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Ann Thorac Surg 2003;75:1048-1058
© 2003 The Society of Thoracic Surgeons

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Review

The volume-outcome relationship: from Luft to Leapfrog

^a Department of Thoracic and Cardiovascular Surgery, Lahey Clinic, Burlington, Massachusetts, USA
^b Department of Health Care Policy, Harvard Medical School, Burlington, Massachusetts, USA
^c Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA

^* Address reprint requests to Dr Shahian, Department of Thoracic and Cardiovascular Surgery, Lahey Clinic, 41 Mall Rd, Burlington, MA 01805, USA
e-mail: david.m.shahian{at}lahey.org

	Abstract

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 
Numerous reports have documented a volume-outcome relationship for complex medical and surgical care, although many such studies are compromised by the use of discharge abstract data, inadequate risk adjustment, and problematic statistical methodology. Because of the volume-outcome association, and because valid outcome measurements are unavailable for many procedures, volume-based referral strategies have been advocated as an alternative approach to health-care quality improvement. This is most appropriate for procedures with the greatest outcome variability between low-volume and high-volume providers, such as esophagectomy and pancreatectomy, and for particularly high-risk subgroups of patients. Whenever possible, risk-adjusted outcome data should supplement or supplant volume standards, and continuous quality improvement programs should seek to emulate the processes of high-volume, high-quality providers. The Leapfrog Group has established a minimum volume requirement of 500 procedures for coronary artery bypass grafting. In view of the questionable basis for this recommendation, we suggest that it be reevaluated.

	Introduction

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 
Numerous studies have demonstrated substantial variability in outcomes among providers of specialized medical and surgical care, including coronary artery bypass grafting (CABG) [1–5]. Reports from Canada, which has a greater regionalization of services and fewer low-volume providers, appear to show less such variation [6, 7]. In an attempt to explain these observations, many investigators have studied the structural characteristics of hospitals and individual practitioners, particularly their volume of procedures [2–4, 7–29].

The overall evidence supporting an association between volume and outcome is compelling. Dudley and colleagues [16, 30] reviewed 70 studies comparing the results for high-risk procedures at high-volume and low-volume hospitals. Sixty of these studies showed significantly better results at high-volume hospitals and 8 studies showed a nonsignificant trend toward better results. None of the studies demonstrated significantly worse results for high-volume providers. As part of an Institute of Medicine workshop report, Halm and associates [10] reviewed 88 of the most credible volume-outcome studies published since 1980. There was a statistically significant positive relationship between hospital or physician volume and better outcome in 77% of studies, including all 16 reports that were judged to have the best methodology. None of the studies showed a significant negative relationship. Based on available literature, Birkmeyer [20] estimated that high-volume providers have mortality rates that are 20% to 50% lower than low-volume providers for procedures such as CABG, carotid endarterectomy, and abdominal aortic aneurysm repair, and perhaps even greater differences for pancreatectomy and esophagectomy.

Volume-based referral strategies have been advocated by the Leapfrog Group and others, not only because of evidence supporting a volume-outcome relationship, but also because other options for improving quality have been regarded as impractical or ineffective [30]. Other structural measures of quality are not as predictive of outcome as volume [20]; process measures are not well understood; regulatory approaches are currently viewed with less enthusiasm [26]; and market-based approaches such as report cards have not been successful in influencing consumer behavior [31–34]. For infrequently performed procedures such as esophagectomy and pancreatectomy, it is also difficult to accrue sufficient patients for meaningful statistical analysis [24, 26, 35]. A continuous quality improvement approach can be difficult, costly, time-consuming, and has rarely been implemented [20, 23, 30]. Notably, both continuous quality improvement and report cards have been used extensively and effectively only in cardiac surgery [21, 34, 36–38].

In contrast to these other alternatives, Dudley and Johansen [30] assert that volume-based referral strategies are an immediate and feasible approach to quality improvement that will result, on average, in better outcomes. Volume thresholds may be used to encourage (market-based) or mandate (selective contracting) consumer use of designated hospitals, to justify restrictive licensure and certification of referral centers, to control the diffusion of new services, and to guide professional training requirements [17, 18, 20, 22, 23, 26, 30].

