Originally published as JCO Early Release 10.1200/JCO.2007.15.6356 on June 23 2008

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Directing Surgical Quality Improvement Initiatives: Comparison of Perioperative Mortality and Long-Term Survival for Cancer Surgery

Karl Y. Bilimoria, David J. Bentrem, Joseph M. Feinglass, Andrew K. Stewart, David P. Winchester, Mark S. Talamonti, Clifford Y. Ko

From the Department of Surgery; Division of General Internal Medicine, Feinberg School of Medicine, Northwestern University; Cancer Programs, American College Surgeons, Chicago; Department of Surgery, Evanston Northwestern Healthcare, Evanston, IL; Department of Surgery, University of California, Los Angeles; and VA Greater Los Angeles Healthcare System, Los Angeles, CA

Corresponding author: Karl Y. Bilimoria, MD, MS, Cancer Programs, American College of Surgeons, 633 N St Clair St, 25th Floor, Chicago, IL 60611; e-mail: k-bilimoria{at}northwestern.edu

	ABSTRACT

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Purpose Quality-improvement initiatives are being developed to decrease volume-based variability in surgical outcomes. Resources for national and hospital quality-improvement initiatives are limited. It is unclear whether quality initiatives in surgical oncology should focus on factors affecting perioperative mortality or long-term survival. Our objective was to determine whether differences in hospital surgical volume have a larger effect on perioperative mortality or long-term survival using two methods.

Patients and Methods From the National Cancer Data Base, 243,103 patients who underwent surgery for nonmetastatic colon, esophageal, gastric, liver, lung, pancreatic, or rectal cancer were identified. Multivariable modeling was used to evaluate 60-day mortality and 5-year conditional survival (excluding perioperative deaths) across hospital volume strata. The number of potentially avoidable perioperative and long-term deaths were calculated if outcomes at low-volume hospitals were improved to those of the highest-volume hospitals.

Results Risk-adjusted perioperative mortality and long-term conditional survival worsened as hospital surgical volume decreased for all cancer sites, except for liver resections where there was no difference in survival. When comparing low- with high-volume hospitals, the hazard ratios for perioperative mortality were substantially larger than for long-term survival. However, the number of potentially avoidable deaths each year in the United States, if outcomes at low-volume hospitals were improved to the level of highest-volume centers, was significantly larger for long-term survival.

Conclusion Although the magnitude of the hazard ratios implies that quality-improvement efforts should focus on perioperative mortality, a larger number of deaths could be avoided by focusing quality initiatives on factors associated with long-term survival.

	INTRODUCTION

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Numerous studies during the last three decades have demonstrated improved perioperative mortality and long-term survival for patients undergoing complex cancer operations at high-volume hospitals compared with low-volume centers.^1-7 However, identifying underlying reasons for this relationship has been challenging.^4,8 The majority of patients in the United States receive their care at low-volume community hospitals, and few hospitals in the United States satisfy high-volume requirements.⁹ Thus, many have suggested that limited access to these high-volume centers may make regionalization an impractical policy initiative.^10-12

Hospital volume is a proxy for unmeasured structural features and processes of care, and efforts have recently shifted to assess health care quality on the basis of process measures.^13,14 In surgical oncology, the few measures proposed to date concern factors that will influence long-term outcomes such as adjuvant therapy standards for breast and colorectal cancer and the requirement to examine at least 12 lymph nodes to adequately stage colon cancers.¹⁴ Most surgical measures put forth by the Surgical Care Improvement Project (SCIP), Centers for Medicare & Medicaid Services (CMS), American Hospital Association (AHA), and the Joint Commission have focused on perioperative, in-hospital surgical processes of care.^13,15,16 Hospitals and oversight agencies have limited resources and must focus their quality-improvement efforts in particular domains of care; however, it is unclear whether factors affecting perioperative mortality or long-term survival will have a larger effect on patient outcomes.

