Rahima N. Nenshi. A thesis submitted in conformity with the requirements for the degree of Master of Science (Clinical Epidemiology)

Transcription

1 THE ONTARIO STRUCTURES OF CARE IN COLORECTAL CANCER SURGERY STUDY (OSCRC): ASSESSING HOSPITAL LEVEL VARIATION AND IMPACT ON SHORT TERM PATIENT OUTCOMES A thesis submitted in conformity with the requirements for the degree of Master of Science (Clinical Epidemiology) Graduate Department of Health Policy, Management and Evaluation University of Toronto Copyright by 2009

2 Abstract HOSPITAL-LEVEL STRUCTURES OF CARE AND SHORT TERM OUTCOMES OF COLORECTAL CANCER SURGERY Masters of Science 2009 Graduate Department of Health Policy, Management and Evaluation University of Toronto Introduction: Surgical treatment is the cornerstone of the management of colorectal cancer (CRC). This study described the structures of care at Ontario hospitals performing CRC surgery. Methods: Patients diagnosed with CRC undergoing surgery were identified from Data linkage identified all institutions performing CRC surgery. Multiple hospital level structures were measured. For the final year of our study, the impact of these structures on 30-day mortality was evaluated. Results: 20,784 patients underwent CRC surgery. Each year, between 106 and 109 institutions performed at least one CRC operation. There was variation in hospital level structures of care. After adjustment for patient characteristics, no hospital level structures were independently associated with 30d mortality. Conclusions: Although variation in surgical care and patient outcomes is likely related to variation in processes and structures of care, after adjusting for covariates, our study did not show any significant relationship between hospital level structures and 30-day mortality. ii

3 Acknowledgements First, I would like to thank my supervisor Dr. David Urbach for his patience, contagious enthusiasm about health services research, attention to detail and for his mentorship in both the clinical and research realms. Thank you to my committee members, Dr. Nancy Baxter, Dr. Erin Kennedy and Dr. Rinku Sutradhar. Your feedback in the development and fine-tuning of this project has been invaluable and I thank you for your support and encouragement throughout this process. I would also like to acknowledge Refik Saskin, analyst extraordinaire, for his help at all stages of the creation of the databases necessary to complete my project and also for his gracious tolerance of my timid, yet frequent visits to his office for help. Thank you to Binu Jacob for her help in various aspects of SAS programming and in helping me figure out multilevel modeling. Also, thank you to Dr. Rahim Moineddin for sharing his expertise in building and interpreting a multilevel model. I am indebted to the members of the Surgical Clinical Epidemiology research group, whose weekly Monday morning meetings kept me on my toes and from whom I learnt a lot about the world of surgical research. Thank you also to Stacey Stegienko, Joy Zoleta and Julie Harnish for helping me with the many essential day to day things a research student in a new environment requires. To my fellow SSP s in clinical epidemiology, Cagla Eskicioglu, Kristen Davidge, and Bryan Wells, it was a true pleasure to work with you and learn from you! To my family: my parents, my sister and my in-laws you have been a constant source of strength for me and the passion with which you believe in me helps me to believe in myself. Finally, to the most important person in my life, my husband, Harshal: Your love, sense of humour, unwavering support for my career, and constant encouragement are the only reason I can do what I do Thank you. iii

4 Table of Contents Abstract... ii Acknowledgements...iii Table of Contents... iv List of Tables... vi List of Figures...ix List of Abbreviations... x Introduction... 1 Colorectal Cancer Epidemiology... 1 Natural History of CRC... 2 The Surgical Management of CRC... 4 Variation in the surgical management and outcomes of CRC... 5 Beyond the Volume Outcome relationship Exploring Quality of Care Why does variation exist? Hospital-level structures of interest Rationale Objectives Methods Overview Data sources Selection Criteria Patient-level variables Hospital-level variables iv

5 Statistical Analysis Results Patient Characteristics Characteristics of Hospitals in the OSCRC study Study Outcomes Multivariable modeling Discussion Objective #1 To describe the structures of care identifiable in administrative data for CRC surgery in Ontario Objective # 2 To describe the variability of structures of care across Ontario hospitals Objective #3 Modeling relationships between structures of care and 30-day mortality Limitations Summary and future directions References v

