HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Personal Folders Download to citation manager Permission Requests Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Glance, L. G. Articles by Osler, T. M. Search for Related Content PubMed PubMed Citation Articles by Glance, L. G. Articles by Osler, T. M. Related Collections Coronary disease

Ann Thorac Surg 2003;76:1155-1162
© 2003 The Society of Thoracic Surgeons

---

Original article: cardiovascular

Is the hospital volume-mortality relationship in coronary artery bypass surgery the same for low-risk versus high-risk patients?

^a Department of Anesthesiology, University of Rochester Medical Center, School of Medicine and Dentistry, Rochester, New York, USA
^b Department of Community and Preventive Medicine, University of Rochester Medical Center, School of Medicine and Dentistry, Rochester, New York, USA
^c Department of Health Policies, University of Rochester Medical Center, School of Medicine and Dentistry, Rochester, New York, , USA
^d Department of Surgery, The University of Vermont College of Medicine, Burlington, Vermont, USA

Accepted for publication May 9, 2003.

^* Address reprint requests to Dr Glance, Department of Anesthesiology, University of Rochester Medical Center, 601 Elmwood Ave, Box 604, Rochester, NY 14642, USA
e-mail: laurent_glance{at}urmc.rochester.edu

	Abstract

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 
BACKGROUND: There is evidence to support the existence of an inverse relation between mortality after coronary artery bypass graft (CABG) surgery and procedure volume. It is unclear whether all patients benefit equally from having CABG surgery performed at high-volume centers. The objective of this study was to determine whether the volume-outcome association for CABG surgery is modified by patient risk.

METHODS: This retrospective cohort analysis was conducted using data from the Cardiac Surgery Reporting System database on all patients (20,078) undergoing CABG surgery in New York State who were discharged in 1996. The main outcome measure was in-hospital mortality as a function of procedure volume after adjusting for severity of disease. Logistic regression modeling was used to explore the interaction between patient risk and procedure volume.

RESULTS: There is a significant interaction between procedure volume and patient risk (p = 0.01). The final model exhibits excellent discrimination (C statistic = 0.818) and goodness-of-fit (Hosmer-Lemeshow statistic = 6.02; p = 0.645). Very low (<0.5%) and low-risk (0.5%–2.0%) patients exhibit a greater reduction in CABG mortality than high (5.0%–10.0%) and very high risk (>10%) patients at high-volume centers relative to low-volume centers. Among the highest risk patients (>25% risk of mortality), higher risk patients have better outcomes at higher volume centers.

CONCLUSIONS: For the vast majority of patients, low-risk patients benefit significantly more than high-risk patients from undergoing CABG surgery at high-volume centers instead of at low-volume centers. Low-risk patients benefit significantly more than high-risk patients from undergoing CABG surgery at high-volume centers instead of at low-volume centers. However, before generalizing these findings to other states, this study should be repeated using other regional population-based clinical databases.

	Introduction

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 
There is strong evidence to support an inverse relationship between procedure volume and mortality for certain surgical procedures [1–5]. The Institute of Medicine reports that "[t]here can be little doubt that for a wide variety of surgical procedures and medical conditions, higher volumes (whether assessed by hospital or by physician) are associated with better health outcomes" [5]. Research on the volume-outcome relationship has important implications for health care policy. Based on the evidence that higher procedure volumes result in better outcomes, it has been suggested that selective referral of patients to high-volume centers could result in lower overall mortality for certain conditions [6]. Health insurance purchasers, insurers, and regulators may in the future use hospital volume criteria as the basis for evidence-based referrals to channel patients towards high-quality providers [5]. The Leapfrog Group, a consortium of major corporations representing 10 million employees in the United States, advocates a policy of evidence-based hospital referral for high-risk surgery based primarily on hospital volume [7].

