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Original Article |

Surgeon and Hospital Characteristics as Predictors of Major Adverse Outcomes Following Colon Cancer Surgery:  Understanding the Volume-Outcome Relationship FREE

Kevin G. Billingsley, MD; Arden M. Morris, MD, MPH; Jason A. Dominitz, MD, MHS; Barbara Matthews, MBA; Sharon Dobie, MD; William Barlow, PhD; George E. Wright, PhD; Laura-Mae Baldwin, MD, MPH
[+] Author Affiliations

Author Affiliations: Department of Surgery, Oregon Health and Science University, Portland (Dr Billingsley); Department of Surgery, University of Michigan School of Medicine, Ann Arbor (Dr Morris); and Division of Gastroenterology, VA Puget Sound Health Care System (Dr Dominitz), and Department of Family Medicine (Drs Matthews, Dobie, Wright, and Baldwin), University of Washington School of Medicine, and Cancer Research and Biostatistics (CRAB) (Dr Barlow), Seattle, Wash.


Arch Surg. 2007;142(1):23-31. doi:10.1001/archsurg.142.1.23.
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Hypothesis  Although numerous studies have demonstrated an association between surgical volume and improved outcome in cancer surgery, the specific structures and mechanisms of care that are associated with volume and lead to improved outcomes remain poorly defined. We hypothesize that there are modifiable surgeon and hospital characteristics that explain observed volume-outcome relationships.

Design  Retrospective cohort study.

Setting  Surveillance, Epidemiology, and End Results cancer registry areas.

Patients  Patients aged 66 years and older, diagnosed and surgically treated for stage I, II, or III colon cancer between 1992 and 1996 (n = 22 672).

Main Outcome Measures  Thirty-day postoperative mortality and 30-day postoperative procedural interventions, including reoperation and image-guided percutaneous procedures.

Results  Surgeon volume, but not hospital volume, is a significant predictor of postoperative procedural intervention (adjusted odds ratio for very high–volume surgeons vs low-volume surgeons, 0.79; 95% confidence interval, 0.64-0.98). In the unadjusted analyses, high hospital volume (odds ratio, 0.67; 95% confidence interval, 0.56-0.81) and very high hospital volume (odds ratio, 0.65; 95% confidence interval, 0.54-0.79) is associated with lower postoperative mortality. Postoperative procedural intervention is not a significant mediator of the relationship between hospital volume and mortality. A single variable—the presence of sophisticated clinical services—was the most important explanatory variable underlying the relationship between hospital volume and mortality.

Conclusions  Very high surgeon volume is associated with a reduction in surgical complications. However, the association between increasing hospital volume and postoperative mortality appears to derive mainly from a full spectrum of clinical services that may facilitate the prompt recognition and treatment of complications.

Hospital surgical volume is associated with clinical outcome for patients undergoing colorectal cancer resections and a variety of other cancer operations.1,2 Both short-term outcomes—such as operative mortality,3 length of stay, and cost4—and long-term outcomes—such as survival3,5,6—are associated with hospital volume. These relationships have stimulated efforts to regionalize certain high-risk cancer operations.7,8 Despite these observations, we understand very little about the mechanisms by which increasing clinical volume leads to more favorable surgical outcomes.

Recent evidence indicates that the practice volume of the surgeon as well as the hospital is important in optimizing outcomes for cancer operations, including postoperative mortality and cancer-related survival.4,9 One potential explanation for more favorable outcomes among patients of high-volume cancer surgeons is that the surgeons' accumulated experience allows them to minimize technical errors. Alternatively, high-volume surgeons and hospitals may be more successful at creating a clinical environment that increases the safety of surgical care. It is possible that the favorable outcomes associated with high-volume hospitals are derived from the range of clinical services offered in these high-volume centers. Such services may include expertise in critical care medicine and sophisticated diagnostic and treatment services. Prior research has demonstrated that a higher level of hospital-based technological sophistication, including open heart surgery and organ transplantation programs, is associated with lower mortality rates.10 This study defines the association of surgeon and hospital volume with 2 short-term adverse outcomes of colon cancer surgery: operative mortality and surgical complications that require postoperative procedures. This study aims to examine the extent to which the observed volume-outcome associations are explained by other measurable surgeon and hospital characteristics. Ultimately, identifying processes of care that lead to success in high-volume centers will allow surgeons and hospitals, regardless of their practice volume, to implement changes that will improve outcomes throughout the health care system.