6 List of Tables Table 1: Characteristics of men and women 20 years of age or older, newly diagnosed with colon and rectal cancer, in Ontario, 2003/04 1 (2)... 1 Table 2. Tumor-Node-Metastasis (TNM) definitions, AJCC 6th ed. (6)... 3 Table 3. Tumor-Node-Metastasis (TNM) Staging for Colorectal Cancer, AJCC 6th ed. (6)... 3 Table 4: Radiation therapy consultations and services received by individuals 20 years of age or older, with newly diagnosed rectal cancer, 12 months before and after their final surgery, by LHIN, in Ontario, 2003/04 (2)... 6 Table 5: CCI Surgical Intervention codes used to identify patients who underwent CRC Surgery in the Ontario Structures of care for Colorectal Cancer Surgery (OSCRC) study Table 6: ICD-10 Chemotherapy and Radiotherapy codes used to identify patients who had advanced disease in the OSCRC study Table 7: ICD-10 Chemotherapy and Radiotherapy codes used to identify patients who had advanced disease in the OSCRC study Table 8: OHIP fee codes used to identify patients undergoing laparoscopic surgery in the OSCRC study Table 9: CCI Surgical Intervention codes used to identify surgeons who perform colorectal surgery and surgeons who perform >50 cases of colorectal surgery per year in the OSCRC study Table 10: OHIP fee codes used to identify institutions with or without CT and MRI the OSCRC study Table 11: OHIP fee codes used to identify institution level colonoscopy availability in the OSCRC study vi

7 Table 12: OHIP fee codes used to identify institution level interventional radiology (IR) service availability in the OSCRC study Table 13: OHIP billing codes used to identify institution level cardiology and anesthesia service availability in the OSCRC study Table 14: Demographic and Geographical characteristics of patients in the OSCRC study from Table 15: Surgery characteristics of patients in the OSCRC study Table 16: Clinical Characteristics of patients in the OSCRC study by site of disease Table 17: Hospital colorectal surgery case volume by year in the OSCRC study Table 18: Characteristics of hospitals in the OSCRC study Table 19: Intensive Care Unit (ICU) characteristics of hospitals in the OSCRC study Table 20: Relationship of structures of care at hospitals in the OSCRC study and Urban (Academic/Non-Academic 1 ) and Rural Status 2 in Table 21: Relationship of structures of care at hospitals in the OSCRC study and volume quintile in Table 22: Patient-Level Outcomes 1 in the OSCRC study Table 23: Adverse outcomes among patients in the OSCRC study according to diagnostic imaging-related structures of care available at the hospital where surgery occurred Table 24: Adverse outcomes among patients in the OSCRC study according to colonoscopyrelated structures of care available at the hospital where surgery occurred Table 25: Adverse outcomes among patients in the OSCRC study according to cardiology and anesthesia related structures of care available at the hospital where surgery occurred vii

8 Table 26: Adverse outcomes among patients in the OSCRC study according to ICU-related structures of care available at the hospital where surgery occurred Table 27: Adverse outcomes among patients according to whether they had surgery at a hospital in the OSCRC study with the following subspecialty access Table 28: Relationship of Urban/Rural, Academic/Non-academic, and Volume quintile status of hospitals in the OSCRC study and short-term patient outcomes Table 29: Correlation Matrix for Hospital-level variables, Year= Table 30: Logistic Regression Models for 30d mortality in the final year of the OSCRC study, Table 31: Multilevel Model for 30d mortality with patient covariates only in the final year of the OSCRC study, Table 32: Multilevel and GEE Models for 30d mortality in the final year of the OSCRC study, Table 33: Multilevel Model for 30d mortality including only volume quintile and patient covariates in the final year of the OSCRC study, viii

9 List of Figures Figure 1: Variation in 30 day mortality among Ontario Hospitals (CCO Data) Figure 2: Examples of Structures, Processes and Outcomes in the Donabedian Model (49) Figure 3: Example of Hierarchical Data Figure 4: Characteristics 1 of hospitals in OSCRC study ix