Many studies have investigated the volume-outcome relationship for coronary artery bypass surgery [1, 2, 8–16]. Most of these studies have demonstrated that better outcomes are associated with higher hospital volumes [1, 2, 8–13, 16–18]. However, the exact nature of the volume-outcome relationship for coronary artery bypass graft (CABG) surgery is less clear in some of the more recent studies. Birkmeyer and colleagues [1] published their findings from a study of more than 900,000 Medicare patients in an administrative database and found that higher procedure volumes resulted in lower mortality. The primary limitation of this study is that the risk adjustment methodology used is based on administrative data. ICD-9-CM codes do not represent all important clinical information, may not always be coded accurately by nonclinical personnel, and do not distinguish between preexisting conditions and complications [19]. Two other studies, both using prospectively collected clinical data on all patients undergoing CABG surgery in New York State (NYS) have also identified a clear volume-outcome association [12, 13]. However, another study also based on NYS showed no significant volume-outcome relationship [14]. This latter study was performed using administrative data, and thus may not adjust adequately for severity-of-disease. Two other large studies, both using clinical databases did not support the existence of a significant volume-outcome association: the first, based on The Society of Thoracic Surgery Cardiac database [20], the second, on the Department of Veterans Affairs database [15]. One of the limitations of the Veterans Affairs (VA) study, identified by the study authors, is that the CABG volumes at VA hospitals may not take into account the procedures performed at non-VA hospitals by VA surgeons.

One aspect of the volume-outcome relationship that has received very little attention is the question of whether the outcome benefit attributable to higher procedure volumes, if present, is modified by severity-of-disease. In other words, do patients who are more ill have a greater benefit from being treated at higher-volume centers than healthier patients? One of the early CABG studies demonstrated a stronger inverse relationship between volume and mortality in patients who underwent nonscheduled CABG surgery versus patients undergoing elective CABG surgery [11]. The only other study [16] to investigate the interaction between patient risk and the volume-outcome relationship was performed using a commercial outcomes benchmarking data set. After adjusting for severity-of-disease using All Patient Refined-Diagnosis Related Groups, patients with a moderate (2% to 5%) and high (5% to 20%) predicted risk of death were found to benefit more than patients at minimal (< 0.5%) and low (0.5 to 2%) risk of death from having CABG surgery performed at high-volume versus low-volume hospitals. No other volume-outcome studies for CABG surgery has evaluated whether the outcome benefit attributable to higher procedure volumes is modified by severity-of-disease. The finding that only specific subgroups of patients benefit from being treated at high-volume centers could lead to policies that promote targeted regionalization of care (ie, only transferring those patients who would benefit most from being treated at high-volume centers) [16].

This study extends previous work in this area by evaluating whether severity-of-disease modifies the volume-outcome relationship in CABG surgery using a clinical database. By using a clinical data set, our study is less likely to be biased by inadequate risk adjustment. Our study specifically models the interaction between patient risk and hospital volume in order to determine whether low-risk, intermediate-risk, and high-risk patients benefit equally from having CABG surgery at high-volume centers. The finding that low-risk, intermediate-risk, and high-risk patients do not benefit equally from receiving care at high-volume centers may have significant implications for the application of policies that advocate selective referral of CABG surgical patients.

	Material and methods

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 
Data
The database used for this retrospective cross-sectional analysis was obtained from the Cardiac Surgery Reporting System (CSRS) of NYS. This database includes information on patient demographics, hospital identifiers, preoperative risk factors, and outcomes. All patients undergoing CABG surgery in NYS who were discharged in 1996 (n = 20,078) were included in this analysis. The structure, data collection, and audit mechanism for this registry have been previously described [12, 21].

Exploratory data analysis
The median number of CABG procedures performed at hospitals in this database was 535. For the purpose of exploratory data analysis, hospitals with a CABG surgery volume greater than 500 cases per year were designated as high-volume hospitals. The demographics and risk factors of patients undergoing CABG surgery at low-volume and high-volume hospitals were compared using standard statistical techniques. We then used the 1996 CSRS CABG prediction model [22] (Model 1) to divide the patients in the data set into four risk groups for in-hospital mortality: very low (< 0.5%), low (0.5% to 2%), moderate (2.0% to 5.0%), high (5.0% to 10%), and very high (> 10%). This model has been previously validated [22] and shown to have excellent discrimination (C statistic equal to 0.813) and excellent calibration (Hosmer-Lemeshow statistic equal to 5.94) [23].

The odds ratio for in-hospital mortality for patients at high-volume versus low-volume hospitals were then calculated for each of the four risk groups.