DATA SOURCES

This study used data from the Surveillance, Epidemiology, and End Results (SEER) cancer registry program for individuals diagnosed with colorectal cancer between 1992 and 1996; data were linked to their Medicare claims for outpatient and inpatient services from 1991 to 1997. During the time of this study, the SEER registries included approximately 14% of the US population. The SEER program data include tumor location, stage of disease, and patient demographics.11,12 The Medicare data include all billed claims for services provided to patients enrolled in fee-for-service Medicare, including the original surgical resection and all postoperative procedural interventions (PPIs).13 We used unique provider identification numbers from the Medicare claims data to link physicians' demographic and practice characteristics as reported in the 1993 or 1997 American Medical Association Masterfile. Unique Medicare hospital numbers linked the cancer resection hospital to facility characteristics reported to Medicare via the Medicare Healthcare Reporting and Information System and Provider of Service surveys.

STUDY POPULATION

We identified 33 555 patients aged 66 years and older diagnosed with American Joint Committee on Cancer stage I, II, or III colon cancer between 1992 and 1996. Colon cancers were identified using SEER cancer site codes 18.0, 18.2 through 18.9, and 19.9. We excluded patients who had tumor histologic findings other than adenocarcinoma (n = 433) and patients with prior colorectal cancer (n = 856). We also excluded patients without complete enrollment in parts A and B, or fee-for-service Medicare in the year before diagnosis (n = 7460) and the 6 months following the month of diagnosis (n = 212). These exclusions ensured complete capture of claims data for measuring comorbidity prior to cancer diagnosis, as well as our capability to track procedures after surgery. We excluded patients without a Medicare claim indicating surgical resection of their colon cancer within 6 months of diagnosis (n = 1922). The final study group included 22 672 patients. Of these patients, 22 352 had an identifiable hospital and 21 533 had an identifiable surgeon.

STUDY VARIABLES
Demographic, Clinical, and Tumor Characteristics

The SEER database provided patient date of birth, race/ethnicity, and sex. American Joint Committee on Cancer data from the SEER program identified 3 stages of disease (I, II, and III) and 4 tumor stages (T1, T2, T3, and T4). To measure comorbidity, we adapted the Romano-Charlson index to include outpatient and inpatient diagnoses made during the 11 months prior to the month before colon cancer diagnosis.14,15 This index creates a weighted score using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes for 18 conditions, such as myocardial infarction, congestive heart failure, and chronic pulmonary disease. We classified individuals into 1 of 3 categories of comorbidity: having an index score of 0, 1, or 2 and higher. To adjust for acuity of illness at the time of surgery, we identified individuals with obstructive colon cancer (ICD-9-CM diagnosis codes 560.89 and 560.9), perforated cancer (ICD-9-CM code 569.83), and those admitted under emergent conditions (a Medicare claims–based variable identifying admissions through the emergency department, or those requiring urgent or emergent treatment).

Environmental Characteristics

The SEER registry represented the region in which each patient received care. The median income of race- and age-matched individuals within each patient's census tract estimated socioeconomic status. The race-specific percentage of high school graduates older than 25 years within each patient's census tract was used as a proxy for a combination of socioeconomic status, social class, and education.

Outcomes

The primary outcome measures were 30-day postoperative mortality and 30-day PPIs, such as reoperative laparotomy and other procedures to treat surgical complications (eg, percutaneous drainage of abdominal abscess). Such procedures within 30 days of the index operative procedure are most frequently associated with complications involving the wound, anastomosis, or a technical problem at the time of the primary procedure.16

Surgeon and Hospital Characteristics

Individual surgeons were identified by unique provider identification numbers from the colon cancer resection claim in the Medicare data. For patients with multiple resection claims, we employed an algorithm that prioritized more complex procedures and procedures attributed to the primary surgeon to identify the appropriate resection and the responsible surgeon. Matching a Medicare hospitalization to the date of the surgical resection identified the appropriate hospital. For cases without precisely matching dates, we also used the closest hospitalization or outpatient facility claims within 30 days of resection to identify the resection hospital.

