FREE NEJM E-TOC    HOME   |   SUBSCRIBE   |   CURRENT ISSUE   |   PAST ISSUES   |   COLLECTIONS   |   Search Term  Advanced Search

Sign in | Get NEJM's E-Mail Table of Contents — Free | Subscribe

Previous Volume 345:181-188 July 19, 2001 Number 3 Next

Abstract PDF Add to Personal Archive Add to Citation Manager Notify a Friend E-mail When Cited PubMed Citation

ABSTRACT

Background Among patients who have undergone high-risk operations for cancer, postoperative mortality rates are often lower at hospitals where more of these procedures are performed. We undertook a population-based study to estimate the extent to which the number of procedures performed at a hospital (hospital volume) is associated with survival after resection for lung cancer.

Methods We studied patients 65 years old or older who received a diagnosis of stage I, II, or IIIA non–small-cell lung cancer between 1985 and 1996, resided in 1 of the 10 study areas covered by the Surveillance, Epidemiology, and End Results Program, and underwent surgery at a hospital that participates in the Nationwide Inpatient Sample (2118 patients and 76 hospitals).

Results The volume of procedures at the hospital was positively associated with the survival of patients (P<0.001). Five years after surgery, 44 percent of patients who underwent operations at the hospitals with the highest volume were alive, as compared with 33 percent of those who underwent operations at the hospitals with the lowest volume. Patients at the highest-volume hospitals also had lower rates of postoperative complications (20 percent vs. 44 percent) and lower 30-day mortality (3 percent vs. 6 percent) than those at the lowest-volume hospitals.

Conclusions Patients who undergo resection for lung cancer at hospitals that perform large numbers of such procedures are likely to survive longer than patients who have such surgery at hospitals with a low volume of lung-resection procedures.

In this study of the relation between hospital volume and outcome after surgery for lung cancer, we examined the rates of survival and postoperative complications in both teaching and nonteaching hospitals.^14,15

Methods

Sources of Data

            The Surveillance, Epidemiology, and End Results Program and Medicare

Patients were identified from the Surveillance, Epidemiology, and Ends Results (SEER) Cancer Registries, which have been linked to data on Medicare hospitalizations. The SEER data base contains detailed information on all newly diagnosed cases of cancer in five metropolitan areas (San Francisco, Oakland, and San Jose, California; Detroit; Atlanta; Seattle; and Los Angeles County) and five states (Connecticut, Utah, New Mexico, Iowa, and Hawaii).¹⁶ The Medicare data base contains information on hospital-discharge diagnoses from 1984 onward and information on the dates of death of the participants who have died.

We determined from the SEER data base the following characteristics of patients: sex, race, age at diagnosis, and stage of cancer (patients with unknown nodal status were excluded). We assigned a socioeconomic status to patients on the basis of the median income in the ZIP Code of residence (obtained from the 1990 U.S. Census). We used the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM)¹⁷ discharge codes from the admission during which surgery was performed to determine both the extent of chronic illness as measured by the Romano modification¹⁸ of the Charlson comorbidity index¹⁹ and the operation that was performed: partial lobectomy (wedge or segmental resection, ICD-9-CM code 32.2 or 32.3), lobectomy (ICD-9-CM code 32.1 or 32.4), or pneumonectomy (ICD-9-CM code 32.5 or 32.6).

            The Nationwide Inpatient Sample

Hospitals were identified from the Nationwide Inpatient Sample (NIS).²⁰ The NIS consists of a stratified random sample of 1012 hospitals in 22 states; data from 5 of these states (California, Connecticut, Iowa, Utah, and Washington) overlap with those from SEER regions and include American Hospital Association (AHA) hospital identifiers that make linkage between the two data bases possible. The NIS contains complete data on discharges from each participating hospital and reports the teaching status and type of location (urban or nonurban) of the hospital. We assigned to each hospital the characteristics and the annual volume of procedures that were documented for the 1997 discharges in the NIS. To calculate the volume of procedures, we counted the number of patients whose records indicated a diagnosis of lung cancer (principal NIS diagnosis code, 19) and the performance of lung resection (principal NIS procedure code, 36).

Study Patients

We analyzed data on 2118 patients in the SEER–Medicare data base who received a diagnosis of lung cancer between 1985 and 1996 and who underwent resection for lung cancer at 1 of 76 hospitals included in the NIS for 1997. These patients were drawn from the 12,921 patients 65 years old or older who resided in 1 of the 10 areas covered by the SEER data base and who met the following requirements: a diagnosis of primary cancer of the lung (International Classification of Diseases for Oncology, 2nd edition ²¹ [ICD-O-2] codes 34.0 through 34.9) between 1985 and 1996, with non–small-cell histologic features (ICD-O-2 morphology [M] codes other than 8000, 8002, 8041 through 8045, 8240, 8241, 8244, and 8246); stage I, II, or IIIA disease according to the criteria of the American Joint Committee on Cancer Staging^22,23; indemnity insurance through the Medicare program; and lung resection within four months after diagnosis. The hospitals were drawn from the pool of 1012 hospitals that participate in the NIS, in 423 of which at least one operation for lung cancer was performed in 1997. The patients and hospitals we studied had characteristics similar to those in the parent data bases (Table 1), with the exception that more hospitals in our study were investor-owned rather than not-for-profit.

View this table: [in this window] [in a new window]   Table 1. Characteristics of the Patients Identified through the SEER–Medicare Data Base and of the Hospitals Identified from the Nationwide Inpatient Sample That Were Included in or Excluded from the Study.