In this review, we present the evidence for a volume-outcome relationship in a variety of medical and surgical conditions, examine some conceptual, methodological and statistical concerns regarding these studies, and consider the practical implications of regionalization. CABG studies are discussed in detail with particular attention to the 500-procedure volume threshold established by the Leapfrog Group.

	Evidence supporting the volume-outcome relationship

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 
Modern investigation of the volume-outcome hypothesis began with the work of Luft and colleagues [14] in 1979. These authors examined 1974 to 1975 discharge data on 12 surgical procedures from 1,498 hospitals. For certain operations (CABG, open heart surgery, vascular surgery, and TURP), hospitals that performed more than 200 procedures annually had patient-mix-adjusted death rates that were 25% to 41% lower than hospitals with fewer than 200 procedures (5.7% vs 3.4% for CABG). For a second group of procedures (colectomy, biliary tract surgery, total hip replacement, abdominal aortic aneurysm repair, vagotomy and pyloroplasty for ulcer disease, and cholecystectomy with common duct exploration), mortality stabilized at a much lower volume, ranging between 10 and 50 procedures per year. Finally, for vagotomy and cholecystectomy there was no observed volume-outcome relationship. In this prescient work, the authors identified many of the principles and questions that have been the basis of subsequent investigations over the next two decades, including (1) the applicability of the relationship to only more complex procedures; (2) procedure-specific functional relationships and thresholds; (3) the relative role of surgeon versus hospital volume; (4) the uncertain causality of the relationship; (5) the potential risks and benefits of regionalization; and (6) the need for comprehensive, risk-adjusted outcome data.

Subsequent studies have confirmed that the volume-outcome relationship persists despite adjustments for other structural characteristics [11, 12] and that there is considerable overlap in performance between high-volume and low-volume providers [39]. The volume-outcome association has been observed for both hospitals and individual providers, although some believe the evidence is stronger for the former [8, 25, 40]. The proportion of patients at an institution performed by low-volume providers is also important [13], and high-volume hospitals may actually enhance the performance of low-volume physicians [3, 41–43]. There remain many unanswered questions regarding the importance of the overall operative experience of surgeons, performance of closely related procedures, contemporaneous practice at more than one hospital, initial acquisition versus maintenance of skills, and transient versus permanent low-volume operators [13, 21, 23, 40, 44].

In the largest study currently available, Birkmeyer and associates [24] reviewed the results of 2.5 million Medicare patients who underwent 1 of 14 cancer or cardiovascular procedures between 1994 and 1999. Mortality and volume were inversely related for all these procedures, but the magnitude of the difference between very high-volume and very low-volume providers varied substantially (large differences for esophagectomy and pancreatectomy, small differences for CABG and carotid endarterectomy).

Certain specific conditions and procedures have been most extensively studied, including vascular surgery, cancer, and cardiac care. Many investigators [23, 41, 45–50], although not all [51–53], have documented lower postoperative death and stroke rates for patients undergoing carotid endarterectomy at high-volume hospitals. In a recent review by Birkmeyer and associates [24], of 479,289 Medicare patients, the difference between low-volume and high-volume hospitals was minimal (< 40 procedures, 1.7% mortality; > 164 procedures, 1.5% mortality). Studies of abdominal aortic aneurysm repair have generally demonstrated an inverse relationship of hospital volume and mortality for elective procedures [3, 45–47, 54–57] and surgeon volume and mortality for ruptured aneurysms [55, 58].

Hillner [59] reviewed volume-outcome studies in cancer treatment and concluded that the relationship existed primarily for more complex and less frequently performed procedures. Hannan and colleagues [60] used hierarchical models to study New York patients undergoing cancer resection of the colon, stomach, or lung between 1994 and 1997, and an inverse relationship between mortality and volume for surgeons and hospitals was noted. Begg and associates [61] reviewed the outcomes of 5,013 Medicare patients who underwent resections of the pancreas, esophagus, liver, lung, or pelvis between 1984 and 1993. There was a significant inverse relationship between volume and mortality for all procedures except pneumonectomy. For esophagectomy, 30-day mortality for the low-volume providers (1 to 5 procedures per year) and high-volume providers (> 11 procedures per year) was 17.3% and 3.4%, respectively, and for pancreatectomy the corresponding values were 12.9% and 5.8%, respectively. These two operations provide the most dramatic examples of the volume-outcome association, probably because of their relative infrequency, technical complexity, and challenging postoperative care [62–69]. In the recent Medicare study by Birkmeyer and colleagues [24], adjusted surgical mortality for pancreatectomy varied from 16.3% (< 1 procedure per year) to 3.8% (> 16 procedures per year), and for esophagectomy the mortality ranged from 20.3% (< 2 procedures per year) to 8.4% (> 19 procedures per year).