Surgeon characteristics were derived from the American Medical Association Masterfile and included age, sex, location of practice, board certification (colorectal surgery, general surgery, other certification, or none), years in practice, and practice arrangement (solo vs group). Hospital characteristics were derived from both the Medicare Healthcare Reporting and Information System and the Provider of Service survey. These characteristics included ownership (nonprofit, for profit, and government), teaching status, eligibility for disproportionate share hospital payments, average daily census, designation as a National Cancer Institute Cancer Center or cooperative clinical trials group participant, number of intensive care unit beds, and membership in the American College of Surgeons Oncology Group. We also developed a variable that served as a marker for hospitals that offered a range of sophisticated clinical services. The hospitals described as sophisticated clinical service institutions had programs in cardiac surgery and solid organ transplantation. These data were derived from Provider of Service surveys performed in 1996 and 1998. The combination of transplantation and cardiac surgery programs was chosen because of the association of these programs with other medical services, including cardiac care, critical care, and medical subspecialties.

Procedure Volume

We defined each hospital's volume by measuring the total number of index colon cancer resections performed in that facility for patients diagnosed from 1992 through 1996. Surgeon volume was measured by the number of index colon resections the surgeon performed as the primary surgeon on the same group of study patients. While these definitions attributed volume of procedures in later years to surgeries performed in earlier years, the 5-year volume variable was highly correlated with the annual volumes measured in the earlier years and was a much more stable measure of surgical volume than annual measurement, especially for surgeons. Although this methodology does not capture non-Medicare surgical volume for surgeons or hospitals, it has been used in similar studies3,5,17 and has been validated using state hospital discharge data.18,19 Surgeon volume (and other characteristics) could not be determined for 1139 study patients (5.0%) because we were unable to identify the unique provider identification numbers of the primary surgeon. Hospital volume could not be determined for 320 patients (1.4%) because they were missing the hospital identifier. Surgeon and hospital volume are presented as quartiles: low, medium, high, and very high.

Statistical Analyses

χ2 Tests were used to determine the association between patient characteristics and surgical volume of their surgeon and hospital. We also used χ2 tests to examine the characteristics of surgeons and hospitals at each volume stratum. We calculated the crude 30-day mortality and PPI rates for patients of surgeons and hospitals with different volume levels. For each outcome, a series of logistic regression models examined the degree to which our study variables mediated the volume-outcome relationship for both hospitals and surgeons. In the process of logistic regression modeling, we tested all demographic, clinical, environmental, surgeon, and hospital variables. Final regression models included all of the original variables that were significant predictors of the outcome or that improved the model fit. We applied general estimating equation methods20 to our final models to account for clustering of patients by physician and hospital. We found no meaningful differences in the confidence intervals, and we have reported findings from the original modeling.

CHARACTERISTICS OF THE STUDY GROUP

Table 1 summarizes the number of patients, hospitals, surgeons, and case volumes over the 5-year study period. In our sample, the majority of surgeons (67.1%) and hospitals (71.9%) provided surgical treatment for small numbers of colon cancer patients. A limited group of hospitals (4.7%) and surgeons (6.1%) were very high–volume providers.

Table Graphic Jump LocationTable 1. Surgeon and Hospital Colorectal Cancer Surgery Volumes by Quartile

Table 2 presents patient characteristics across surgeon and hospital volume groups. The patients of low-volume surgeons were the most likely of all surgeon volume groups to have had unfavorable clinical characteristics, including obstruction (20.8%), perforated cancers (3.6%), and admission with emergent status (19.5%). The most notable difference among the patients of the hospital volume groups was their socioeconomic status. Patients served by low-volume hospitals were the most likely to be from the lowest socioeconomic status group (65.0%; annual incomes <$25 000); patients treated in very high–volume hospitals had the lowest percentage (46.5%) of low-income individuals.