 
Analyses of the Entire SEER–Medicare Cohort

The principal advantage of using the NIS to ascertain the volume of procedures is that it contains a count of the actual number of lung-cancer operations performed during one year at each hospital, but major disadvantages are that only a small proportion of the patients covered by the SEER–Medicare data base underwent their procedures at a facility that participated in the NIS and that the 1997 NIS data do not cover the same period as the SEER–Medicare data we used. We chose to use the NIS data because they allowed us to express results in terms of the actual volume of procedures. We also repeated all the analyses using the entire SEER–Medicare cohort, and when relevant, we report summary statistics and P values from these analyses, for which the characteristics of the hospitals were derived from the 1993 AHA data base.

Outcomes after Resection for Lung Cancer

We assessed survival and the frequency of postoperative complications after resection for lung cancer. We evaluated the absolute duration of survival from the date of hospitalization for surgery to the date of death as reported to Medicare, as well as the likelihood of survival at 30 days and 2 years. Records of deaths are complete through December 31, 1994, for patients with lung cancer diagnosed before 1991 and through December 31, 1998, for those with lung cancer diagnosed between 1991 and 1996. The follow-up for all patients was at least two years. For the patients who were still alive, data were censored as of these dates.

The frequency of postoperative complications and the length of stay after the admission for surgery were determined on the basis of claims in the Medicare file.^24,25 We separated serious acute complications into surgical and pulmonary complications. Surgical complications included pneumothorax, pulmonary collapse, and accidental puncture, damage, or contamination of the surgical site (ICD-9-CM codes 512.0, 512.1, 512.8, 518, 518.1, 998.2 through 998.81, E870.0, and E871.0); pulmonary complications included new-onset pulmonary insufficiency and respiratory arrest (ICD-9-CM codes 518.5, 518.81, 518.82, 799.1, and 997.3). This group of diagnoses is distinct from those used to calculate the Romano–Charlson index, which we used to measure comorbidity. The latter index focuses on chronic illnesses such as congestive heart failure (ICD-9-CM codes 402 through 404), liver disease (ICD-9-CM code 572), and chronic obstructive pulmonary disease (ICD-9-CM codes 415.0, 416.8, 416.9, 491 through 494, and 496).

Statistical Analysis

The results are presented according to category of the hospital's volume of procedures exclusively for purposes of illustration. In all the statistical tests, the volume was considered as a continuous measure, and variances were adjusted to correct for the fact that these data include multiple observations from some hospitals. Categorical outcomes (30-day survival, 2-year survival, presence or absence of complications, and characteristics of the hospitals and the patients) were assessed by means of a modified version of the Mantel–Haenszel test for trend in all unadjusted analyses and by a method involving generalized estimating equations for all analyses that included other covariates.^26,27,28 The association between the length of stay and the volume of procedures was assessed by means of the rank-correlation test. Survival data were assessed by means of a Cox proportional-hazards model in which we adjusted the variance using the Robust macro developed for use with SAS software (SAS Institute, Cary, N.C.).²⁹ All analyses were performed with SAS software, version 8.0. All P values are two-sided. The categorizations of the covariates included in the models are reflected in Table 2, and the particular covariates included in each model are specified in Table 3 and Table 4.

View this table: [in this window] [in a new window]   Table 2. Characteristics of the 76 Hospitals Studied, According to the Volume of Lung-Cancer Resections Performed during 1997, and of 2118 Medicare Beneficiaries with Stage I, II, or IIIA Non–Small-Cell Lung Cancer Who Underwent Lung-Cancer Resection between 1985 and 1996 at One of These Hospitals.

 

View this table: [in this window] [in a new window]   Table 3. Relation between the Volume of Operations and the Outcome of Operations for Primary Non–Small-Cell Lung Cancer.

 

View this table: [in this window] [in a new window]   Table 4. Relation between the Volume of Procedures, Complications, and Survival after Operations for Primary Lung Cancer.

 
Results

Characteristics of the Hospitals

For the purpose of illustration, the hospitals are categorized according to the number of lung-cancer operations performed in 1997 (Table 2). In nearly half the hospitals (34 of 76), fewer than nine lung-cancer operations were performed in that year. In contrast, at 16 of the 76 hospitals (21 percent) 20 to 66 procedures were performed in 1997, and at 2 hospitals (3 percent) 67 to 100 were performed. Hospitals in which higher numbers of lung-cancer operations were performed tended to be teaching hospitals in urban locations. There were no significant trends that associated the volume of procedures with the characteristics of the patients listed in Table 2.

The Relation between Volume and Outcome

The 30-day, 2-year, and overall rates of survival were all significantly associated with the volume of procedures (Table 3). The most important difference between high-volume and low-volume hospitals was in overall survival. The rate of survival at five years was 44 percent among patients who underwent resection at either of the two hospitals with the highest volume of procedures and 33 percent among patients who had surgery at a hospital in which fewer than nine operations were performed in 1997. An analysis of the entire SEER–Medicare cohort demonstrated a significant but more limited difference (7 percentage points; P<0.001) in five-year survival between the hospitals with the lowest volume (36 percent) and those with the highest volume (43 percent). We also observed that for each increment in the procedure-volume category, overall survival improved both in absolute terms (Figure 1) and within analyses that adjusted for other factors that influence survival (Table 3).

View larger version (16K): [in this window] [in a new window]   Figure 1. Survival of Medicare Beneficiaries 65 Years of Age or Older Who Received a Diagnosis of Stage I, II, or IIIA Non–Small-Cell Lung Cancer between 1985 and 1996 and Underwent Resection for Lung Cancer, According to the Volume of Such Procedures Performed Annually at the Hospitals Where the Patients Were Treated. Procedure volume was determined on the basis of data from the 1997 Nationwide Inpatient Sample. A total of 2118 patients were included in the analysis.

 
The Relation among Teaching Status, Volume, and Survival

Overall, the rate of five-year survival among patients who underwent surgery at a teaching hospital was 42 percent, as compared with 34 percent among those at nonteaching hospitals (P<0.001). After stratifying hospitals according to their volume of procedures, we also observed a relation between the rate of survival and the volume of procedures in teaching hospitals in particular (Table 3).

