variables on long-term mortality and their associated risk ratios. Regression model selection was done with backward elimination (Wald statistic, confirmed using forward and stepwise selection).
Potential confounding due to the unbalanced LVH versus HVH patient variables on outcome comparisons cannot be discounted, even after multivariate risk adjustment [23, 24]. To minimize these effects, we utilized LVH propensity score analysis derived via a nonparsimonious logistic regression model (LVH = 1, HVH = 0) [23, 24]. All the variables listed in Table 1 and their significant interactions were included in this model. The score was then incorporated into subsequent multivariate model analyses as a covariate. In case of OM, the population was divided to LVH propensity score quintiles and compared. A p < 0.05 cutoff was used to indicate significance (SPSS version 10.0, SPSS Inc, Chicago, IL).
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Results |
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TopAbstractIntroductionPatients and MethodsResultsCommentAcknowledgmentsReferences |
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Operative Mortality
Unadjusted OM was similar for the two hospitals (HVH vs LVH, 2.98% vs 2.38%; p = 0.59) (Table 2). The corresponding observed-to-expected ratio of mortality data of The STS risk model were 0.83 and 0.82, respectively. Separate comparisons of the low, moderate, and high-risk subgroups also indicated similar OM results for HVH and LVH irrespective of risk category. Hospital volume was not among the OM predictors by logistic regression, which included increasing age, longer cardiopulmonary bypass, insulin dependence, cerebrovascular disease, chronic obstructive pulmonary disease, emergencies, redo surgery, all-vein grafting, and coronary endarterectomy (see Table 3). Forcing hospital volume (HVH = 0, LVH = 1) as a covariate did not alter model prediction (OR = 0.82; range, 0.40 to 1.71; p = 0.60) as illustrated by the receiver operator characteristic curve comparison (Fig 1). Individual surgeons and Medicaid and uninsured status did not predict OM.
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Unadjusted LVH versus HVH Kaplan-Meier survival for as much as approximately 1,100 days post-CABG are shown in Figure 2 (top); this indicated a significantly worse HVH survival (risk ratio, 95% confidence interval = 1.59; range, 1.06 to 2.39; p = 0.026 log rank and 0.020 Breslow). The LVH survival was superior at 1 year (95.6% vs 93.1%) and 3 years (91.5% vs 87.8%). The low STS risk LVH cohort showed a significantly better survival (Fig 2, bottom). Covariate adjustment via Cox regression analysis showed that hospital volume was not a significant predictor of 0 to 3-year mortality (Fig 3, top) (risk ratio = 1.28; range, 0.84 to 1.96; p = 0.247). Individual surgeons and Medicaid and uninsured status did not predict survival. The multivariate predictors of increased midterm mortality are detailed in Table 4, and these included increased age, vein only grafting, preoperative renal failure, longer cardiopulmonary bypass, preoperative myocardial infarction, chronic obstructive pulmonary disease, obesity, small patient size, diabetes, cerebrovascular disease, and congestive heart failure.
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Comment |
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TopAbstractIntroductionPatients and MethodsResultsCommentAcknowledgmentsReferences |
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The role of hospital-procedure and surgeon-procedure volumes on CABG outcomes have been investigated by many [1–18]. With few exceptions [12, 13], studies had indicated that higher CABG surgery hospital and surgeons volumes are associated with lower mortality rates [1–10]. Consequently it was reasoned that a significant number of CABG deaths may be avoided if a policy of "regionalization" is adopted to avoid low-volume hospitals [14–18]. However, implementation of such procedure-volume guidelines may be unwarranted from a number of perspectives: (1) they equate low-volume hospitals with good outcomes to those of poorer quality of care; (2) they assume similarly higher quality of CABG care in all high-volume hospitals relative to all smaller programs; and (3) they do not, as has been proposed, appropriately account for potentially substantial surgeon-volume confounding effects [1–3]. Another concern is that a regionalization policy may cause significant disruption in the current delivery of care with thousands of patients being referred away from low-volume to high-volume hospitals. To ease this, some have recommended that such referrals be limited to high-risk patients [14], yet the appropriateness of this approach was recently challenged [2, 3].
Many prior studies exploring CABG volume-outcome effects relied on unadjusted (or incompletely adjusted) early or operative mortality that are easily accessible from administrative databases. Also, many of these analyses predicted worse CABG outcomes in small compared with large hospital programs [1–10]. It is noteworthy that the LVH versus HVH differences we found in unadjusted 0 to 3-year mortality (including a slightly lower [not significant] unadjusted OM in LVH patients) are contrary to these predictions. From the 1994 to 1999 national Medicare claims data, Birkmeyer and colleagues [5] showed a 1.3% absolute drop in CABG unadjusted OM from very low-volume (< 230) to very high-volume hospitals (
850). Operative mortality of Medicare patients at low-volume hospitals (3.95%) and high-volume hospitals (4.08%) were similar. Hannan and colleagues [2] analyzed the clinical data from 30 New York State centers between 1997 and 1999, and they noted significantly decreased OM in high-volume compared with low-volume hospitals even after risk adjustment. Their statewide study is among the most complete analyses based on clinical data, yet only a small minority (< 3%) had their CABG done at low-volume centers due to New York State restrictions. A subsequent analysis of their data showed that these volume effects were true for both low-risk as well as moderate-to-high-risk patients [3]. This was also true for our analysis (Table 2, Fig 1).