Using the National Cancer Data Base (NCDB), outcomes were evaluated for 243,103 patients undergoing one of seven complex cancer resections with well-documented volume-outcome relationships.^4,17,18 The objective of this study was to determine whether differences in hospital surgical volume have a larger effect on perioperative mortality or long-term survival. Differences between high-volume and low-volume hospitals were compared for perioperative mortality and long-term survival using two methods. First, multivariable Cox proportional hazards modeling was used to directly compare differences in outcomes by hospital volume at 60 days and 5 years. Secondly, we estimated the number of potentially avoidable deaths at 60 days and 5 years if outcomes at low-volume hospitals were improved to the level of highest-volume hospitals. Developing a better understanding of whether hospital volume, as a surrogate for processes of care and structural features, has a larger impact on perioperative mortality or long-term survival will help direct quality-improvement efforts for cancer surgery.

	METHODS

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Data Acquisition and Patient Selection
The National Cancer Data Base (NCDB) is a program of the American College of Surgeons, the Commission on Cancer (CoC), and the American Cancer Society.^19,20 On the basis of national incidence estimates from the American Cancer Society, the NCDB captures approximately 70% of all cancers in the United States annually.^20,21 This study protocol was approved by the Northwestern University Institutional Review Board (Chicago, IL).

Using the NCDB, patients undergoing cancer-directed surgery for primary cancers from 1994 to 1999 for seven malignancies (colon, esophageal, gastric, liver, lung, pancreatic, and rectal) were identified using International Classification of Diseases for Oncology (second edition) site-specific codes.²² The diagnosis year 1999 with follow-up reported in 2005 was the most recent year of data with follow-up information available. Surgical procedure detail was identified based on Registry Operations and Data Standards (ROADS) coding.²³ To minimize confounding, patients were excluded from the study if they had atypical histologies (lymphomas, sarcomas, GI stromal tumors, leiomyomas, neuroendocrine tumors, or metastases to the liver), stage IV disease, or were younger than 18 years old at the time of diagnosis.

The NCDB requires reporting of six preexisting comorbidities based on International Classification of Disease, ninth edition (ICD-9-CM) classification as of 2003.²⁴ The primary cancer diagnosis and postoperative complications are not included when these six codes are reported. Patients from 2003 to 2004 were identified by the same selection criteria above. A modified Charlson comorbidity score was calculated to assess the severity of preexisting comorbidities.^25,26 Mean Charlson scores were calculated for each hospital. The mean hospital Charlson score was then assigned at the patient level to the 1994 to 1999 analytic cohorts.

Outcomes and Hospital Volume
The primary outcome measures were perioperative mortality and 5-year survival by hospital volume specific to each malignancy. Perioperative mortality was defined as death within 60 days of the index operation. Five-year overall survival was calculated in months from the date of the index operation to the date of death or last contact. Five-year conditional survival was calculated as the time from surgery to death or last contact for patients who survived greater than 60 days after the index surgery. This conditional survival method excludes the effect of perioperative mortality when assessing long-term outcomes.²⁷ Separately for each cancer site examined in this study, hospitals were ranked by average annual surgical volume. Before analysis, cut points were chosen that most closely categorized patients into five approximately equal groups (quintiles).

Survival Analyses
Univariate 5-year overall and conditional survival were estimated by the Kaplan-Meier method, and differences by case volume were compared using the log-rank test.²⁸ Multivariable Cox proportional hazards modeling was used to examine the association between hospital volume and time to death while adjusting for potential confounders including sex, age (< 55, 55 to 64, 65 to 74, 75 years), race (white, nonwhite), stage (I to III), patients’ median ZIP code income (< $36,000, $36,000), Charlson score, type of resection, chemotherapy administration, radiation treatment, and year of diagnosis.²⁹ The type of resection was included as a covariate in the analyses for colon (hemicolectomy v total colectomy), gastric (subtotal v total gastrectomy); hepatic (wedge/segmentectomy v lobectomy), lung (lobectomy/segmentectomy v pneumonectomy), pancreatic (pancreaticoduodenectomy v distal pancreatectomy v total pancreatectomy), and rectal (low-anterior v abdominoperineal resection) cancers. Since patient-level socioeconomic data are not collected by cancer registries, median household income was assessed based on the patient's ZIP code at the time of diagnosis using the 2000 United States Census Bureau data file.³⁰