Postoperative Complications

We found a strong negative association between the volume of the procedures and the likelihood of either operative (P<0.001) or pulmonary (P=0.002) complications (Table 4), with complication rates that were twice as high at hospitals with the lowest volume as at those with the highest volume. We also observed a relation between longer hospital stays and hospitals with lower volume (Table 4). Although this latter association is unlikely to be clinically significant, it supports our hypothesis that the postoperative course at hospitals with lower volumes is, on average, more complex. The primary association between hospital volume and survival was only marginally altered when we simultaneously considered the effect of complications on survival through either stratified or multivariate analyses (Table 4). In other words, these results are not consistent with the hypothesis that differences in complication rates are the chief explanation for the relation between volume and survival.

Discussion

We found a rate of survival at five years that was higher by 11 percentage points (44 percent vs. 33 percent) among patients who underwent resections for lung cancer at hospitals with the highest volumes of such procedures than among those at the hospitals with the lowest volumes. Moreover, regardless of the volume of procedures, the rate of survival was better among patients who had their operations at teaching hospitals rather than nonteaching hospitals, although this finding did not confound the relation between volume and outcome.

Serious postoperative complications occurred at the hospitals with the lowest volume twice as often as at those with the highest volume (44 percent vs. 20 percent). It seemed plausible that these higher rates of complications might explain the relation between the hospital's volume of procedures and long-term survival. However, the complications we identified in the Medicare files only partially explained the association between high volume and a higher rate of overall survival. Whether a clearer picture would have emerged if we had more complete documentation of postoperative events (such as can be obtained through a review of patients' charts) remains an open question.

Our study has other limitations because of the incompleteness of the data on the hospitals and the patients included in NIS, Medicare, and the SEER data base. The hospitals included in the 1997 NIS are characterized simply as teaching or nonteaching, belying the complex array of organizational frameworks that exists. The 1997 data may also have limited relevance to patients who entered the cohort in the earlier years of our study. Incomplete data on adjuvant treatment and miscoded data on coexisting conditions (both potential problems with Medicare records) are also matters of concern. The lack of data on adjuvant treatment, however, should not have affected our results for two reasons. First, randomized trials have not demonstrated a consistent survival benefit for patients with stage I or stage II disease — a category that includes 89 percent of the patients in our study.^30,31 Second, in a separate analysis of patients with early-stage disease, the results were similar to those in the cohort as a whole (data not shown).³²

As for miscoding or incomplete coding of coexisting conditions,³³ there were no discernible differences between the groups of patients in the characteristics we measured (Table 2), which lessens the likelihood that unobserved differences in these factors are an important source of bias. The staging information in the SEER data base may also have biased our results, especially because the sampling of mediastinal lymph nodes may be more thorough in hospitals with high volumes of procedures than in those with low volumes. However, among patients with stage IA (T1N0M0) disease who had undergone lobectomy (17 percent of the cohort), the relation between the volume of procedures and five-year survival was of the same magnitude as that in the entire cohort (data not shown). In this subgroup of patients, we know that the stage was probably ascertained correctly. At least one N1 node was examined, and the likelihood of a "skip" metastasis to the N2 node is very low (4 to 8 percent in most reports).^34,35

How should we react to these findings? Survival might be improved by identifying the variations in perioperative and intraoperative care that are responsible for the differences we found. A study in which an association between volume and outcome was identified in the care of patients with myocardial infarction found that differential use of aspirin, beta-blockers, and other therapies accounted for some of the differences in outcome that appeared to be linked to the volume of procedures.³⁶ An alternative response to our results would be to limit the performance of resections for lung cancer to centers with better outcomes. This approach has been endorsed by a number of investigators,^37,38,39,40 as well as in a recent report from the Institute of Medicine on the quality of care for cancer in the United States.⁴¹

We hesitate to advocate this latter approach for three reasons. First, shifting surgical patients to a few institutions with high volumes of procedures may have unintended effects on the quality of care both at those institutions, which would face substantial increases in the volume of patients, and at the institutions with low volumes, where the care of the remaining patients might suffer. Second, increased volume and the teaching status of the hospital appear to be markers of improved outcome, but these characteristics do not, in isolation, identify individual high-quality hospitals.⁴² Finally, the association we observed between the volume of procedures and postoperative complications hints at the possibility that rectifiable variations in care may account for differences in outcome. Targeting these variations may be the best way to achieve a durable improvement in the treatment of patients with early-stage lung cancer.

Supported by a grant (RO1-CA-090226, to Dr. Bach) from the National Cancer Institute.

We are indebted to the staffs of the Applied Research Program, National Cancer Institute; the Office of Information Services and the Office of Strategic Planning, Health Care Financing Administration; Information Management Services; the SEER Program tumor registries that created the SEER–Medicare data base; and the Healthcare Cost and Utilization Project, 1988 through 1997, that created the Nationwide Inpatient Sample; to Larry Kaiser and Joan Warren for their thoughtful input; and to Sheryl Rifas-Shiman and Sofia Yakren for their dedicated assistance. The interpretation and reporting of the data are the sole responsibility of the authors.

Source Information

From the Health Outcomes Research Group, the Departments of Epidemiology and Biostatistics (P.B.B., L.D.C., D.S., S.E.G., C.B.B.), Medicine (P.B.B., D.S.), and Surgery (R.J.D.), Memorial Sloan-Kettering Cancer Center, New York.

Address reprint requests to Dr. Bach at the Health Outcomes Research Group, Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, 1275 York Ave., Box 221, New York, NY 10021.