10 List of Abbreviations AFP Alternate Funding Plan AJCC American Joint Committee on Cancer CCI Canadian Classification of Health Interventions CIHI-DAD The Canadian Institute for Health Information Discharge Abstract Database CRC Colorectal Cancer CT Computed tomography FOBT Fecal Occult Blood Test ICES Institute for Clinical and Evaluative Sciences ICD-9 - The International Classification of Diseases, 9th Revision ICD-10 - The International Classification of Diseases, 10th Revision ICU Intensive Care Unit IKN ICES Key Number IPDB ICES Physician database IPPE - Income per person equivalent LHIN Local Health Integration Network MOHLTC Ministry of Health and Long-term Care MRI Magnetic Resonance Imaging NACRS National Ambulatory Care Reporting System NSQIP - National Surgical Quality Improvement Program OCR Ontario Cancer Registry OHIP Ontario Health Insurance Plan OSCRC Ontario Structures of care in Colorectal Cancer Surgery study PCC Pearson Correlation Coefficient REB Research Ethics Board RPDB Registered Persons Database TNM Tumor-Node-Metastasis VA Veterans Affairs x

11 Introduction Colorectal Cancer Epidemiology Colorectal cancer (CRC) is the third most common cause of cancer and the second most common cause of cancer death among Canadian men and women (1). An estimated 8,129 people in Ontario were diagnosed with CRC in 2007, and in the same year 2,793 died of this disease (1). Ontario data from 2003/2004 summarized in Table 1 and adapted from an exhibit in Cancer Surgery in Ontario (2), shows the age-standardized incidence rate of colon cancer is 56.4 cases per 100,000 for men and 52.9 cases per 100,000 for women. For rectal cancer, the age standardized incidence rate is 20.5 per 100,000 for men and 13.7 per 100,000 for women. The incidence of CRC also increases with age and the incidence in those above 75 years old is cases per 100,000 (2). Table 1: Characteristics of men and women 20 years of age or older, newly diagnosed with colon and rectal cancer, in Ontario, 2003/04 1 (2) Characteristic Colon Cancer Rectal Cancer Sex Number (%) Age-standardized 2 rate Age-standardized 2 Number (%) per 100,000 rate per 100,000 Male 2680 (50.9) (59.1) 20.5 Female 2585 (49.1) (40.9) 13.7 Age Group years 623 (11.8) (18.3) years 975 (18.5) (23.1) years 727 (13.8) (14.0) years 896 (17.0) (14.3) years 2044 (38.8) (30.3) These data are from Cancer Surgery in Ontario (2) 2 Rates standardized to 1991 Canadian population. Subgroup proportions standardized to overall cohort. 2 Age-specific rates have not been standardized Trends in Ontario have shown an increase in both the incidence of CRC as well as in the surgical treatment of CRC, from 4,318 large bowel resections in 1993/1994 to 6,190 large bowel resections in 2003/2004 (3). 1

12 Natural History of CRC Although some hereditary forms of CRC exist, the large majority of colorectal malignancies are sporadic and >90% are histologically characterized as adenocarcinomas (4, 5). It is commonly understood that adenocarcinomas of the colon and rectum originate from benign, adenomatous polyps (although not all adenomatous polyps will develop into cancer) (4). Patients with colorectal cancer may present with clinical symptoms such as weight loss, change in bowel movements, abdominal pain, anemia or rectal bleeding. They can also be diagnosed through screening tests, such as a Fecal Occult Blood Test (FOBT), imaging tests such as barium enema or CT colonography, or by screening sigmoidoscopy or colonoscopy. A definitive diagnosis of cancer usually involves colonoscopy, which allows for biopsy, possible excision, pathologic diagnosis and surveillance of the remainder of the colon and rectum. If colonoscopy reveals a polyp, depending on the characteristics of the lesion, it may be amenable to local excision using endoscopic methods. Some types of polyps (e.g.: large or flat (sessile)) are not amenable to endoscopic removal and therefore patients require surgery for removal. If a colonic polyp is left untreated (or is missed on colonoscopy) it is postulated that it is then at risk to begin the adenoma-carcinoma sequence, and may eventually progress to malignant disease. Patients who present with advanced disease or symptoms such as bowel obstruction or bleeding may require urgent surgery for removal of the primary tumor or for palliation of symptoms. Once diagnosed with colorectal cancer, staging is required to assess the local and distant extent of disease. This generally involves imaging of the chest and abdomen to assess the presence or absence of metastatic disease. In some centers, for rectal cancer, pre-operative MRI and/or endorectal ultrasound is also used for pre-operative planning. Staging is important for several 2