Only patients surviving beyond 60 days after the index surgery were included in the long-term conditional survival Cox analyses. The proportional hazards assumptions were confirmed graphically. Hazard ratios with 95% CIs were generated. To allow direct comparison of perioperative mortality and long-term survival analyses, the same covariates were used in the Cox models for both perioperative mortality and 5-year conditional survival analyses. The regression models accounted for clustering of outcomes within hospitals using robust variance estimates; however, this did not qualitatively affect the results.³¹

Calculation of Potentially Avoidable Deaths
The potential number of avoidable deaths was estimated for perioperative mortality (at 60 days) and long-term conditional survival (at 5 years) for each of the seven cancer sites using a modification of the methods described by Dudley et al³² (detailed in the footnote for Table 4). This provides an estimate of the number of potentially avoidable deaths if outcomes at the lower-volume centers (80% of hospitals) were comparable with those at the highest volume quintile centers (20% of hospitals).

	RESULTS

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From the NCDB, 243,103 patients who underwent surgery for nonmetastatic colon, esophageal, gastric, hepatic, lung, pancreatic, and rectal cancers were identified (Table 1). The annual case volume thresholds for the highest quintile ranged from more than seven patients for hepatic malignancies to more than 125 patients for colon cancer, whereas the annual case volume cutoffs for the lowest quintile ranged from two cases for pancreatic cancer to fewer than 42 patients for colon cancer (Table 1).

View larger version (15K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 1. Five-year conditional survival comparing patients undergoing resection at highest-volume and lowest-volume quintile hospitals (adjusted for all covariates in the Cox model). (A) Colon, (B) esophagus, (C) liver, (D) lung, (E) pancreas, (F) rectal, (G) stomach.

Finally, we calculated and compared the number of potentially avoidable deaths if care and outcomes at the lower-volume centers (which care for 80% of patients) were similar to those of the highest-volume centers (which care for 20% of patients; Table 4). These estimations utilize the adjusted hazard ratios from the perioperative and conditional long-term Cox analyses described herein. The number of avoidable perioperative deaths (from 0 to 60 days from the index surgery) in the United States in 1 year associated with hospital volume quintile differences ranged from 127 for esophageal cancer to 701 for colon cancer. The number of potentially avoidable long-term deaths (> 60 days after the index surgery) in 1 year in the United States ranged from 491 for pancreatic resections to 2,700 for colon resections. For these seven cancers combined, the total number of potentially avoidable deaths if outcomes at lower-volume hospitals were improved to that of highest-volume hospitals was 2,207 for perioperative mortality and 7,245 for long-term survival.

	DISCUSSION

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In 1979, Luft et al described the volume-outcome relationship for complex surgeries, and since then, a tremendous body of literature has been generated confirming that, for most complex operations, high-volume centers have better perioperative mortality and long-term survival rates compared with low-volume hospitals.^1,17,18 Most acknowledge that volume is a proxy for unmeasured structural characteristics and processes of care, and identifying specific factors has been challenging.^4,8 Quality-improvement initiatives currently address a variety of clinical process measures that affect the quality of care in the perioperative period as well as some measures designed to influence long-term survival. However, the relative benefits of addressing factors influencing perioperative mortality and long-term survival remain unclear, particularly for cancer surgery. Resources to study, develop, validate, and implement quality measures are limited, and developing a better understanding of the differences between perioperative and long-term outcomes may help focus quality-improvement efforts. If we can determine whether hospital volume, as surrogate for processes of care and structural features, has a larger effect on perioperative mortality or long-term survival, quality initiatives can be directed more efficiently.