New models
A new logistic regression model was developed (Model 2) to explore the influence of hospital volume in patients undergoing CABG surgery. The set of covariates in this model includes all 18 risk factors in the 1996 CSRS CABG model [22] and hospital volume; hospital volume was included in this model as a main effect only. The volume measure was defined as the annual number of patients undergoing CABG surgery for a particular hospital in the database. A robust variance estimator [24] was used to accommodate the hierarchical structure of the data because individual patients are nested within hospitals, and therefore patient outcomes within the same hospital may be correlated.

A third model was constructed (Model 3), which included hospital volume (V) as a main effect and an interaction term. This model was specified so that V would interact with the baseline probability of death. The "main effect" volume term in this model is specified by the term ß_V*V'. The interaction terms are specified by ß_{V int}V'(p_base)^.1 and ß_{V int}'V'(p_base)^.3, where V' is the hospital volume minus the volume of the lowest-volume center, and p_base is the predicted probability of death for a patient if that patient were treated at the lowest-volume center. The model specification is shown below:

where

and

We chose to specify this model to have volume interact with the baseline probability of death instead of having volume interact with each risk factor individually in order to make it feasible to interpret the interaction between volume and overall patient risk. This model equation is constrained in such a way that the set of coefficients ß₁**,...,ß**_p are the same for both the main effects and interaction portions of the model. Because volume interacted with a constrained form of the risk factors, the maximum likelihood estimators for the model coefficients could not be computed using conventional algorithms. A set of routines written in STATA{2001 11/id} were used to obtain the maximum likelihood estimators for this model. After first coding the likelihood function for this model using the "ml model" command, the "ml maximize" command was used to carry out the maximization [25]. The ml maximize command has the option to compute the robust variance estimators necessary to evaluate data with a hierarchical structure [25]. The two models (Models 2 and 3) were compared using a joint Wald test. The performance of the final model was then evaluated using measures of discrimination and calibration [26]. The C statistic was used to assess model discrimination. The Hosmer-Lemeshow goodness-of-fit statistic was calculated using a program implemented in STATA.

	Results

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 
The population studied consisted of all the patients undergoing CABG surgery in NYS who were discharged in 1996 (n = 20,078). These patients were treated in 32 hospitals. Seventy-five percent of the patients underwent surgery at high-volume centers (> 500 cases/yr). Figure 1 displays the distribution of CABG surgery volume by hospital. The differences between the patient populations treated at high-volume and low-volume hospitals are summarized in Table 1. Low-volume hospitals treated a higher proportion of diabetic patients (32% vs 27%), end-stage renal disease on dialysis (1.4% vs 0.84%), patients with recent myocardial infarctions, and patients undergoing redo surgery (12.4% vs 11.4%). The proportion of patients with ejection fractions less than 20% and between 20% and 29% were not statistically different; however more patients with ejection fractions between 30% and 39% underwent CABG surgery at high-volume hospitals. The predicted in-hospital mortality for the low-volume and high-volume cohort were the same (p = 0.45). The observed in-hospital mortality rate was greater in the low-volume cohort as compared with the high-volume cohort (2.84% vs 2.30%; p = 0.03).

View larger version (46K): [in this window] [in a new window]   Fig 1. Hospital coronary artery bypass graft surgery volume: number of coronary artery bypass graft operations at each hospital in the data set.

View this table: [in this window] [in a new window]   Table 1. Demographics and Risk Factors of Patients Undergoing Coronary Artery Bypass Grafting at High-Volume (> 500 cases/yr) and Low-Volume ( 500 case/yr)

View larger version (11K): [in this window] [in a new window]   Fig 2. Relative odds of death of patients undergoing coronary artery bypass graft surgery as compared with the lowest-volume hospital as a function of baseline probability of death. (Patient baseline risk of death: large circle = 0.5%; square = 1%; triangle = 2%; small circle = 5%; diamond = 7.5%.)

View larger version (9K): [in this window] [in a new window]   Fig 3. Relative odds of death of patients undergoing coronary artery bypass grafting surgery as compared with the lowest-volume hospital as a function of baseline probability of death. (Patient baseline risk of death: circle = 25%; square = 35%; triangle = 50%.)