Cancer studies have also demonstrated the impact of volume on endpoints other than surgical mortality, including the use of more advanced surgical techniques, perioperative morbidity, local recurrence, and long-term survival [67, 70–74]. This reflects the importance not just of surgical skill but also process issues such as treatment selection, adjuvant therapy, and long-term follow-up.

The volume-outcome association also has been investigated in various types of cardiac care including heart transplant [75], pediatric cardiac surgery [57, 76, 77], myocardial infarction [78, 79], percutaneous transluminal coronary angioplasty [42, 43, 80–83], and CABG [2–4, 7, 14, 21, 28, 34, 38–40, 57, 84–86].

	Coronary artery bypass grafting

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 
CABG is a mature procedure that has been performed for three decades, and cardiac surgeons have led all other medical specialties in the development of risk-adjusted databases, publication of outcomes, and continuous quality improvement activities. CABG is also unique among high-complexity procedures in its frequency. Data presented by Birkmeyer and associates [17] suggest that CABG is 10 times as common as abdominal aortic aneurysm resection in the United States, 150 times as common as esophagectomy, and 2 1/2 times as common as carotid endarterectomy. Ironically, despite being the most frequently performed and thoroughly investigated of all complex surgical operations, CABG has also been targeted with the most aggressive and restrictive volume standards.

Beginning with the original work of Luft and associates [14] in 1979, showing a volume threshold of about 200 procedures, CABG was a common focus of early volume-outcome studies [4, 28, 39]. Showstack and associates [84] studied 18,986 patients who underwent CABG at one of 77 California hospitals in 1983. Overall, hospitals that performed 20 to 100 procedures per year or 201 to 350 procedures per year had significantly worse outcomes than the highest volume hospitals (> 350 procedures per year). For scheduled operations, only hospitals with 201 to 350 procedures per year had statistically significantly higher mortality (2.9% vs 2.2%); however, for nonscheduled patients, hospitals with 20 to 100 or 201 to 350 procedures annually had significantly higher mortality. Hospitals that performed 101 to 200 CABG procedures per year, which accounted for 28% of total hospitals and 16% of all CABG patients, did not differ significantly from the highest volume group in either the scheduled or nonscheduled category, and there was only a marginal difference when all patients were considered (p < 0.10). The greatest lifesaving potential in this study appeared to be for nonscheduled patients, similar to the findings of Nallamothu and associates [87] that a significant mortality difference between low-volume (< 200 procedures annually) and high-volume hospitals was observed only in the minority of patients who were high-risk.

Grumbach and associates [7] used 1987 to 1989 discharge abstract data to compare the results of CABG operations in New York, Canada, and California. In New York and Canada, 60% of CABG procedures were performed in hospitals with an annual CABG volume exceeding 500 procedures, whereas the corresponding value for California was only 26%. Four percent of New York and 2% of Canadian CABG procedures were performed in hospitals with an annual CABG volume of fewer than 200 procedures per year, whereas over one-third of the patients in California were performed in such hospitals. The highest mortality rate in this study was in California hospitals performing fewer than 100 CABG procedures per year, which comprised 31% of the California hospitals. Interestingly, just as in the study of Showstack and associates [84], the mortality for hospitals performing 100 to 199 annual procedures in New York was not significantly different from hospitals that performed more than 500 procedures per year (p = 0.16). Similarly, mortality for the 200 to 499 procedures per year Canadian group was no different than that of Canadian hospitals performing more than 500 procedures per year (p = 0.51).