References

1. Begg CB, Cramer LD, Hoskins WJ, Brennan MF. Impact of hospital volume on operative mortality for major cancer surgery. JAMA 1998;280:1747-1751. [Free Full Text]
2. Sosa JA, Bowman HM, Gordon TA, et al. Importance of hospital volume in the overall management of pancreatic cancer. Ann Surg 1998;228:429-438. [CrossRef][Web of Science][Medline]
3. Birkmeyer JD, Warshaw AL, Finlayson SR, Grove MR, Tosteson AN. Relationship between hospital volume and late survival after pancreaticoduodenectomy. Surgery 1999;126:178-183. [Web of Science][Medline]
4. Schrag D, Cramer LD, Bach PB, Cohen AM, Warren JL, Begg CB. Influence of hospital procedure volume on outcomes following surgery for colon cancer. JAMA 2000;284:3028-3035. [Free Full Text]
5. Hannan EL, O'Donnell JF, Kilburn H Jr, Bernard HR, Yazici A. Investigation of the relationship between volume and mortality for surgical procedures performed in New York State hospitals. JAMA 1989;262:503-510. [Free Full Text]
6. Hannan EL, Popp AJ, Tranmer B, Fuestel P, Waldman J, Shah D. Relationship between provider volume and mortality for carotid endarterectomies in New York State. Stroke 1998;29:2292-2297. [Free Full Text]
7. Hughes RG, Hunt SS, Luft HS. Effects of surgeon volume and hospital volume on quality of care in hospitals. Med Care 1987;25:489-503. [CrossRef][Web of Science][Medline]
8. Edwards EB, Roberts JP, McBride MA, Schulak JA, Hunsicker LG. The effect of the volume of procedures at transplantation centers on mortality after liver transplantation. N Engl J Med 1999;341:2049-2053. [Free Full Text]
9. Roohan PJ, Bickell NA, Baptiste MS, Therriault GD, Ferrara EP, Siu AL. Hospital volume differences and five-year survival from breast cancer. Am J Public Health 1998;88:454-457. [Free Full Text]
10. Yao SL, Lu-Yao G. Population-based study of relationships between hospital volume of prostatectomies, patient outcomes, and length of hospital stay. J Natl Cancer Inst 1999;91:1950-1956. [Free Full Text]
11. Ellison LM, Heaney JA, Birkmeyer JD. The effect of hospital volume on mortality and resource use after radical prostatectomy. J Urol 2000;163:867-869. [CrossRef][Web of Science][Medline]
12. Khuri SF, Daley J, Henderson W, et al. Relation of surgical volume to outcome in eight common operations: results from the VA National Surgical Quality Improvement Program. Ann Surg 1999;230:414-429. [CrossRef][Web of Science][Medline]
13. Romano PS, Mark DH. Patient and hospital characteristics related to in-hospital mortality after lung cancer resection. Chest 1992;101:1332-1337. [Free Full Text]
14. Rosenthal GE, Harper DL, Quinn LM, Cooper GS. Severity-adjusted mortality and length of stay in teaching and nonteaching hospitals: results of a regional study. JAMA 1997;278:485-490. [Free Full Text]
15. Holm T, Johansson H, Cedermark B, Ekelund G, Rutqvist L-E. Influence of hospital- and surgeon-related factors on outcome after treatment of rectal cancer with or without preoperative radiotherapy. Br J Surg 1997;84:657-663. [CrossRef][Web of Science][Medline]
16. Potosky AL, Riley GF, Lubitz JD, Mentnech RM, Kessler LG. Potential for cancer related health services research using a linked Medicare-tumor registry database. Med Care 1993;31:732-748. [Web of Science][Medline]
17. 1999 Hospital & payor ICD-9-CM: international classification of diseases, 9th rev., clinical modification. 5th ed. Salt Lake City: Medicode, 1998.
18. Romano PS, Roos LL, Jollis JG. Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol 1993;46:1075-1079. [CrossRef][Web of Science][Medline]
19. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373-383. [CrossRef][Web of Science][Medline]
20. Best AE. Secondary data bases and their use in outcomes research:a review of the Area Resource File and the Healthcare Cost and Utilization Project. J Med Syst 1999;23:175-181. [CrossRef][Medline]
21. Percy C, Van Holten V, Muir C, eds. International classification of diseases for oncology. 2nd ed. Geneva: World Health Organization, 1990.
22. Mountain CF. A new international staging system for lung cancer. Chest 1986;89:Suppl:225S-233S. [Free Full Text]
23. Mountain CF. Revisions in the International System for Staging Lung Cancer. Chest 1997;111:1710-1717. [Free Full Text]
24. Iezzoni LI, Daley J, Heeren T, et al. Using administrative data to screen hospitals for high complication rates. Inquiry 1994;31:40-55. [Web of Science][Medline]
25. Lawthers AG, McCarthy EP, Davis RB, Peterson LE, Palmer RH, Iezzoni LI. Identification of in-hospital complications from claims data: is it valid? Med Care 2000;38:785-795. [CrossRef][Web of Science][Medline]
26. Begg MD. Analyzing k (2x2) tables under cluster sampling. Biometrics 1999;55:302-307. [CrossRef][Web of Science][Medline]
27. Diggle PJ, Liang K-Y, Zeger SL. Analysis of longitudinal data. Oxford, England: Oxford University Press, 1995.
28. Allison PD. Logistic regression using the SAS system: theory and application. Cary, N.C.: SAS Institute, 1999:179-97.
29. White H. Maximum likelihood estimation of misspecified models. Econometrica 1982;50:1-25.
30. Ettinger DS, Cox JD, Ginsberg RJ, et al. NCCN non-small-cell lung cancer practice guidelines. Oncology (Huntingt) 1996;10:Suppl:81-111. [Medline]
31. Keller SM, Adak S, Wagner H, et al. A randomized trial of postoperative adjuvant therapy in patients with completely resected stage II or IIIA non-small-cell lung cancer. N Engl J Med 2000;343:1217-1222. [Free Full Text]
32. Rosell R, Gómez-Codina J, Camps C, et al. A randomized trial comparing preoperative chemotherapy plus surgery with surgery alone in patients with non-small-cell lung cancer. N Engl J Med 1994;330:153-158. [Free Full Text]
33. Jollis JG, Ancukiewicz M, DeLong ER, Pryor DB, Muhlbaier LH, Mark DB. Discordance of databases designed for claims payment versus clinical information systems: implications for outcomes research. Ann Intern Med 1993;119:844-850. [Free Full Text]
34. Asamura H, Nakayama H, Kondo H, Tsuchiya R, Shimosata Y, Naruke T. Lymph node involvement, recurrence, and prognosis in resected small, peripheral, non-small-cell lung carcinomas: are these carcinomas candidates for video-assisted lobectomy? J Thorac Cardiovasc Surg 1996;111:1125-1134. [Free Full Text]
35. Ishida T, Yano T, Maeda K, Kaneko S, Tateishi M, Sugimachi K. Strategy for lymphadenectomy in lung cancer three centimeters or less in diameter. Ann Thorac Surg 1990;50:708-713. [Abstract]
36. Thiemann DR, Coresh J, Oetgen WJ, Powe NR. The association between hospital volume and survival after acute myocardial infarction in elderly patients. N Engl J Med 1999;340:1640-1648. [Free Full Text]
37. Grumbach K, Anderson GM, Luft HS, Roos LL, Brook R. Regionalization of cardiac surgery in the United States and Canada: geographic access, choice, and outcomes. JAMA 1995;274:1282-1288. [Free Full Text]
38. Luft HS, Bunker JP, Enthoven AC. Should operations be regionalized? The empirical relation between surgical volume and mortality. N Engl J Med 1979;301:1364-1369. [Abstract]
39. Hillner BE, Smith TJ. Hospital volume and patient outcomes in major cancer surgery: a catalyst for quality assessment and concentration of cancer services. JAMA 1998;280:1783-1784. [Free Full Text]
40. Hillner BE, Smith TJ, Desch CE. Hospital and physician volume or specialization and outcomes in cancer treatment: importance in quality of cancer care. J Clin Oncol 2000;18:2327-2340. [Free Full Text]
41. Hewitt M, ed. Interpreting the volume-outcome relationship in the context of health care quality: workshop summary. Washington, D.C.: National Academy of Sciences, 2000.
42. Phillips KA, Luft HS. The policy implications of using hospital and physician volumes as "indicators" of quality of care in a changing health care environment. Int J Qual Health Care 1997;9:341-348. [Free Full Text]