	Comment

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

It is unclear why among patients with a mortality risk < 9% (95% of the patient sample) low-risk patients appear to benefit more than higher-risk patients from undergoing CABG surgery at high-volume centers. The conventional wisdom is that routine patients can be treated in community hospitals, whereas high-risk patients should be referred to tertiary care centers with greater expertise and higher patient volumes. One could speculate that perioperative care is more standardized and protocol-driven at high-volume centers resulting in less variation in care and improved outcomes. Perhaps low-risk patients are more likely to benefit from clinical pathways simply because their care is more routine than that of higher-risk patients whose clinical course is more likely to fall outside of clinical pathways.

The results of the study by Nallamothu and colleagues [16] suggest the opposite findings, namely that moderate-risk and high-risk patients benefit more than low-risk patients from having CABG surgery at high-volume centers. In these authors’ study, they compared the mortality rates of low-volume and high-volume hospitals for minimal, low, moderate, high, and severe-risk patients. However, because the CABG prediction model used to assign patients to different risk groups was based on administrative data, some of the patients may not have been assigned to the correct risk group. One of the most important limitations of administrative data sets for risk adjustment is that they do not distinguish between comorbidities, medical problems that existed before hospitalization and complications that occurred during the hospitalization. For example, a complication of care that is incorrectly identified as comorbidity may spuriously increase a patient’s predicted mortality. Therefore, in this study, it is not possible to know if the patients at low-volume hospitals had the same level of risk as the patients at high-volume hospitals within each risk strata.

Despite the extensive body of research on the subject of the relationship between volume and mortality, the question of whether higher volumes result in lower mortality (practice makes perfect hypothesis) or lower mortality leads to higher patient volumes through increased referrals (selective referral hypothesis) remains unanswered [2]. A similar question may be raised with respect to the interaction between volume and mortality. Is it possible that low risk patients are being triaged to lower quality hospitals and higher risk patients are selectively referred to higher quality hospitals, because referring physicians believe that the patients who are more ill need to be treated at better hospitals? Addressing this question is beyond the scope of this study. However, the answer to this question is important for translating these results into policy.

The nature of the structures and processes resulting in superior outcomes at high-volume centers [5] is also left undefined by this and other studies investigating volume-outcome relationships. Some groups have advocated evidenced-based hospital referrals based simply on hospital volume as a means of improving outcomes [6, 7]. However, such a policy could have important indirect effects. This could create incentives for some hospitals near the volume threshold to operate on patients who may have otherwise been managed nonoperatively so as to qualify as a high-volume center [7]. Regionalization of services could reduce competition and lower quality of care [6]. Regionalization could also result in loss of specialists and limit patient access to specialty care [6]. Finally, a policy of regionalizing CABG surgery based on volume criteria alone could result in the closing of some high-quality centers that have low patient volumes. Volume, by itself, does not necessarily lead to better outcomes. More likely, "It is a proxy measure for other factors that affect care" [5]. The existence of a wide variation in processes of care in the clinical setting is well recognized [28]. For CABG surgery, the differences in structure and processes of care between low-volume and high-volume centers could be studied in order to identify the best practices, which could then be adapted to individual institutions. This approach avoids some of the problems inherent in evidence-based referrals using volume as a quality proxy. Because there may be a much greater outcome differential between low-volume and high-volume hospitals for low-risk patients versus high-risk patients, it may be very useful to uncover the best practices responsible for producing superior outcomes in low-risk patients at high-volume hospitals.