In this study, two methods were used to determine whether perioperative mortality or long-term survival has a larger impact on patient outcomes by examining the effect of hospital surgical volume. First, we assessed the association between outcomes and hospital surgical volume using Cox proportional hazards models. Secondly, we estimated the absolute number of potentially avoidable deaths in 1 year in the United States in the perioperative period compared with long-term if the quality of care at low-volume centers (80% of hospitals) were equivalent to that at the highest-volume quintile centers (20% of hospitals). No previous study to our knowledge has directly compared perioperative and long-term outcomes for multiple complex cancer surgeries.

Numerous studies and structured reviews have demonstrated differences in perioperative mortality according to hospital surgical volume.^1-4,17,18 Improved outcomes at high-volume hospitals have been repeatedly demonstrated for colon, esophageal, gastric, hepatobiliary, lung, pancreatic, and rectal cancers. Similarly, we found substantial volume-related differences in the risk of perioperative mortality for all seven cancer sites as evidenced by the hazard ratios. As expected, the differences in perioperative mortality between high- and low-volume centers were most striking for high-complexity operations such as esophageal, liver, and pancreatic cancer resections.

Multiple factors have been shown to contribute to differences in perioperative outcomes including preoperative evaluation/patient selection,^33,34 anesthesia care,³³ surgical technique,^33,35 postsurgical order pathways,^36,37 nurse staffing and training,³⁸ and intensive care unit management and staffing.^39,40 Furthermore, the ability and capacity to deal with complex postoperative complications with the assistance of experienced interventional radiologists,⁴¹ emergency response and code teams,^38,42 and 24-hour in-house resident or physician coverage^43,44 may result in improved perioperative outcomes. Finally, the experience and training of the surgeon and consulting physicians at high-volume centers may also contribute to better perioperative outcomes.^33,45-47

Recent studies have focused on the impact of hospital procedure volume on long-term outcomes after complex cancer resections and have concluded that differences in long-term survival by hospital volume are modest compared with differences in perioperative mortality.^7,48,49 High-volume hospitals have been shown to have better long-term outcomes compared with low-volume centers for colon, esophageal, pancreatic, rectal, and gastric cancers.^4,17,18 However, Fong et al⁶ demonstrated that differences in long-term survival after liver resection between high- and low-volume centers are minimal at 5 years after surgery. Similarly, we found a volume-survival correlation for all cancer sites except for liver resections. Numerous factors may contribute to improved long-term outcomes at high-volume hospitals including completeness of resection,⁵⁰ adequacy of nodal examination,^51,52 utilization of adjuvant treatments,⁵³ clinical trials participation,⁵⁴ and aggressiveness of postresection cancer surveillance activities. Further work is needed to determine the relative influence of these factors on long-term outcomes.

As an alternate approach, we further quantified the differences in outcomes using the number of potentially avoidable deaths that could be attributed to the volume-outcome relationship for perioperative mortality compared with long-term survival. Recent studies and our results demonstrate that the numbers of potential lives saved are relatively few in the perioperative period.^32,55 No previous study has examined this issue for long-term outcomes, but we found that the differences in the number of potentially avoidable deaths were significantly larger for long-term survival for all cancer sites examined.

Although this may appear to be contrary to the findings of the Cox proportional hazards model because the hazard ratios comparing low- to high-volume centers were significantly larger for perioperative mortality than long-term survival, two factors play an important role in the differences between the hazard ratios (risk of death) and the absolute numbers of potentially avoidable deaths. First, the incidence of the cancer has a significant effect on the absolute number of lives saved. Secondly, the proportion of patients who die in the perioperative period is small compared with the large proportion that die within 5 years. Thus, a combination of the cancer incidence and the number of deaths explain this apparent paradox between the risk of death on the basis of hazard ratios and the absolute number of potentially avoidable deaths.