In the most recent and largest volume-outcome study of CABG based on administrative data, Birkmeyer and associates [24] have reported the results of 901,667 Medicare patients who underwent CABG at 1,068 hospitals between 1994 and 1999. The range of adjusted mortality was much smaller than in earlier Medicare studies, varying from 5.6% (< 230 estimated total CABG procedures per hospital) to 4.5% (> 849 procedures). Over the broad middle range of volume from 230 procedures to 849 procedures, mortality varied only from 5.1% to 4.7%. This may be an important demonstration of the decreasing impact of volume over time as procedures mature.

In 1991, Hannan and colleagues [2] reported the first volume-outcome study for CABG to use properly risk-adjusted clinical data. This study has been cited as one of the best in the literature by two principal advisors [16, 17] to the Leapfrog group on evidence-based referrals, and it has undoubtedly influenced the recommendation of that organization regarding volume standards for CABG. The data source for this study included 12,448 patients who underwent CABG in New York during 1989, which was the first year of the New York Cardiac Surgery Reporting System (CSRS). Higher volume hospitals had higher expected mortality, which contradicts the findings of some other studies [11, 12, 14, 87, 88] that such hospitals may attract better risk patients. Using a logistic regression model, the log of surgeon volume was significantly related to mortality (p < 0.001), but hospital volume was only "marginally related" to mortality (p = 0.04). Risk-adjusted hospital mortality ranged from 7.25% in hospitals performing between 1 to 199 procedures per year to 2.85% for hospitals performing more than 890 cardiac procedures per year. Risk-adjusted mortality for surgeons performing fewer than 55 procedures per year was 8.14% compared with 2.43% for surgeons performing 260 or more procedures per year. High-volume surgeons in high-volume hospitals achieved the lowest mortality (2.18%).

Several important aspects of this study must be emphasized. First, in contrast to virtually every other publication relating CABG volume and mortality, these authors used total number of cardiac operations as the volume indicator, which is in our opinion a much better measure of overall cardiac surgical experience. However, volumes cited in this article must be interpreted with caution because some refer to total cardiac experience and some to CABG only. Second, the data in this study came from 1989, the first year of data collection in the New York Cardiac Surgery Reporting System. This was the least reliable year of the New York database, primarily because of under-coding and over-coding of comorbidities [31, 89].

Finally, the nature of the functional relationship between volume and mortality in this and other studies must be closely scrutinized. We extracted hospital mortality and volume data from this article, and we present them in graphical form in Figures 1 to 3. Figure 1 is a scatterplot of the adjusted mortality rate versus CABG volume for each hospital. At higher volume levels, there is less variability, although a few programs exceed the state average risk-adjusted mortality. Over the broad middle range of volume, there is increasing dispersion of results on both sides of the state average as sample sizes decrease and confidence intervals broaden, consistent with the behavior of a binomial proportion. Importantly, numerous hospitals performing 150 to 500 procedures per year had risk-adjusted mortality rates well below the state average. The outcomes in the very lowest volume group of hospitals are clearly anomalous and skewed toward high mortality; their performance suggests that they may have a different functional relationship between volume and mortality than the remainder of hospitals. Figure 2 is a plot of the log odds of observed mortality versus CABG volume. The horizontal line is the log odds of observed mortality for the entire state, and the irregular line is a LOWESS smoother (robust locally weighted scatterplot smoother; f = 0.5, 2 iterations; MINITAB Statistical Software, Release 13 for Windows; State College, PA), a nonparametric estimate of the shape of the relationship between these variables [90]. Figure 3 is the same plot for the log-odds adjusted mortality.

View larger version (13K): [in this window] [in a new window]   Fig 1. Hospital coronary artery bypass grafting (CABG) volume and adjusted mortality for New York state in 1989 [2].

View larger version (16K): [in this window] [in a new window]   Fig 2. Hospital coronary artery bypass grafting (CABG) volume and log-odds of observed hospital mortality for New York state in 1989, as derived from the data of Hannan and associates [2]. The curvilinear line is a LOWESS scatterplot smoother showing the shape of the relationship between the two variables. The horizontal line is the log-odds of observed mortality for the entire state.