There are several potential limitations to this study. (1) In-hospital mortality was used because 30-day mortality data were not available in the CSRS database. In-hospital mortality is potentially biased by variation in length of stays across institutions [2]. However, the 30-day mortality rate also may be biased, because it includes deaths unrelated to CABG surgery and will not include patient deaths whose hospital length of stay is longer than 30 days [12]. (2) Although this study assessed the impact of hospital volume on mortality, mortality is only one of several indirect measures of quality of care. Quality of care, as defined by The Institute of Medicine, is the "degree to which health services for individuals and populations increases the likelihood of desired health outcomes..." [29]. Although complications of care can result in significant patient morbidity, these were not included in our analysis. Unlike mortality, complications are not always recorded accurately [30], and the accuracy of complication data are difficult to verify through database audits. Moreover, quality of care also encompasses the issue of whether the care rendered is appropriate [31]. Future outcome studies should also consider evaluating appropriateness of the care delivered. Finally, the hospitals in NYS may not be representative of the hospitals performing CABG surgery nationwide. With the release of CABG surgery "report cards" in NYS to the public beginning in 1991, there has been an "exodus of low-volume surgeons with high–risk-adjusted mortality" [13]. However, the elimination of some of the lowest-volume providers would be expected to bias the results in this analysis to show less of a volume-outcome relationship. Therefore, perhaps we would expect to see a more substantial volume-outcome effect in other regions that do not have similar outcome reporting programs in place.

This study has several strengths. By using the CSRS database, which contains prospectively collected clinical data, our findings are not subject to the limitations inherent to analyses based on administrative data. Risk adjustment using administrative data are complicated by the fact that most administrative databases do not distinguish complications of care from comorbidities present before hospital admission [19] and may not include all patient diagnoses. For CABG surgery in NYS, Hannan and colleagues [32] have shown that a prediction model based on the CSRS database exhibited better discrimination than a model based on an administrative database (ie, the Statewide Planning and Research Cooperative System database.

This study also presents an innovative approach to modeling the interaction between patient risk and hospital volume. Although the conceptualization of the statistical model is relatively straightforward, implementation of the model involved programming the likelihood function, because conventional statistical programs are not able to provide maximum likelihood estimates of the variables for this model.

We believe that our study is the first to evaluate the interaction between hospital volume and patient risk in a clinical database. There is no reason to believe, a priori, that all patients undergoing CABG surgery would benefit equally from being treated at high-volume centers. We constructed a statistical model that allowed us to assess the interaction between hospital volume and aggregate patient risk in patients who had CABG surgery. This approach could also be extended to assess the impact of patient risk on the volume-mortality relationship for other surgical procedures, as well as other nonoperative therapies.

In conclusion, this study suggests that low-risk patients benefit more than high-risk patients from having their surgery at high-volume centers instead of low-volume centers. Before generalizing this finding to areas outside of NYS, this study should be repeated using other regional and national population-based clinical databases. If this finding is validated in other settings, it may have important policy implications. The practice of referring low-risk patients to community hospitals with low operative volumes, and selectively referring only high-risk patients to high-volume centers may need to be reevaluated. However, volume is an imperfect proxy for quality of care and should not be used as the sole basis for regionalizing care. Instead, the information generated from this analysis and others like it should be used to help guide quality improvement efforts. Because low-risk patients stand to benefit the most by having CABG surgery in high-volume centers, future studies should focus on identifying the specific processes of care at high-volume centers that lead to improved outcomes in this subset of patients. Then these processes could be adapted to low-volume and intermediate-volume centers performing CABG surgery. We also believe that the efforts of the Leapfrog group to impose volume standards based on the evidence of a volume-outcome relationship in studies such as this one should serve as a call to arms to the medical community to lead this country toward the development of a national, population-based system to measure health care outcomes, instead of relying on imperfect volume cutoffs to identify high-quality care.

	Acknowledgments

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 
This project was supported by a Research Career Development Award to Dr Glance from the Agency for Healthcare Research and Quality (K08 HS11295).