Table Graphic Jump LocationTable 2. Patient Characteristics by Surgeon and Hospital Volume*
SURGEON AND HOSPITAL CHARACTERISTICS AND RELATIONSHIP TO VOLUME

Patients served by high-volume surgeons were most likely to receive surgical care from board-certified colorectal surgeons (26.6%). Patients who received care from low-volume surgeons had the highest rate of receipt of surgical care from non–board certified surgeons (16%). Patients treated in very high–volume hospitals were the most likely to receive care in not-for-profit hospitals, teaching hospitals, and hospitals with a clinical cancer program (Table 3 and Table 4). Patients treated in very high–volume hospitals also tended to receive care in facilities that offered sophisticated clinical services (83.4%).

Table Graphic Jump LocationTable 3. Patients Cared for by Different Types of Surgeons by Surgeon Volume
Table Graphic Jump LocationTable 4. Patients Cared for by Different Types of Hospitals by Hospital Volume
RELATIONSHIP BETWEEN VOLUME AND POSTOPERATIVE PROCEDURAL INTERVENTION

Surgeon volume was significantly associated with PPI (Table 5) (complete model available in eTable 1).

Table Graphic Jump LocationeTable 1. Procedural Intervention With Physician Volume

While the addition of patient demographics, clinical characteristics, and acuity explained a part of the association between surgeon volume and PPI, very high–volume surgeons maintained their association with decreased PPI in the fully adjusted regression model. We found no significant association between hospital volume and PPI.

Table Graphic Jump LocationTable 5. Adjusted Odds of Postoperative Procedural Intervention Among Patients of Surgeons and Hospitals With Different Volumes
RELATIONSHIP BETWEEN VOLUME AND POSTOPERATIVE MORTALITY

Both surgeon and hospital volume were associated with postoperative mortality in the unadjusted analysis. Patients of high- and very high–volume surgeons and hospitals had significantly lower postoperative mortality than the patients of their low-volume counterparts (Table 6) (complete model available in eTable 2).

Table Graphic Jump LocationeTable 2. Mortality With Physician Volume

In the surgeon volume analysis, the addition of patient demographics, clinical characteristics, clinical acuity, and environmental characteristics explained a substantial portion of the volume-mortality association. The addition of these variables to the model increased the odds ratio (OR) for the very high–volume surgeons from 0.70 to 0.88. While PPI was a significant independent predictor of mortality (OR, 2.48; 95% confidence interval [CI], 2.01-3.07), the addition of PPI to the regression model did not explain the relationship between surgeon volume and postoperative mortality. Colorectal surgery board certification was associated with decreased mortality (OR, 0.69; 95% CI, 0.51-0.94). This certification explained only a small portion of the association between mortality and volume for high-volume surgeons, but it accounted for a significant portion of the association for very high–volume surgeons. Even after adjustment for patient-level variables, surgeon characteristics, and hospital characteristics, high-volume (but not very high–volume) surgical practice remained significantly associated with decreased postoperative mortality.

Table Graphic Jump LocationTable 6. Adjusted Odds of 30-Day Mortality Among Patients of Surgeons and Hospitals With Different Volumes

In the hospital volume analysis, environmental factors, more than clinical or demographic characteristics, accounted for the association between hospital volume and postoperative mortality (Table 6). Clinical characteristics, including perforation (OR, 3.39; 95% CI, 2.65-4.36) and obstruction (OR, 1.92; 95% CI, 1.64-2.25), were independently and significantly associated with 30-day mortality. However, PPI did not explain the hospital volume–mortality relationship, and the addition of surgeon volume and board certification explained this relationship only minimally. Of greatest importance was the availability of sophisticated clinical services, which explained all of the remaining volume-mortality relationship and replaced hospital volume as the most highly significant predictor of postoperative mortality (OR, 0.75; 95% CI, 0.62-0.89). We performed several additional analyses examining interactions between sophisticated services and other variables. First, we examined the interaction between comorbidity and sophisticated services to determine whether the impact of sophisticated services on mortality varied depending on the case severity of the patient. We found that the presence of sophisticated clinical services consistently improved mortality rates across all levels of patient comorbidity. We also examined whether there was an interaction between hospital volume and sophisticated hospital services and found that the relationship between sophisticated hospital services and mortality was consistent across all levels of hospital volume. For low-volume hospitals the mortality rates were 5% and 6% in hospitals with and without sophisticated services, respectively. In very high–volume hospitals the mortality rates were 3.7% and 4.7% for hospitals with and without these services, respectively.