The results of this study should be interpreted in light of certain limitations. First, the NCDB does not currently collect surgeon information; however, quality initiatives to date, particularly those from the American College of Surgeons, American Society of Clinical Oncology (ASCO), the National Comprehensive Cancer Network (NCCN), and the National Quality Forum (NQF), are primarily focused on assessing hospital-level performance rather than individual surgeon performance. Secondly, long-term outcomes were assessed on the basis of all-cause mortality. Most studies of the surgical volume-outcome relationship have focused on overall survival. Moreover, disease-free survival is difficult to assess because recurrences and the date of recurrence are underreported to cancer registries. Thus, overall survival was selected as the metric for long-term outcomes.

Although prior studies have suggested that surgical volume-related differences in long-term survival are small compared with those observed for perioperative mortality, the results of this study suggest that not only should quality-improvement initiatives in surgical oncology address factors affecting perioperative mortality, but they should also have a considerable focus on identifying factors impacting long-term outcomes. There are large disparities in perioperative mortality between lowest- and highest-volume centers evidenced by the magnitude of the hazard ratios. This implies that there are significant lessons that can be learned from the way high-volume hospitals care for patients in the perioperative period. The differences in long-term survival between high- and low-volume hospitals may appear marginal when examining the hazard ratios; however, we found that the absolute number of potentially avoidable deaths was considerably larger long-term. Thus, small improvements in factors affecting long-term outcomes (ie, lymph node evaluation for colon cancer, adjuvant treatment utilization) will potentially affect a larger number of patients and save more lives.

Rather than regionalizing or centralizing care for all complex cancer resections, identifying hospital structural characteristics and processes of care affecting outcomes and transference to low-volume centers represents a mechanism to improve outcomes for most cancer resections at lower-volume hospitals where most patients in the United States receive their care. Implementing quality measures and monitoring performance may provide hospitals with targets for quality-improvement initiatives. Thus, there is an opportunity to improve cancer care in the United States by identifying, validating, and implementing quality measures that influence both perioperative mortality and long-term survival.

	AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

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The author(s) indicated no potential conflicts of interest.

	AUTHOR CONTRIBUTIONS

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Conception and design: Karl Y. Bilimoria, David J. Bentrem, Joseph M. Feinglass, Clifford Y. Ko

Financial support: Clifford Y. Ko

Administrative support: Clifford Y. Ko

Provision of study materials or patients: Joseph M. Feinglass, Andrew K. Stewart, Clifford Y. Ko

Collection and assembly of data: Karl Y. Bilimoria, Andrew K. Stewart

Data analysis and interpretation: Karl Y. Bilimoria, David J. Bentrem, Joseph M. Feinglass, Andrew K. Stewart, David P. Winchester, Mark S. Talamonti, Clifford Y. Ko

Manuscript writing: Karl Y. Bilimoria, David J. Bentrem, Joseph M. Feinglass, Andrew K. Stewart, David P. Winchester, Mark S. Talamonti, Clifford Y. Ko

Final approval of manuscript: Karl Y. Bilimoria, David J. Bentrem, Joseph M. Feinglass, David P. Winchester, Mark S. Talamonti, Clifford Y. Ko

	ACKNOWLEDGMENTS

 
We thank the American College of Surgeons, National Cancer Data Base staff for their assistance.

	NOTES

 
published online ahead of print at www.jco.org on June 23, 2008.

Supported by the American College of Surgeons, Clinical Scholars in Residence program and a research fellowship from the Department of Surgery, Feinberg School of Medicine, Northwestern University (both to K.Y.B.); and American Cancer Society Grant No. ACS IRG 93-037-12 (D.B.).

Presented at the Annual Meeting of the Society of Surgical Oncology, March 13-16, 2008 Chicago, IL.

Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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Submitted December 4, 2007; accepted April 14, 2008.

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