Abstract PDF Add to Personal Archive Add to Citation Manager Notify a Friend E-mail When Cited PubMed Citation

This article has been cited by other articles:

• Brunelli, A., Charloux, A., Bolliger, C. T., Rocco, G., Sculier, J-P., Varela, G., Licker, M., Ferguson, M. K., Faivre-Finn, C., Huber, R. M., Clini, E. M., Win, T., De Ruysscher, D., Goldman, L., on behalf of the European Respiratory Society and, (2009). ERS/ESTS clinical guidelines on fitness for radical therapy in lung cancer patients (surgery and chemo-radiotherapy). Eur Respir J 34: 17-41 [Abstract] [Full Text]  
• Bach, P. B. (2009). Quality Wrapped in Volume Inside a Hospital. ANN INTERN MED 150: 729-730 [Full Text]  
• Cheung, M. C., Hamilton, K., Sherman, R., Byrne, M. M., Nguyen, D. M., Franceschi, D., Koniaris, L. G. (2009). Impact of Teaching Facility Status and High-Volume Centers on Outcomes for Lung Cancer Resection: An Examination of 13,469 Surgical Patients. Ann. Surg. Oncol. 16: 3-13 [Abstract] [Full Text]  
• Paulson, E. C., Ra, J., Armstrong, K., Wirtalla, C., Spitz, F., Kelz, R. R. (2008). Underuse of Esophagectomy as Treatment for Resectable Esophageal Cancer. Arch Surg 143: 1198-1203 [Abstract] [Full Text]  
• Kozower, B. D., Stukenborg, G. J., Lau, C. L., Jones, D. R. (2008). Measuring the Quality of Surgical Outcomes in General Thoracic Surgery: Should Surgical Volume Be Used to Direct Patient Referrals?. Ann. Thorac. Surg. 86: 1405-1408 [Full Text]  
• Lathan, C. S., Neville, B. A., Earle, C. C. (2008). Racial Composition of Hospitals: Effects on Surgery for Early-Stage Non-Small-Cell Lung Cancer. JCO 26: 4347-4352 [Abstract] [Full Text]  
• Farjah, F., Wood, D. E., Varghese, T. K. Jr, Symons, R. G., Flum, D. R. (2008). Trends in the Operative Management and Outcomes of T4 Lung Cancer. Ann. Thorac. Surg. 86: 368-374 [Abstract] [Full Text]  
• Sasako, M., Sano, T., Yamamoto, S., Kurokawa, Y., Nashimoto, A., Kurita, A., Hiratsuka, M., Tsujinaka, T., Kinoshita, T., Arai, K., Yamamura, Y., Okajima, K., the Japan Clinical Oncology Group, (2008). D2 Lymphadenectomy Alone or with Para-aortic Nodal Dissection for Gastric Cancer. NEJM 359: 453-462 [Abstract] [Full Text]  
• Ra, J., Paulson, E. C., Kucharczuk, J., Armstrong, K., Wirtalla, C., Rapaport-Kelz, R., Kaiser, L. R., Spitz, F. R. (2008). Postoperative Mortality After Esophagectomy for Cancer: Development of a Preoperative Risk Prediction Model. Ann. Surg. Oncol. 15: 1577-1584 [Abstract] [Full Text]  
• Farjah, F., Wood, D. E., Yanez, D. III, Symons, R. G., Krishnadasan, B., Flum, D. R. (2008). Temporal Trends in the Management of Potentially Resectable Lung Cancer. Ann. Thorac. Surg. 85: 1850-1856 [Abstract] [Full Text]  
• Hearld, L. R., Alexander, J. A., Fraser, I., Jiang, H. J. (2008). Review: How Do Hospital Organizational Structure and Processes Affect Quality of Care?: A Critical Review of Research Methods. Med Care Res Rev 65: 259-299 [Abstract]  
• Meguid, R. A., Brooke, B. S., Chang, D. C., Sherwood, J. T., Brock, M. V., Yang, S. C. (2008). Are Surgical Outcomes for Lung Cancer Resections Improved at Teaching Hospitals?. Ann. Thorac. Surg. 85: 1015-1025 [Abstract] [Full Text]  
• Zahn, R, Gottwik, M, Hochadel, M, Senges, J, Zeymer, U, Vogt, A, Meinertz, T, Dietz, R, Hauptmann, K E, Grube, E, Kerber, S, Sechtem, U (2008). Volume-outcome relation for contemporary percutaneous coronary interventions (PCI) in daily clinical practice: is it limited to high-risk patients? Results from the Registry of Percutaneous Coronary Interventions of the Arbeitsgemeinschaft Leitende Kardiologische Krankenhausarzte (ALKK). Heart 94: 329-335 [Abstract] [Full Text]  
• Haasbeek, C. J.A., Senan, S., Smit, E. F., Paul, M. A., Slotman, B. J., Lagerwaard, F. J. (2008). Critical Review of Nonsurgical Treatment Options for Stage I Non-Small Cell Lung Cancer. The Oncologist 13: 309-319 [Abstract] [Full Text]  