	References

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 

1. Birkmeyer J.D., Siewers A.E., Finlayson E.V., et al. Hospital volume and surgical mortality in the United States. N Engl J Med 2002;346:1128-1144.[Abstract/Free Full Text]
2. Hannan E.L., O’Donnell J.F., Kilburn H., Jr, Bernard H.R., Yazici A. Investigation of the relationship between volume and mortality for surgical procedures performed in New York State hospitals. JAMA 1989;262:503-510.[Abstract/Free Full Text]
3. Hannan E.L., Kilburn H., Jr, O’Donnell J.F., et al. A longitudinal analysis of the relationship between in-hospital mortality in New York State and the volume of abdominal aortic aneurysm surgeries performed. Health Serv Res 1992;27(4):517-542.[Medline]
4. Hannan E.L., Popp A.J., Tranmer B., Fuestel P., Waldman J., Shah D. Relationship between provider volume and mortality for carotid endarterectomies in New York State. Stroke 1998;29(11):2292-2297.[Abstract/Free Full Text]
5. Hewitt M. Interpreting the volume-outcome relationship in the context of health care quality. 1. 2000. Institute of Medicine
6. Dudley R.A., Johansen K.L., Brand R., Rennie D.J., Milstein A. Selective referral to high-volume hospitals: estimating potentially avoidable deaths. JAMA 2000;283:1159-1166.[Abstract/Free Full Text]
7. Birkmeyer JD, Birkmeyer CM, Wennberger DE, Young M. Leapfrog safety standards: the potential benefits of universal adoption. website;2000
8. Luft H.S., Bunker J.P., Enthoven A.C. Should operations be regionalized? The empirical relation between surgical volume and mortality. N Engl J Med 1979;301:1364-1369.[Abstract]
9. Luft H.S., Hunt S.S., Maerki S.C. The volume-outcome relationship: practice makes perfect or selective referral patterns?. Health Serv Res 1987;22(2):157-182.[Medline]
10. Hughes R.G., Hunt S.S., Luft H.S. Effects of surgeon volume and hospital volume on quality of care in hospitals. Med Care 1987;25(6):489-503.[Medline]
11. Showstack J.A., Rosenfeld K.E., Garnick D.W., Luft H.S., Schaffarzick R.W., Fowles J. Association of volume with outcome of coronary artery bypass graft surgery. Scheduled vs nonscheduled operations. JAMA 1987;257:785-789.[Abstract/Free Full Text]
12. Hannan E.L., Kilburn H., Jr, Bernard H., O’Donnell J.F., Lukacik G., Shields E.P. Coronary artery bypass surgery: the relationship between in hospital mortality rate and surgical volume after controlling for clinical risk factors. Med Care 1991;29(11):1094-1107.[Medline]
13. Hannan E.L., Siu A.L., Kumar D., Kilburn H., Jr, Chassin M.R. The decline in coronary artery bypass graft surgery mortality in New York State. The role of surgeon volume. JAMA 1995;273:209-213.[Abstract/Free Full Text]
14. Sollano J.A., Gelijns A.C., Moskowitz A.J., et al. Volume-outcome relationships in cardiovascular operations. New York State, 1990–1995. J Thorac Cardiovasc Surg 1999;117:419-428.[Abstract/Free Full Text]
15. Shroyer A.L., Marshall G., Warner B.A., et al. No continuous relationship between Veterans Affairs hospital coronary artery bypass grafting surgical volume and operative mortality. Ann Thorac Surg 1996;61:17-20.[Abstract/Free Full Text]
16. Nallamothu B.K., Saint S., Ramsey S.D., Hofer T.P., Vijan S., Eagle K.A. The role of hospital volume in coronary artery bypass grafting: is more always better?. J Am Coll Cardiol 2001;38:1923-1930.[Abstract/Free Full Text]
17. Hannan E.L., Kilburn H., Jr, Racz M., Shields E., Chassin M.R. Improving the outcomes of coronary artery bypass surgery in New York State. JAMA 1994;271:761-766.[Abstract/Free Full Text]
18. Hannan E.L., Siu A.L., Kumar D., Kilburn H., Chassin M.R. The decline in coronary artery bypass graft surgery mortality in New York State. The role of surgeon volume. JAMA 1995;273:209-213.
19. Iezzoni L.I. Assessing quality using administrative data. Ann Intern Med 1997;127(8 Pt 2):666-674.[Abstract/Free Full Text]
20. Clark R.E., Crawford F.A., Anderson R.P., Grover F.L., Kouchoukos N.T., Waldhausen J.A. Outcome as a function of annual coronary artery bypass graft volume. Ann Thorac Surg 1996;61:21-26.[Abstract/Free Full Text]
21. Hannan E.L., Racz M., Kavey R.E., Quaegebeur J.M., Williams R. Pediatric cardiac surgery: the effect of hospital and surgeon volume on in-hospital mortality. Pediatrics 1998;101(6):963-969.[Abstract/Free Full Text]
22. New York State Department of Health. Coronary artery bypass surgery in New York state: 1994–1996. NYS Department of Health, 1998
23. Glance L.G., Osler T.M. Comparing outcomes of coronary artery bypass surgery: is the New York cardiac surgery reporting system model sensitive to changes in case mix?. Crit Care Med 2001;29:2090-2096.[Medline]
24. Bach P.B., Cramer L.D., Schrag D., Downey R.J., Gelfand S.E., Begg C.B. The influence of hospital volume on survival after resection for lung cancer. N Engl J Med 2001;345:181-188.[Abstract/Free Full Text]
25. Gould W., Sribney W. Maximum likelihood estimation with STATA. College Station, TX: Stata Press, 1999.
26. Hadorn D.D., Keeler E., Rogers W.H., Brook R.H. Assessing the performance of mortality prediction models. Santa Monica: RAND/UCLA/Harvard Center for Health Care Financing Policy Research, 1993.
27. Hosmer D.W., Lemeshow S. Applied logistic regression, 2nd ed New York: Wiley-Interscience Publication, 2000.
28. Blumenthal D., Epstein A.M. Quality of health care, part 6: the role of physicians in the future of quality management. N Engl J Med 1996;335:1328-1331.[Free Full Text]
29. Medicare: a strategy for quality assurance. Washington, DC: National Academy Press, 1990.
30. Silber J.H., Rosenbaum P.R., Schwartz J.S., Ross R.N., Williams S.V. Evaluation of the complication rate as a measure of quality of care in coronary artery bypass graft surgery. JAMA 1995;274:317-323.[Abstract/Free Full Text]
31. Blumenthal D. Part 1: quality of care—what is it?. N Engl J Med 1996;335:891-894.[Free Full Text]
32. Hannan E.L., Kilburn H., Jr, Lindsey M.L., Lewis R. Clinical versus administrative data bases for CABG surgery. Does it matter?. Med Care 1992;30(10):892-907.[Medline]