13 reasons. The stage of the tumor determines the prognosis for the patient as well as directs neoadjuvant (chemotherapy or radiotherapy treatment given before surgery) and/or adjuvant therapy (chemotherapy or radiotherapy treatment given after surgery) and operative planning. Tables 2 and 3 summarize the American Joint Committee on Cancer (AJCC) 6th edition tumornode-metastasis (TNM) staging of colorectal cancer (6). This staging system is based on the depth of invasion of the bowel wall, extent of regional lymph node involvement, and the presence of distant metastatic disease. With increasing stage of disease, the 5 year overall survival decreases from greater than 90% to less than 10% (7). Table 2. Tumor-Node-Metastasis (TNM) definitions, AJCC 6th ed. (6) Primary Tumor (T) TX Primary tumor cannot be assessed Tis Carcinoma in situ T1 Tumor invades submucosa T2 Tumor invades muscularis propria T3 Tumor penetrates muscularis propria and invades subserosa T4 Tumor directly invades other organs or structures or perforates visceral peritoneum Nodal status (N) NX Regional lymph nodes cannot be assessed N0 No metastases in regional lymph nodes N1 Metastases in one to three regional lymph nodes N2 Metastases in four or more regional lymph nodes Distant Metastases (M) MX Presence or absence of distant metastases cannot be determined M0 No distant metastases detected M1 Distant metastases detected Table 3. Tumor-Node-Metastasis (TNM) Staging for Colorectal Cancer, AJCC 6th ed. (6) Stage TNM Classification Five year overall survival I T1-2, N0, M0 >90 % IIa IIb T3, N0, M0 T4, N0, M % IIIa IIIb IIIc T1-2, N1, M0 T3-4, N1, M0 T (any), N2, M % IV T (any), N(any), M1 5-7 % 3

14 Surgery is the primary treatment for colorectal cancer, and currently it is the only modality by which cure is possible. However, even if cure is not possible, surgery may be needed to palliate symptoms such as pain, bleeding, obstruction or perforation. In Ontario, more than 80 percent of persons with cancer undergo surgery at some point during their illness, for diagnosis, staging, curative treatment, or palliation (2). The Surgical Management of CRC In Ontario, 74.4% of CRC surgery is performed by general surgeons without a self-identified surgical oncology or colorectal subspecialty and 74.3% of surgeries are performed in nonacademic settings (2). The goal of surgery can be to stage disease, to achieve cure, for palliation of symptoms or to treat complications (e.g. obstruction) of the disease. The choice of surgical procedure is dependent on factors such as the location of the primary tumor, the presence of other polyps or primary tumors, considerations of maintaining continence and whether or not it is considered safe to restore bowel continuity. In general, right-sided and transverse colon tumors are resected with a right hemicolectomy. Left-sided and sigmoid tumors are removed by a left hemicolectomy or sigmoidectomy. Proximal rectal tumors are treated with an anterior resection and more distal rectal tumors are usually treated with an abdominoperineal resection with a permanent end colostomy. The goal of surgical therapy with curative intent is to achieve complete removal of the primary cancer with tumor-free margins, to remove all lymph nodes in the anatomic drainage basin of the involved bowel segment and, if needed, to remove adjacent organs involved with the primary tumor and to restore intestinal continuity when possible. Appropriate resection, and therefore staging, of the carcinoma also informs decisions about postoperative radiation and chemotherapy. Depending on disease stage, radiation and/or chemotherapy often complements the surgical treatment of patients. Randomized clinical trials 4