• Hershman, D. L., Buono, D., McBride, R. B., Tsai, W. Y., Joseph, K. A., Grann, V. R., Jacobson, J. S. (2008). Surgeon Characteristics and Receipt of Adjuvant Radiotherapy in Women With Breast Cancer. JNCI J Natl Cancer Inst 100: 199-206 [Abstract] [Full Text]  
• Thompson, B., Baade, P., Coory, M., Carriere, P., Fritschi, L. (2008). Patterns of Surgical Treatment for Women Diagnosed with Early Breast Cancer in Queensland. Ann. Surg. Oncol. 15: 443-451 [Abstract] [Full Text]  
• Wouters, M. W., Wijnhoven, B. P., Karim-Kos, H. E., Blaauwgeers, H. G., Stassen, L. P., Steup, W.-H., W.Tilanus, H., Tollenaar, R. A. (2008). High-Volume versus Low-Volume for Esophageal Resections for Cancer: The Essential Role of Case-Mix Adjustments based on Clinical Data. Ann. Surg. Oncol. 15: 80-87 [Abstract] [Full Text]  
• Little, A. G (2007). Risk and benefit: the eternal Yin and Yang of thoracic surgery. Thorax 62: 929-930 [Full Text]  
• Strand, T.-E., Rostad, H., Damhuis, R. A M, Norstein, J. (2007). Risk factors for 30-day mortality after resection of lung cancer and prediction of their magnitude. Thorax 62: 991-997 [Abstract] [Full Text]  
• Markman, M. (2007). Concept of Optimal Surgical Cytoreduction in Advanced Ovarian Cancer: A Brief Critique and a Call for Action. JCO 25: 4168-4170 [Full Text]  
• Hollenbeck, B. K., Hong Ji, , Zaojun Ye, , Birkmeyer, J. D. (2007). Misclassification of Hospital Volume With Surveillance, Epidemiology, and End Results Medicare Data. SURG INNOV 14: 192-198 [Abstract]  
• Colice, G. L., Shafazand, S., Griffin, J. P., Keenan, R., Bolliger, C. T. (2007). Physiologic Evaluation of the Patient With Lung Cancer Being Considered for Resectional Surgery: ACCP Evidenced-Based Clinical Practice Guidelines (2nd Edition). Chest 132: 161S-177S [Abstract] [Full Text]  
• Robinson, L. A., Ruckdeschel, J. C., Wagner, H. Jr, Stevens, C. W. (2007). Treatment of Non-small Cell Lung Cancer-Stage IIIA: ACCP Evidence-Based Clinical Practice Guidelines (2nd Edition). Chest 132: 243S-265S [Abstract] [Full Text]  
• Sundaresan, S., Langer, B., Oliver, T., Schwartz, F., Brouwers, M., Stern, H., Expert Panel on Thoracic Surgical Oncology, (2007). Standards for Thoracic Surgical Oncology in a Single-Payer Healthcare System. Ann. Thorac. Surg. 84: 693-701 [Abstract] [Full Text]  
• Raz, D. J., Zell, J. A., Ou, S-H. I., Gandara, D. R., Anton-Culver, H., Jablons, D. M. (2007). Natural History of Stage I Non-Small Cell Lung Cancer: Implications for Early Detection. Chest 132: 193-199 [Abstract] [Full Text]  
• Johnson, D. H., Rusch, V. W., Turrisi, A. T. (2007). Scalpels, Beams, Drugs, and Dreams: Challenges of Stage IIIA-N2 Non-Small-Cell Lung Cancer. JNCI J Natl Cancer Inst 99: 415-418 [Full Text]  
• Bach, P. B., Jett, J. R., Pastorino, U., Tockman, M. S., Swensen, S. J., Begg, C. B. (2007). Computed Tomography Screening and Lung Cancer Outcomes. JAMA 297: 953-961 [Abstract] [Full Text]  
• Black, W. C., Baron, J. A. (2007). CT Screening for Lung Cancer: Spiraling Into Confusion?. JAMA 297: 995-997 [Full Text]  
• Gould, M. K., Berg, C. D., Aberle, D. R., the National Lung Screening Trial Executive Commit, , Bach, P. B., Kulaga, S., Karp, I., Yee, A. J., Lynch, T. J., Silvestri, G. A., Miller, A., Markowitz, S., Miller, J. A., Lee, P., Postmus, P. E., Sutedja, T. G., Dehavenon, A., Henschke, C. I., Smith, J. P., Miettinen, O. S. (2007). CT screening for lung cancer.. NEJM 356: 743-744 [Full Text]  
• Zhang, W., Ayanian, J. Z., Zaslavsky, A. M. (2007). Patient characteristics and hospital quality for colorectal cancer surgery. Int J Qual Health Care 19: 11-20 [Abstract] [Full Text]  
• Losina, E., Wright, E. A., Kessler, C. L., Barrett, J. A., Fossel, A. H., Creel, A. H., Mahomed, N. N., Baron, J. A., Katz, J. N. (2007). Neighborhoods Matter: Use of Hospitals With Worse Outcomes Following Total Knee Replacement by Patients From Vulnerable Populations. Arch Intern Med 167: 182-186 [Abstract] [Full Text]  
• Kahn, K. L. (2007). On Referral Patterns for Patients With Breast Cancer. JCO 25: 244-246 [Full Text]  