There has been relatively little examination of the structures and processes of care responsible for the observed volume-outcome relationship in cancer surgery. A persistent question remains: does increasing surgical volume enable surgeons to reduce technical errors and their attendant complications, or does practice volume lead to improvements in the processes of perioperative care? This study examines the relationship between surgeon and hospital volume and mortality as well as the relationship between volume and an intermediate surgical outcome: complications, as defined by events requiring a procedural intervention. This study ultimately aims to identify modifiable surgical training or hospital organizational factors that explain the demonstrated volume-outcome relationships.

Our results suggest that while colon cancer surgery is performed with a high degree of safety within the health care system, there are surgeon and hospital factors, including volume, that are associated with adverse outcomes, such as the need for postsurgical procedures and postoperative mortality. This study serves as a reminder that surgeon volume is a very important predictor of surgery complications, even in a technically straightforward procedure, such as colectomy. Logistic regression modeling found no other factors (ie, patient, environmental, other physician, or hospital) to account for the association between surgeon volume and complications. It is not clear whether surgeon or practice volume leads to a reduction in technical errors, improved clinical judgment, or better patient selection. Regardless, it is clear that as surgeons perform colon cancer operations with greater frequency, they can reduce their complication rates, as measured by PPI. However, when mortality is modeled as an outcome, PPI explains little of the relationship between hospital and surgeon volume, and postoperative mortality. These findings lead us to conclude that although increasing surgeon volume may decrease complications, decreasing complications is not the major mechanism by which practice volume decreases postoperative mortality. Our results suggest that minimizing postoperative mortality is associated primarily with systems of care that provide increased safety in the postoperative period.

One of the most striking findings of this study is that a single variable—the presence of sophisticated clinical services, defined by the presence of a cardiac surgery program and a solid organ transplantation program—was the most important explanatory variable underlying the relationship between hospital volume and mortality. These programs were chosen as markers of sophisticated clinical services because cardiac surgery programs require the availability of urgent cardiac catheterization, cardiac care units, and around-the-clock availability of intensive care unit specialists.21 Similarly, hospitals with solid organ transplantation programs have a depth of expertise in multiple medical specialties, as well as interventional radiology. In short, the presence of these programs suggests that a hospital has an array of clinical services that will facilitate the timely management of virtually any medical or surgical complication. While hospital volume was associated with postoperative mortality in the unadjusted analysis, the level of sophisticated clinical services dwarfed volume as a predictor of mortality in our adjusted analysis. Patient characteristics (eg, age, obstruction, perforation, and comorbidity), surgeon characteristics (board certification), and having a PPI were all associated with postoperative mortality, but none of these explained the significant relationship between sophisticated clinical services and mortality.

In our analysis of the association between surgeon and hospital volume and mortality, we find that after adjustment for patient, surgeon, and hospital factors, high-volume surgeons, but not very high–volume surgeons, have lower mortality rates than low-volume surgeons. This finding suggests a surgeon volume–mortality relationship in colon cancer, but only at a certain volume level, beyond which additional practice volume may not further improve outcomes. The reasons for this are unclear, and this finding requires further exploration and confirmation in other studies.