View larger version (16K): [in this window] [in a new window]   Fig 3. Hospital coronary artery bypass grafting (CABG) volume and log-odds of adjusted mortality for New York state in 1989 [2]. The curvilinear line is a LOWESS scatterplot smoother showing the shape of the relationship between the two variables. The horizontal line is the log-odds of observed mortality for the entire state.

Contrary evidence
The most compelling evidence against a general volume-outcome relationship comes from the Veterans Affairs Administration [51, 91]. Using a comprehensive risk-adjusted database and a variety of statistical techniques, Khuri and associates [51] investigated outcomes for eight common, noncardiac procedures among 68,631 patients operated upon in Veterans Affairs (VA) hospitals. No relationship of volume to 30-day mortality was noted, and there was no volume threshold. Although these results appear to conflict with those of most other studies, there are significant caveats regarding generalizations from VA data [30, 51, 85, 92]. The patients are unusually homogenous and primarily older males. VA hospitals are generally low to moderate volume, and thus the range of patient volumes available for comparative analysis is somewhat restricted. Several procedures (esophagectomy and pancreatectomy) having the strongest volume-outcome association in prior studies were not included in the report of Khuri and associates [51]. In the VA, many processes and structural requirements have already been standardized and results have been monitored for years. Finally, there is a close affiliation of many VA hospitals with high-volume academic centers, and they may consequently benefit from common staff, processes, and oversight procedures.

With regard to the volume-outcome relationship for CABG, Clark [86] reviewed data from 1991 to 1993 on 120,377 patients from 180 practice groups (not hospitals) that had submitted their results to the Society of Thoracic Surgeons database. Procedural volumes ranged from fewer than 100 per year to more than 900 per year. Linear and logistic regression showed a "weak to very weak inverse correlation" between volume and mortality (r² = 0.0492; odds ratio = 1.000), but the only "clinically relevant" correlation of volume to mortality was for groups performing fewer than 100 procedures per year. Notably, 56.1% of patients were operated on by groups performing 500 or fewer procedures per year, which is the current volume standard of the Leapfrog group. Arguably, the Society of Thoracic Surgeons database is voluntary and may be skewed toward groups with better results. Also this study focuses on groups, not hospitals or surgeons, and thus it is not strictly comparable with most other volume-outcome studies.

Shroyer and colleagues [85] investigated the results of 23,986 CABG procedures performed between 1987 and 1992 at 44 VA hospitals. When hospital CABG volume was used as a covariate in a multivariate risk model, it had no relationship to mortality. In hospital models, threshold analysis demonstrated a change point at 100 CABG procedures per year, although this was not confirmed in a Poisson additive model. Although this study is large and well documented, it may not be generalizable because of the same caveats discussed previously regarding the unique features of VA hospitals.

Sollano and associates [57] studied discharge abstract data of 97,137 New York patients undergoing CABG between 1990 and 1995 (the period after implementation of a statewide report card). There was no relationship of volume to mortality for CABG, although there was a relationship of volume to mortality for pediatric cardiac surgery, and the authors attributed this difference to the impact of public outcome reporting of CABG.

	Controversial aspects of the volume-outcome hypothesis

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 
Despite the preponderance of studies that support a volume-outcome relationship, and the increasing use of this hypothesis to justify major health policy decisions, many unanswered questions remain.

	Conceptual

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 
A certain level of training and repetition is important for any complex task, and many studies document a continuous decline in surgical mortality with increasing volume. However, common experience in nonmedical areas would suggest that volume is not an absolute prerequisite for high quality, nor is it necessarily even the most frequently used criterion. For specialized medical care, some threshold level of volume is required to develop the technical proficiency and processes necessary for optimal patient care. However, notwithstanding this caveat, high-quality results are often achieved by low to moderate-volume providers, and high volume does not guarantee high quality.

	Methodology of volume-outcome studies

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 
Data source
Although a few volume-outcome studies are based on clinical databases [2], the majority are limited by their use of administrative data from discharge abstracts [23]. Many studies focus only on the Medicare population because of the availability of that data [24]. Birkmeyer [18], a proponent of volume-based referral, also acknowledges that many studies are skewed by data from both high-volume referral centers and from low-volume California hospitals, and this may limit their general applicability. Furthermore, many reports are outdated and do not take into account advancements in medical and surgical care [24]. The performance gap between low-volume and high-volume providers has been observed to narrow over time [23, 83, 93] because of both general advancements in medicine and the maturation of specific procedures.