• Hollenbeck, B. K., Dunn, R. L., Miller, D. C., Daignault, S., Taub, D. A., Wei, J. T. (2007). Volume-Based Referral for Cancer Surgery: Informing the Debate. JCO 25: 91-96 [Abstract] [Full Text]  
• Billingsley, K. G., Morris, A. M., Dominitz, J. A., Matthews, B., Dobie, S., Barlow, W., Wright, G. E., Baldwin, L.-M. (2007). Surgeon and Hospital Characteristics as Predictors of Major Adverse Outcomes Following Colon Cancer Surgery: Understanding the Volume-Outcome Relationship. Arch Surg 142: 23-31 [Abstract] [Full Text]  
• Tien, H. C., Farrell, R., Macdonald, J. (2006). Preparing Canadian military surgeons for Afghanistan.. CMAJ 175: 1365-1365 [Full Text]  
• Strand, T-E, Rostad, H, Moller, B, Norstein, J (2006). Survival after resection for primary lung cancer: a population based study of 3211 resected patients. Thorax 61: 710-715 [Abstract] [Full Text]  
• Kahn, J. M., Goss, C. H., Heagerty, P. J., Kramer, A. A., O'Brien, C. R., Rubenfeld, G. D. (2006). Hospital volume and the outcomes of mechanical ventilation.. NEJM 355: 41-50 [Abstract] [Full Text]  
• Wright, G, Manser, R L, Byrnes, G, Hart, D, Campbell, D A (2006). Surgery for non-small cell lung cancer: systematic review and meta-analysis of randomised controlled trials. Thorax 61: 597-603 [Abstract] [Full Text]  
• Rostad, H., Strand, T.-E., Naalsund, A., Talleraas, O., Norstein, J. (2006). Lung cancer surgery: the first 60 days. A population-based study.. Eur. J. Cardiothorac. Surg. 29: 824-828 [Abstract] [Full Text]  
• Ferri, L. E., Law, S., Wong, K.-H., Kwok, K.-F., Wong, J. (2006). The Influence of Technical Complications on Postoperative Outcome and Survival After Esophagectomy. Ann. Surg. Oncol. 13: 557-564 [Abstract] [Full Text]  
• Lipscomb, J. (2006). Transcending the Volume-Outcome Relationship in Cancer Care. JNCI J Natl Cancer Inst 98: 151-154 [Full Text]  
• Schrag, D., Earle, C., Xu, F., Panageas, K. S., Yabroff, K. R., Bristow, R. E., Trimble, E. L., Warren, J. L. (2006). Associations Between Hospital and Surgeon Procedure Volumes and Patient Outcomes After Ovarian Cancer Resection. JNCI J Natl Cancer Inst 98: 163-171 [Abstract] [Full Text]  
• Freixinet, J. L., Julia-Serda, G., Rodriguez, P. M., Santana, N. B., de Castro, F. R., Fiuza, M. D., Lopez-Encuentra, A., Bronchogenic Carcinoma Cooperative Group of the Sp, (2006). Hospital volume: operative morbidity, mortality and survival in thoracotomy for lung cancer.: A Spanish multicenter study of 2994 cases. Eur. J. Cardiothorac. Surg. 29: 20-25 [Abstract] [Full Text]  
• Nallamothu, B. K., Eagle, K. A., Ferraris, V. A., Sade, R. M. (2005). Should Coronary Artery Bypass Grafting Be Regionalized?. Ann. Thorac. Surg. 80: 1572-1581 [Full Text]  
• Perrot, E., Guibert, B., Mulsant, P., Blandin, S., Arnaud, I., Roy, P., Geriniere, L., Souquet, P.-J. (2005). Preoperative Chemotherapy Does Not Increase Complications After Nonsmall Cell Lung Cancer Resection. Ann. Thorac. Surg. 80: 423-427 [Abstract] [Full Text]  
• Lorent, N., De Leyn, P., Lievens, Y., Verbeken, E., Nackaerts, K., Dooms, C., Van Raemdonck, D., Anrys, B., Vansteenkiste, J., The Leuven Lung Cancer Group, (2004). Long-term survival of surgically staged IIIA-N2 non-small-cell lung cancer treated with surgical combined modality approach: analysis of a 7-year prospective experience. Ann Oncol 15: 1645-1653 [Abstract] [Full Text]  
• Hansel, N. N., Merriman, B., Haponik, E. F., Diette, G. B. (2004). Hospitalizations for Tuberculosis in the United States in 2000: Predictors of In-Hospital Mortality. Chest 126: 1079-1086 [Abstract] [Full Text]  
• Ayanian, J. Z., Chrischilles, E. A., Wallace, R. B., Fletcher, R. H., Fouad, M. N., Kiefe, C. I., Harrington, D. P., Weeks, J. C., Kahn, K. L., Malin, J. L., Lipscomb, J., Potosky, A. L., Provenzale, D. T., Sandler, R. S., van Ryn, M., West, D. W. (2004). Understanding Cancer Treatment and Outcomes: The Cancer Care Outcomes Research and Surveillance Consortium. JCO 22: 2992-2996 [Full Text]  