Colorectal surgical board certification explains a portion of the volume-mortality link. We find no evidence that board-certified colorectal surgeons operated with fewer complications than general surgeons. We believe that such specialty surgeons may be more effective at implementing protocols and clinical pathways that increase the safety of colon cancer surgery. It is also possible that these improvements in care may relate to the teams of health care providers, including nursing staff that are brought together by specialty-trained surgeons. These results must be interpreted with caution, however, as general surgeons who are not board certified in colorectal surgery perform the majority of colorectal cancer surgery in the United States. The overall low mortality from these procedures demonstrated by this report should serve to reassure the public that colorectal board certification is not requisite for excellent surgical outcomes in colon cancer.

This study has several important limitations. Like all studies using administrative data, the clinical data in this study are imperfect for many detailed analyses. One of the challenges of administrative data is defining optimal case-mix measures. To adjust for case mix, we have used the Romano-Charlson index, which has been widely used and validated for outcomes research using administrative data. We have also adjusted as completely as possible for other clinical variables, including age, stage of disease, acuity of presentation, and presence of bowel perforation and obstruction. To capture differences in health status commonly associated with economic status and class, we also adjusted for race/ethnicity and ZIP code–based educational level and median household income. Despite this extensive array of variables, it is possible that there were unmeasured confounders that contributed to differences in outcome between high-volume and low-volume hospitals and surgeons.

Another limitation is the inability to capture the full spectrum of surgical complications. Previously, the identification of surgical complications using administrative data has been limited by variability and lack of specificity in coding practices.22,23 For this study, we have chosen to focus on a subset of severe complications that are treated with procedural interventions, including reoperation. These procedures are reliably captured in claims data and are closely associated with significant complications.24 We have demonstrated that these complications are associated with increased mortality and prolonged hospital stay.25 This approach, however, misses many less severe complications that may be very important for patients' quality of life and outcomes of cancer treatment.

Because the study sample was defined by patients diagnosed and living in SEER areas rather than by surgeon and hospital location, the study included a small number of hospitals and surgeons outside of the SEER area registries. We repeated all analyses excluding these surgeons and hospitals and found no meaningful change in our results.

In recent years, volume has been used increasingly as a proxy for quality of care, particularly in technically complex cancer operations. This study focused on a less challenging cancer operation, colectomy. It confirms that for surgeons and the complications of surgery, there is little reason to doubt the aphorism, “Practice makes perfect.” However, complications do not appear to be the major mediator of the relationship between volume and postoperative mortality in colon cancer surgery. This study suggests that in the demonstrated relationship between higher hospital volume and lower mortality, hospital volume may represent a marker for the presence of services that facilitate prompt recognition and effective treatment of complications. As such, it may be possible for medium-volume centers, and potentially low-volume centers, to increase the range of these services to optimize their surgical results. Rather than regionalizing care for all patients with colon cancer, an approach that would be costly as well as undesirable for many patients, the findings of our report suggest that efforts should be made to identify the key processes of care that are in place in hospitals with sophisticated services and implement these at all hospitals performing colorectal cancer surgery.

Overall, our finding that colon cancer surgery is performed relatively safely throughout the health care system is reassuring. Volume will remain an important element in the provision of quality surgical care; however, care must be taken in formulating major health care payment and allocation policies on volume criteria alone.

Correspondence: Kevin G. Billingsley, MD, Department of Surgery L223A, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, Portland, OR 97239 (billingk@ohsu.edu).

Accepted for Publication: November 4, 2005.

Author Contributions:Study concept and design: Billingsley, Dobie, Wright, and Baldwin. Acquisition of data: Billingsley, Matthews, Wright, and Baldwin. Analysis and interpretation of data: Billingsley, Morris, Dominitz, Matthews, Dobie, Barlow, and Baldwin. Drafting of the manuscript: Billingsley. Critical revision of the manuscript for important intellectual content: Morris, Dominitz, Matthews, Dobie, Barlow, Wright, and Baldwin. Statistical analysis: Billingsley, Matthews, and Barlow. Obtained funding: Billingsley, Dobie, Wright, and Baldwin. Administrative, technical, and material support: Dobie.

Financial Disclosure: None reported.

Additional Information:eTable 1 and eTable 2 are available.