Risk adjustment
The degree of risk adjustment has varied widely among volume-outcome studies [23]. Sowden and associates [93] reviewed seven publications based on United States CABG results from 1972 to 1992. As risk adjustment improved from worst to best, the odds ratio for mortality at high-volume hospitals narrowed from 0.54 to 0.84. The mitigating effect of risk-adjusted outcomes on the magnitude of the volume-outcome relationship has been also noted in numerous other studies [47, 85, 94], but it is unlikely that this omission would have uniformly favored high-volume hospitals [30], or that it would change the general nature of the observed relationship [23].

Cross-sectional versus longitudinal analysis
Another methodological concern is the cross-sectional nature of most studies. Comparisons are made during one time period among many hospitals, often differing in location, structural characteristics, patient numbers, and severity. As Hannan [22] has observed, a better way to test the relationship between volume and outcome would be a longitudinal study, assessing what happens at a single institution over time as its volume changes. This has the advantage of holding constant many other characteristics of the hospital and its patient population. Few investigations [55, 95] have studied such longitudinal relationships because provider volumes rarely undergo dramatic changes over time. However, in a recent longitudinal study using hierarchical models, Bronskill and colleagues [96] found no relationship between surgeon volume for CABG and in-hospital mortality using 1991 to 1995 data from the New York State Cardiac Surgery Reporting System.

Statistical analysis
Statistical methodologies have varied widely among volume-outcome studies and include standard multivariable regression and logistic regression, Poisson additive models [85], and hierarchical models [51, 60, 96]. Most studies have modeled the relationship between volume and mortality as a single, continuous, nonlinear function (logarithmic, exponential decay, quadratic, and hyperbolic). The functional relationship appears to vary from procedure to procedure, as do the domain and range of the variables and the inflection points of their volume-mortality curves. The performance of a few extremely low-volume providers is largely responsible for the significant results in many studies. If these were considered as a separate aberrant group rather than being forced into a global functional relationship with the remaining hospitals, such studies would likely demonstrate a less significant volume-outcome association over the intermediate range of volumes.

Volume thresholds, such as the 500-procedure standard established for CABG by the Leapfrog Group, imply two distinct aspects of the relationship between hospital volume and mortality. First, they suggest that the relationship is different for hospitals performing fewer than 500 procedures per year than those performing more than this number. More importantly, such thresholds also imply that hospitals within each of these volume groups have a similar volume-mortality relationship. This may be true of hospitals performing many procedures where we expect an asymptote, but for smaller volume there may be a decreasing relationship as volume increases. A more realistic approach to modeling the volume-outcome relationship should incorporate spline functions (piecewise polynomial functions, often higher order) or other flexible parameterizations that can incorporate different functional relationships for each volume interval.

Hospital or physician volume, the predictor variable of interest in volume-outcome studies, has been analyzed as either a continuous or categorical variable. In the latter, a change point is selected and providers are categorized into low-volume or high-volume groups for analysis. These change points have been variously determined from external literature standards, visual inspection of volume-outcome curves, mean or median volume, sequential analysis of variance, and Poisson additive models. Altman and colleagues [97] have discussed the disadvantages of categorizing continuous data in this fashion, including not only the loss of important information but also the potential for introducing Type I statistical error. As noted by Halm and associates [10], it has not even been determined whether it is more appropriate to group together all providers performing in excess of some low-volume threshold, or if only the highest volume providers have the best results. Finally, the definition of low volume varies dramatically in the literature depending upon the procedure being studied. This designation has been applied to providers performing fewer than 5 to 10 procedures per year for certain operations like esophagectomy and pancreatectomy, whereas for CABG it has often included hospitals performing hundreds of procedures per year. The Leapfrog Group recommendations imply that anything less than 500 CABG procedures per year is low volume.