15 have shown survival benefit and decreased local recurrence with chemotherapy in colon cancer and with adjuvant chemotherapy and/or chemoradiation therapy in rectal cancer (8, 9). The benefit of chemoradiation is attributed to the eradication of micrometastatic disseminated disease by chemotherapy and the eradication of microscopic residual disease by radiotherapy. The 30- day post-operative mortality for patients undergoing CRC surgery in Ontario is less than 5% (1). Variation in the surgical management and outcomes of CRC While surgery is the primary treatment for CRC, there is enormous variation in the patterns of care and outcomes of CRC surgery (10-12). A study by the National Initiative for Cancer Care Quality in the United States estimated that only 78% of CRC patients receive recommended care (13), further highlighting the presence of variation in care and the opportunity for quality improvement in CRC. Recent Ontario data published in the ICES Cancer Surgery Atlas (2) summarized in Table 4, have shown differences in the types of surgery provided and in the use of radiation therapy for patients with rectal cancer received according to the patients Local Health Integration Network (LHIN) of residence (2). The percentage of patients with rectal cancer who underwent resection with permanent stoma ranged from 16% to 43% across LHINs. The use of radiation therapy also varied by LHIN; overall 65% of patients who had surgery also had a radiation oncology consultation, and 21.6% underwent planning for pre-operative radiation. Data on the delivery of radiotherapy were not available, and therefore consultations and planning sessions were used as a proxy for this information. Among LHINs, the proportion of surgical patients with rectal cancer who saw a radiation oncologist ranged from 52% to 82% and the proportion of surgical patients who underwent planning for pre-operative radiation ranged from 10% to 40%. 5

16 Table 4: Radiation therapy consultations and services received by individuals 20 years of age or older, with newly diagnosed rectal cancer, 12 months before and after their final surgery, by LHIN, in Ontario, 2003/04 (2) LHIN of patient residence Total (N) Radiation oncology Radiation therapy planning before surgery N (%) Consults 1 N (%) Sessions 2 Erie St. Clair (82.1) 60 (1.1) 17 (25.4) 18 (1.1) South West (65.1) 103 (1.1) 14 (9.6) 14 (1) Waterloo Wellington (61.3) 53 (1.1) 8 (10) 8 (1) Hamilton Niagara Hald. Brant (56.7) 101 (1.0) 24 (14) 26 (1.1) Central West (58.5) 25 (1.0) 13 (31.7) 15 (1.2) Mississauga Halton (65.3) 52 (1.1) 24 (32) 27 (1.1) Toronto (63.9) 57 (1.1) 20 (24.1) 23 (1.2) Central (59.5) 85 (1.1) 45 (34.4) 45 (1) Central East (60.5) 99 (1.1) 34 (23.1) 35 (1) South East (66.2) 47 (1.0) 8 (11.8) 8 (1) Champlain (79.3) 102 (1.1) 46 (39.7) 47 (1) North Simcoe (73.8) 31 (1.0) 8 (19) 9 (1.1) North East (72.8) 62 (1.1) 9 (11.1) 10 (1.1) North West (51.7) 17 (1.1) 6 (20.7) 6 (1) All regions 1, (65.1) 894 (1.1) 276 (21.6) 291 (1.1) 1 N (average number of consults per patient who had a consultation) 2 N (average number of sessions per patient who had a radiation therapy planning session) A population-based study published in 1999 (14) also evaluated the utilization of surgery and of radiotherapy in the treatment of newly diagnosed rectal cancer in Ontario between 1982 and In this twelve-year time period, 18,695 patients underwent surgery for rectal cancer. The authors used a logistic regression model to calculate odds ratios for resection with permanent colostomy and for receipt of postoperative radiotherapy. Overall, 33.1% (N=6,194) of patients underwent resection with creation of a permanent colostomy. Rates of resections with creation of permanent colostomy varied across regions from 30.6% to 40.9%. The proportion of patients receiving radiation therapy also varied between regions; from 11.6% to 20.7%. The study reported regional outcome variation; the relative risk of death between regions varied from 0.95 (95% CI 0.86, 1.04) to 1.14 (95% CI 1.03, 1.25). This study was limited by the lack of stage 6