Begg  CBCramer  LDHoskins  WJBrennan  MF Impact of hospital volume on operative mortality for major cancer surgery. JAMA 1998;2801747- 1751
PubMed
Gordon  TABurleyson  GPTielsch  JMCameron  JL The effects of regionalization on cost and outcome for one general high-risk surgical procedure. Ann Surg 1995;22143- 49
PubMed
Schrag  DCramer  LDBach  PBCohen  AMWarren  JLBegg  CB Influence of hospital procedure volume on outcomes following surgery for colon cancer. JAMA 2000;2843028- 3035
PubMed
Harmon  JWTang  DGGordon  TA  et al.  Hospital volume can serve as a surrogate for surgeon volume for achieving excellent outcomes in colorectal resection. Ann Surg 1999;230404- 413
PubMed
Schrag  DPanageas  KSRiedel  E  et al.  Hospital and surgeon procedure volume as predictors of outcome following rectal cancer resection. Ann Surg 2002;236583- 592
PubMed
Porter  GASoskolne  CLYakimets  WWNewman  SC Surgeon-related factors and outcome in rectal cancer. Ann Surg 1998;227157- 167
PubMed
Birkmeyer  JDLucas  FLWennberg  DE Potential benefits of regionalizing major surgery in Medicare patients. Eff Clin Pract 1999;2277- 283
PubMed
Gordon  TABowman  HMTielsch  JMBass  EBBurleyson  GPCameron  JL Statewide regionalization of pancreaticoduodenectomy and its effect on in-hospital mortality. Ann Surg 1998;22871- 78
PubMed
Birkmeyer  JDStukel  TASiewers  AEGoodney  PPWennberg  DELucas  FL Surgeon volume and operative mortality in the United States. N Engl J Med 2003;3492117- 2127
PubMed
Hartz  AJKrakauer  HYoung  M  et al.  Hospital characteristics and mortality rates. N Engl J Med 1989;3211720- 1725
PubMed
Nattinger  ABMcAuliffe  TLSchapira  MM Generalizability of the Surveillance, Epidemiology, and End Results registry population: factors relevant to epidemiologic and health care research. J Clin Epidemiol 1997;50939- 945
PubMed
Zippin  CLum  D Study of completeness of the Surveillance, Epidemiology and End Results (SEER) program case ascertainment by hospital size and casefinding source [in English, French]. Health Rep 1993;587- 90
PubMed
Potosky  ALRiley  GFLubitz  JDMentnech  RMKessler  LG Potential for cancer related health services research using a linked Medicare-tumor registry database. Med Care 1993;31732- 748
PubMed
Romano  PSRoos  LLJollis  JG Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol 1993;461075-1079, 1081- 1090
PubMed
Charlson  MEPompei  PAles  KLMacKenzie  CR A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40373- 383
PubMed
Birkmeyer  JDHamby  LSBirkmeyer  CMDecker  MVKaron  NMDow  RW Is unplanned return to the operating room a useful quality indicator in general surgery? Arch Surg 2001;136405- 411
PubMed
Schrag  DPanageas  KSRiedel  E  et al.  Surgeon volume compared to hospital volume as a predictor of outcome following primary colon cancer resection. J Surg Oncol 2003;8368- 79
PubMed
Bach  PBCramer  LDSchrag  DDowney  RJGelfand  SEBegg  CB The influence of hospital volume on survival after resection for lung cancer. N Engl J Med 2001;345181- 188
PubMed
Begg  CBRiedel  ERBach  PB  et al.  Variations in morbidity after radical prostatectomy. N Engl J Med 2002;3461138- 1144
PubMed
Zeger  SLLiang  KYAlbert  PS Models for longitudinal data: a generalized estimating equation approach. Biometrics 1988;441049- 1060[Erratum in:Biometrics. 1989;45:347]
PubMed
DeWeese  JAUrschel  HC  JrWaldhausen  JA Guidelines for minimal standards in cardiac surgery: American College of Surgeons. Bull Am Coll Surg 1991;7627- 29
PubMed
Romano  PSSchembri  MERainwater  JA Can administrative data be used to ascertain clinically significant postoperative complications? Am J Med Qual 2002;17145- 154
PubMed
Romano  PSChan  BKSchembri  MERainwater  JA Can administrative data be used to compare postoperative complication rates across hospitals? Med Care 2002;40856- 867
PubMed
Lawthers  AGMcCarthy  EPDavis  RBPeterson  LEPalmer  RHIezzoni  LI Identification of in-hospital complications from claims data: is it valid? Med Care 2000;38785- 795
PubMed
Morris  AMBaldwin  LMMatthews  B  et al.  Reoperation as a quality indicator in colorectal surgery: a population-based analysis. Ann Surg 2007;24573- 79
PubMed