In contrast, Peterson and colleagues [1] analyzed the 2000 to 2001 isolated CABG outcomes of all participating hospitals in The STS national database. Although they reported a modest yet persistently greater operative mortality in low-volume programs, they concluded that hospital volume is not an adequate marker of quality of CABG care, and that other more clinically rigorous quality assessment instruments should be preferred [25]. They also indicated that the hospital-volume outcome effect was particularly nonsignificant in young (< 65 years) and low operative risk CABG patients. Our results do not conform to this STS analysis, despite the fact that both our institutions’ data are included in their analysis.
Evidence that surgeon volume is a major confounding factor of hospital volume, CABG outcome effects were also presented in the New York State [2, 3] and The STS national [1] studies. The similar LVH and HVH outcomes we report for the same high-volume surgeon team implied that worse CABG outcomes in low-volume hospitals reported by others [1–10] may reflect low surgeon volume rather than hospital volume effects. Consequently, low-volume programs served by low-volume versus high-volume surgeons may be associated with significantly different outcomes.
As described in the Methods section, the same surgeon team also performed cardiac surgery at a third low-CABG volume institution (355 CABG for 2001 to 2003). This data was not included in the primary analysis to avoid potential confounding factors. First, 90% of all CABG procedures were performed by 2 of 5 surgeons (Table 1). Second, at this hospital, an independent perfusion team was utilized at this site, and nearly 35% of the isolated CABG cases were done off-pump compared with about 5% at LVH and HVH. Third, nursing, anesthesia, and intensive care staffs were shared with other services. Last, the teaching aspect of this institution led to greater involvement of physicians from other services as well as greater input of residents and fellows in patient care. Importantly, despite these differences, the unadjusted OM (2.8%; 10 of 355) and observed-to-expected ratio (0.77) were similar to that of LVH and HVH (Table 2). These results at an even smaller and distinctly different cardiac surgery program underscore our primary result that institutional volume may not be an accurate marker of CABG quality, and argue in favor of surgeon experience being the more critical factor.
Limitations of the study include the fact that our practice is representative of only a subset of current practice paradigms in which the same surgeon team is entirely responsible for cardiac surgery at multiple independent hospitals including both low-volume and high-volume programs. Although this eliminated surgeon-volume confounding effects, it also limits the general applicability of the findings. The described LVH and HVH programs are independent institutions with significant differences as well as important similarities that may contribute to outcomes. Briefly the HVH program is long-established (30 years) at an urban hospital and meets the high-volume Leapfrog Group criteria, whereas the LVH is a smaller suburban low-volume community hospital with roughly one third the procedure volume. Both hospitals have committed substantial resources including dedicated personnel, cardiovascular anesthesia, and operating rooms, as well as intensive care and step down units. Nursing and surgical assistant teams were similarly trained with equivalent operational guidelines. Yet their experience is distinct with about 50% of the nursing staff working at both hospitals. Surgical assistant overlap is minimal. The same perfusion team conducted all cardiopulmonary bypass duties at both institutions. There is no overlap in anesthesia.
The scope of this study and the similar procedure volumes among the surgeon team members do not allow for a meaningful direct assessment of surgeon volume effects. Annual surgeon volume, which was controlled for in our analysis, is only one measure of surgeon experience. Indeed, the question of whether the cumulative surgeon volume occurring over many years is a more appropriate volume measure, or at least should be concomitantly considered, was not addressed here or in any other study. Accordingly, future analyses should attempt to address the following question: Is annual surgeon volume equally important in determining quality of care for surgeons with many years of experience versus less experienced surgeons? Our study is not designed, nor sufficiently powered to address this question; all surgeons had comparable annual volumes.
In summary, when the same surgical team applies similar patient care standards and critical pathways, and emphasizes a team approach to cardiac surgery care, it is possible to achieve similar operative and midterm CABG outcomes at independent low-volume or high-volume cardiac surgery programs. Our analysis emphasized the importance of appropriate risk adjustments if comparisons are to be meaningful, which is only possible through detailed clinical databases [1, 25–28]. In conclusion, we find that hospital-volume and surgeon-volume effects are interdependent, which suggests that CABG outcomes are likely to be distinctly different for low-volume hospitals served by low-volume surgeons as opposed to high-volume surgeons. Therefore, hospital CABG volume per se should not be solely used as a marker of surgical quality. Instead, outcome quality markers should rely on thorough risk-adjustment, including surgeon volume factors. An analysis of CABG outcomes for all low-volume hospitals participating in The STS national database that includes annual (and possibly cumulative) surgeon volume as a covariable is warranted to unequivocally address this contention.
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Acknowledgments |
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