These considerations are of more than theoretical statistical interest. Although the determination of volume thresholds appears somewhat arbitrary in many published studies, these have been extracted and used by insurers and regulators to impose minimum volume requirements. The lack of a formal statistical approach to the identification and estimation of the volume change point is one of the most troubling aspects of the volume-outcome debate. A principled approach to this inferential question, characterized in the statistical literature as an inverse prediction or a change point problem, should involve not only the estimation of the change point but also its 95% confidence interval. An example of such an approach is the determination of optimal body mass index (BMI) from data on the relationship between BMI and mortality [98]. Health policy planners must decide their primary goal in studying the volume-outcome relationship. Is it to exclude those providers expected to be the lowest performing in a region or selectively refer only to those providers predicted to have the highest performance (both of which are threshold or change point problems)? Or is it to predict the level of volume that will achieve some predetermined outcome standard (an inverse prediction problem)? Once these objectives are determined, the appropriate statistical techniques, which are frequently complex and nontrivial, can be applied.

In most volume-outcome studies the endpoint (typically mortality) has a low incidence. By the very nature of the study design, the sample sizes differ substantially among providers and are sometimes quite small; this has a considerable impact upon the reliability of interprovider comparisons using classic inferential statistics [26, 35]. Typically, a sample of size n is taken from a provider and is used to make inferences about its true underlying population proportion (ie, mortality), which is the real value of interest. The larger the sample-n, the more certain we are that the sample proportion is a good estimate of the population proportion. Conversely, with small sample sizes we have less confidence about the true performance of the provider, and much of the observed increase in variability may be random. Because of small sample sizes, the observed results of lower-volume providers are greatly affected by even one or two deaths [38]. In addition to the greater statistical uncertainty of estimates when sample sizes are small, Stein’s theorem [99] also suggests that a better estimate of the true performance of such low-volume providers may be obtained by shrinking their observed mortality rates toward the mean of like providers. This reduces the possibility they will be falsely labeled as outliers, one of many advantageous features of hierarchical models [32, 100, 101]. For all these reasons, investigators regard small sample size as one of most troubling methodological weaknesses of volume-outcome research [18, 22, 26, 35, 88], just as it is also a limiting factor in producing credible risk-adjusted outcome reports [32, 102].

This statistical concept is illustrated in Figure 4, which depicts the hypothetical results of nine hospitals with annual caseloads varying from 50 to 800 procedures, all of which have a 4% observed mortality rate. For hospitals having lower yearly volumes, the exact 95% binomial confidence intervals (MINITAB Statistical Software, Release 13 for Windows, State College, PA) of these estimates broaden dramatically, thus indicating that they are a less certain measure of the true performance of these hospitals.

View larger version (17K): [in this window] [in a new window]   Fig 4. Exact 95% confidence intervals (diamonds) for 4% observed mortality (squares) at varying procedure volumes (sample sizes). The confidence intervals widen substantially as sample sizes decrease, making valid interprovider comparisons problematic using standard inferential statistical techniques.

	Causality

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 
Because the volume-outcome relationship has increasingly become the basis for major health policy recommendations, it is troubling that its mechanism remains problematic. Historically, the two major hypotheses are practice makes perfect and selective referral [55, 95, 104]. In the former, it is presumed that increasing volume brings additional expertise, whereas the latter formulation suggests that consumers are drawn to hospitals and physicians with perceived or historically high performance.

It is likely that processes of care also may be largely responsible for the volume-outcome relationship. Research efforts should focus on identifying and disseminating these processes, which may cause less disruption to the health care system than shifting patients among providers [18, 23]. Possible process factors include appropriate selection of patients and treatment type, integrated perioperative care, adjuvant therapy, and long-term follow-up [18, 30, 62, 67, 68, 70, 105].

These various hypotheses have more than theoretical importance. If practice makes perfect is the mechanism, then it should be possible to channel large numbers of patients to almost any institution with the expectation that increased volume will produce better outcomes. However, if selective referral is the mechanism, then contracting or directing patients on any criteria other than actual current performance (eg, low price) may result in unchanged or even poorer outcomes [26, 39, 55, 104]. In this context, it is important to note that the only two reports that specifically studied this question for CABG identified selective referral as the mechanism [95, 104].