Figures

Tables

Table Graphic Jump LocationTable 1. Surgeon and Hospital Colorectal Cancer Surgery Volumes by Quartile
Table Graphic Jump LocationTable 2. Patient Characteristics by Surgeon and Hospital Volume*
Table Graphic Jump LocationTable 3. Patients Cared for by Different Types of Surgeons by Surgeon Volume
Table Graphic Jump LocationTable 4. Patients Cared for by Different Types of Hospitals by Hospital Volume
Table Graphic Jump LocationeTable 1. Procedural Intervention With Physician Volume
Table Graphic Jump LocationTable 5. Adjusted Odds of Postoperative Procedural Intervention Among Patients of Surgeons and Hospitals With Different Volumes
Table Graphic Jump LocationeTable 2. Mortality With Physician Volume
Table Graphic Jump LocationTable 6. Adjusted Odds of 30-Day Mortality Among Patients of Surgeons and Hospitals With Different Volumes

References

Begg  CBCramer  LDHoskins  WJBrennan  MF Impact of hospital volume on operative mortality for major cancer surgery. JAMA 1998;2801747- 1751
PubMed
Gordon  TABurleyson  GPTielsch  JMCameron  JL The effects of regionalization on cost and outcome for one general high-risk surgical procedure. Ann Surg 1995;22143- 49
PubMed
Schrag  DCramer  LDBach  PBCohen  AMWarren  JLBegg  CB Influence of hospital procedure volume on outcomes following surgery for colon cancer. JAMA 2000;2843028- 3035
PubMed
Harmon  JWTang  DGGordon  TA  et al.  Hospital volume can serve as a surrogate for surgeon volume for achieving excellent outcomes in colorectal resection. Ann Surg 1999;230404- 413
PubMed
Schrag  DPanageas  KSRiedel  E  et al.  Hospital and surgeon procedure volume as predictors of outcome following rectal cancer resection. Ann Surg 2002;236583- 592
PubMed
Porter  GASoskolne  CLYakimets  WWNewman  SC Surgeon-related factors and outcome in rectal cancer. Ann Surg 1998;227157- 167
PubMed
Birkmeyer  JDLucas  FLWennberg  DE Potential benefits of regionalizing major surgery in Medicare patients. Eff Clin Pract 1999;2277- 283
PubMed
Gordon  TABowman  HMTielsch  JMBass  EBBurleyson  GPCameron  JL Statewide regionalization of pancreaticoduodenectomy and its effect on in-hospital mortality. Ann Surg 1998;22871- 78
PubMed
Birkmeyer  JDStukel  TASiewers  AEGoodney  PPWennberg  DELucas  FL Surgeon volume and operative mortality in the United States. N Engl J Med 2003;3492117- 2127
PubMed
Hartz  AJKrakauer  HYoung  M  et al.  Hospital characteristics and mortality rates. N Engl J Med 1989;3211720- 1725
PubMed
Nattinger  ABMcAuliffe  TLSchapira  MM Generalizability of the Surveillance, Epidemiology, and End Results registry population: factors relevant to epidemiologic and health care research. J Clin Epidemiol 1997;50939- 945
PubMed
Zippin  CLum  D Study of completeness of the Surveillance, Epidemiology and End Results (SEER) program case ascertainment by hospital size and casefinding source [in English, French]. Health Rep 1993;587- 90
PubMed
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