• Humphrey, L. L., Teutsch, S., Johnson, M. (2004). Lung Cancer Screening with Sputum Cytologic Examination, Chest Radiography, and Computed Tomography: An Update for the U.S. Preventive Services Task Force. ANN INTERN MED 140: 740-753 [Abstract] [Full Text]  
• Meyerhardt, J. A., Tepper, J. E., Niedzwiecki, D., Hollis, D. R., Schrag, D., Ayanian, J. Z., O'Connell, M. J., Weeks, J. C., Mayer, R. J., Willett, C. G., MacDonald, J. S., Benson, A. B. III, Fuchs, C. S. (2004). Impact of Hospital Procedure Volume on Surgical Operation and Long-Term Outcomes in High-Risk Curatively Resected Rectal Cancer: Findings From the Intergroup 0114 Study. JCO 22: 166-174 [Abstract] [Full Text]  
• Kizer, K. W. (2003). The Volume-Outcome Conundrum. NEJM 349: 2159-2161 [Full Text]  
• Hurria, A., Kris, M. G. (2003). Management of Lung Cancer in Older Adults. CA Cancer J Clin 53: 325-341 [Abstract] [Full Text]  
• Meyerhardt, J. A., Catalano, P. J., Schrag, D., Ayanian, J. Z., Haller, D. G., Mayer, R. J., Macdonald, J. S., Benson, A. B. III, Fuchs, C. S. (2003). Association of Hospital Procedure Volume and Outcomes in Patients with Colon Cancer at High Risk for Recurrence. ANN INTERN MED 139: 649-657 [Abstract] [Full Text]  
• Panageas, K. S., Schrag, D., Riedel, E., Bach, P. B., Begg, C. B. (2003). The Effect of Clustering of Outcomes on the Association of Procedure Volume and Surgical Outcomes. ANN INTERN MED 139: 658-665 [Abstract] [Full Text]  
• Glance, L. G., Dick, A. W., Mukamel, D. B., Osler, T. M. (2003). Is the hospital volume-mortality relationship in coronary artery bypass surgery the same for low-risk versus high-risk patients?. Ann. Thorac. Surg. 76: 1155-1162 [Abstract] [Full Text]  
• Treasure, T., Utley, M., Bailey, A. (2003). Assessment of whether in-hospital mortality for lobectomy is a useful standard for the quality of lung cancer surgery: retrospective study. BMJ 327: 73- [Abstract] [Full Text]  
• Skinner, K. A., Helsper, J. T., Deapen, D., Ye, W., Sposto, R. (2003). Breast Cancer: Do Specialists Make a Difference?. Ann. Surg. Oncol. 10: 606-615 [Abstract] [Full Text]  
• Ost, D., Fein, A. M., Feinsilver, S. H. (2003). The Solitary Pulmonary Nodule. NEJM 348: 2535-2542 [Full Text]  
• Hodgson, D. C., Zhang, W., Zaslavsky, A. M., Fuchs, C. S., Wright, W. E., Ayanian, J. Z. (2003). Relation of Hospital Volume to Colostomy Rates and Survival for Patients With Rectal Cancer. JNCI J Natl Cancer Inst 95: 708-716 [Abstract] [Full Text]  
• Bennett, C. L., Somerfield, M. R., Pfister, D. G., Tomori, C., Yakren, S., Bach, P. B. (2003). Perspectives on the Value of American Society of Clinical Oncology Clinical Guidelines as Reported by Oncologists and Health Maintenance Organizations. JCO 21: 937-941 [Abstract] [Full Text]  
• Hu, J. C., Gold, K. F., Pashos, C. L., Mehta, S. S., Litwin, M. S. (2003). Role of Surgeon Volume in Radical Prostatectomy Outcomes. JCO 21: 401-405 [Abstract] [Full Text]  
• Mahadevia, P. J., Fleisher, L. A., Frick, K. D., Eng, J., Goodman, S. N., Powe, N. R. (2003). Lung Cancer Screening With Helical Computed Tomography in Older Adult Smokers: A Decision and Cost-effectiveness Analysis. JAMA 289: 313-322 [Abstract] [Full Text]  
• Smythe, W. R. (2003). Treatment of Stage I Non-small Cell Lung Carcinoma. Chest 123: 181S-187S [Abstract] [Full Text]  
• Graham, A. N J (2002). Cardiothoracic surgeons do a good job. BMJ 324: 1455-1455 [Full Text]  
• Begg, C. B., Riedel, E. R., Bach, P. B., Kattan, M. W., Schrag, D., Warren, J. L., Scardino, P. T. (2002). Variations in Morbidity after Radical Prostatectomy. NEJM 346: 1138-1144 [Abstract] [Full Text]  
• Neugut, A. I., Grann, V. R. (2002). Referral to Medical Oncologists: Are There Barriers at the Gate?. JCO 20: 1716-1718 [Full Text]  
• Partridge, M. R (2002). Thoracic surgery in a crisis. BMJ 324: 376-377 [Full Text]  
• McNeil, B. J. (2001). Hidden Barriers to Improvement in the Quality of Care. NEJM 345: 1612-1620 [Full Text]