This article has been cited by other articles:

				L. G. Glance, T. M. Osler, D. B. Mukamel, and A. W. Dick Estimating the potential impact of regionalizing health care delivery based on volume standards versus risk-adjusted mortality rate Int. J. Qual. Health Care, August 1, 2007; 19(4): 195 - 202. [Abstract] [Full Text] [PDF]

				E. Losina, E. A. Wright, C. L. Kessler, J. A. Barrett, A. H. Fossel, A. H. Creel, N. N. Mahomed, J. A. Baron, and J. N. Katz Neighborhoods Matter: Use of Hospitals With Worse Outcomes Following Total Knee Replacement by Patients From Vulnerable Populations Arch Intern Med, January 22, 2007; 167(2): 182 - 186. [Abstract] [Full Text] [PDF]

				J. H. Liu, D. S. Zingmond, M. L. McGory, N. F. SooHoo, S. L. Ettner, R. H. Brook, and C. Y. Ko Disparities in the utilization of high-volume hospitals for complex surgery. JAMA, October 25, 2006; 296(16): 1973 - 1980. [Abstract] [Full Text] [PDF]

				K. F. Welke, M. J. Barnett, M. S. Vaughan Sarrazin, and G. E. Rosenthal Limitations of Hospital Volume as a Measure of Quality of Care for Coronary Artery Bypass Graft Surgery Ann. Thorac. Surg., December 1, 2005; 80(6): 2114 - 2119. [Abstract] [Full Text] [PDF]

				B. K. Nallamothu, K. A. Eagle, V. A. Ferraris, and R. M. Sade Should Coronary Artery Bypass Grafting Be Regionalized? Ann. Thorac. Surg., November 1, 2005; 80(5): 1572 - 1581. [Full Text] [PDF]

				R. H. Jones The year in cardiovascular surgery J. Am. Coll. Cardiol., May 5, 2004; 43(9): 1706 - 1714. [Full Text] [PDF]

This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Personal Folders Download to citation manager Permission Requests Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Glance, L. G. Articles by Osler, T. M. Search for Related Content PubMed PubMed Citation Articles by Glance, L. G. Articles by Osler, T. M. Related Collections Coronary disease