	Practical implications of regionalization

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 
The volume-outcome relationship has been used to justify regionalization of specialty services. This is often based upon estimates of lives saved, a statistical extrapolation that typically requires substantial assumptions. Tempering the enthusiasm for regionalization are a number of potential negative consequences [16–20, 23, 26–28, 30, 40, 106] for the patient (delay or avoidance in seeking care, loss of continuity with primary physician, preference for local care regardless of outcomes [107], small possibility of inferior care at referral center [23]), for low-volume hospitals (unfair stigmatization, closure of related services, financial viability, incentive to inappropriate utilization), for high-volume hospitals (inability to sufficiently increase capacity and maintain quality), and for the regional health care market (economic distortion, unmerited halo effect and excessive contractual power for high-volume providers, diminished incentive to develop risk-adjusted outcome reporting and continuous quality improvement programs).

Some studies [27, 28] demonstrate that full regionalization (ie, sending all patients to the highest volume hospitals) would disenfranchise a high percentage of institutions currently performing complex procedures (eg, 80% of urban hospitals currently performing elective abdominal aortic aneurysm repair [44]), and this would simultaneously create an increased level of demand at high-volume hospitals that may be impossible to accommodate.

The practical consequences of redirecting large numbers of patients to high-volume providers has led some to propose selective or partial regionalization. This would be based on the mortality spread between low-volume and high-volume providers, the number of patients undergoing a particular procedure, patient acuity, and practical considerations [16, 17, 19, 27, 28, 30, 87]. As suggested by Epstein [44], the least disruption to the health care system might result from targeting procedures with the greatest mortality difference between low-volume and high-volume providers, even though some more frequently performed procedures with a smaller difference in outcome may potentially impact a larger number of patients. Based upon the CABG studies of Showstack [84] and Nallamothu [87], targeted regionalization for particularly high-risk subsets of patients also should be considered.

	Conclusion

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 
Volume-based referral strategies are best used for procedures like esophagectomy and pancreatectomy with large differences in outcomes between low-volume and high-volume providers, and also for particularly high-risk patient subsets. For other complex procedures with a less dramatic range of mortality, volume standards may be used as a red flag to focus attention on the lowest volume providers, not because their results are uniformly poor but because their small numbers make it difficult to accurately assess their performance. Whenever possible, risk-adjusted outcome data should be used to supplement or supplant such volume standards [22]. Continuous quality improvement programs should study and then seek to emulate as many of the process and structural characteristics of high-volume, high-quality providers that are feasible.

Although the Leapfrog Group volume thresholds for other invasive procedures are generally compatible with published outcome data, their 500-procedure volume standard for CABG is inconsistent with the results of empirical studies and the recommendations of major professional societies. Extensive reviews by the Society of Thoracic Surgeons [40, 86] and the Veterans Affairs Administration [85] demonstrate no significant volume effect except at very low levels (100 procedures per year), and the 1999 joint guidelines of the American Heart Association and American College of Cardiology only recommend close monitoring of programs performing fewer than 100 procedures per year [108]. The American College of Surgeons suggests that 100 to 125 procedures per year are sufficient to maintain quality, but that at least 200 procedures are necessary to function efficiently [109].

At a time when overall CABG rates are declining because of percutaneous transluminal coronary angioplasty, establishment of a 500-procedure standard for CABG may encourage inappropriate utilization, disenfranchise a substantial number of high-quality programs, threaten teaching programs, or adversely impact angioplasty and other urgent cardiac care. These volume thresholds should be reevaluated using more appropriate statistical methods for inferring change points from the empirical data, and the Leapfrog Group should also adhere to its plan to waive volume standards whenever high-quality outcome data are available.

We can provide no better conclusion than this recent caveat from Professor Luft [88], the pioneer in volume-outcome research:

"Given that volume per se does little more than assure reasonable confidence intervals around statistical estimates, volume-based policies for excluding or closing facilities are inferior to policies based on the routine reporting of risk-adjusted outcomes and policies to encourage the referral of patients toward facilities with better than expected outcomes and away from those with worse than expected outcomes."

	References

Top Abstract Introduction Evidence supporting the volume... Coronary artery bypass grafting Controversial aspects of the... Conceptual Methodology of volume-outcome... Causality Practical implications of... Conclusion References

 

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