17 information, which presents a significant selection bias, both in terms of the surgical procedure of choice as well as the decision to offer post operative radiotherapy. However, the presence of survival differences in the model adjusted for age and surgical procedure still showed regional variation. A Canadian study published in 1998 evaluated whether surgical subspecialty training in colorectal surgery or frequency of rectal cancer resection were independent prognostic factors for local recurrence and survival (15). The authors reviewed cases of rectal cancer surgery over an 8- year period in which 683 patients underwent rectal cancer resection by one of 53 surgeons. All patients undergoing potentially curative low anterior resection or abdominoperineal resection for primary adenocarcinoma of the rectum were included. A potentially curative resection was defined as negative surgical margins and absence of residual metastatic disease. Using a Cox proportional hazards regression model to account for confounding and interactions, the study reported a hazard ratio of 2.49 (95% CI , P<0.001) of local recurrence if the surgery was performed by a non-specialist surgeon. The same study also reported a hazard ratio of 1.80 (95% CI , P<0.001) of local recurrence in surgeries performed by surgeons who performed <21 resections over the study period ( ). Disease-specific mortality increased with surgery performed by a non-specialist surgeon (HR 1.5, 95% CI , P=0.03) or a surgeon performing less than 21 cases (1.4, 95% CI , P<0.005). There are, however, some limitations to this study. The authors used a liberal definition of local recurrence, and included both histologically proven and radiographically suspected cases of local recurrence. This led to a higher rate of local recurrence, which was reported as 33.2% in the study population. Of note, 27.2% of local recurrence cases in this study did not have histological 7

18 confirmation. Over the study period, several different chemotherapeutic regimens and radiotherapy doses were used and this was a confounder. The authors hypothesized that the observed improved outcome amongst patients undergoing surgery by either a subspecialist surgeon or a surgeon performing >21 cases may be due to operative techniques. Two reviews, published in 2000 (16) and 2001 (17), evaluated the impact of provider characteristics on patient outcomes. Both found that though surgeon expertise and case volume have been associated with improved tumor control, these factors are not consistently associated with perioperative mortality or long-term survival. In the more recent review, Hodgson et al (17) reviewed 57 articles that studied the relationship between patient and provider characteristics and treatment and outcomes of colorectal cancer. Two out of three studies that assessed surgeon volume as a predictor of the type of surgery (sphincter-sparing or not) found that there was no statistically significant relationship. Three of the four studies reviewed, which evaluated the relationship between surgeon volume and post operative mortality, found no significant relationship. The single study (18) that reported lower in-hospital mortality for high volume surgeons had a small absolute magnitude of difference (1.9%), and this difference was not statistically significant. Both reviews emphasized the lack of studies documenting institutional variability in colorectal cancer care. Another study, published in 2001, evaluated the surgeon volume-mortality relationship for colectomy in 22,128 patients undergoing CRC surgery (19).This study found a significant different in mortality between the lowest surgeon volume quintile and the highest surgeon volume quintile. (4.81% vs. 2.23%, P<.0001). Overall, while some studies have reported an association between provider characteristics and postoperative mortality, these findings are not consistent. 8

19 Some studies have shown an increased likelihood of undergoing sphincter-sparing surgery as hospital volume increases (15, 20-22). Higher hospital volume has also been shown to be associated with lower 30-day mortality for colon cancer patients (23). A study published in 2000 (24) used Ontario data to examine the impact of hospital volume and teaching status also on rectal cancer surgery patients. This study examined 1,072 patients diagnosed over a 1-year period and found no clinically significant differences in treatment measures, operative mortality or long-term survival among hospitals classified either by teaching status or by procedure volume. More recently, a population-based study published in 2003 used data from the California Cancer Registry to evaluate the association between hospital volume and post operative mortality following surgery for rectal cancer (10). The cohort included 7,646 patients who underwent surgery for rectal or rectosigmoid cancer from The authors identified three end points: permanent colostomy, 30-day postoperative mortality and overall mortality in the 2 years following surgery. Hospital volume was calculated as the average annual number of rectal cancer patients undergoing surgery in each specific hospital. Volume categories were then created by dividing the cohort into quartiles that contained approximately equal number of patients. Surgeries were performed across 367 hospitals in California over the study period, and the number of operations ranged from 1 to 113 cases per institution over four years. A multivariable logistic regression model (using generalized estimating equations to account for clustering) showed variation in 30d mortality from 1.6% in hospitals performing >20 cases/year as 9

20 compared to 4.8% in hospitals performing <7 cases/year (P <. 001). In a multivariable Cox proportional hazards model, the association between hospital volume and two-year survival was also significant and ranged from 83.7% in the highest volume quartile as compared to 76.6% in the lowest volume quartile. Perhaps the greatest strength of this study is that the California Cancer Registry includes information on tumor stage and therefore, the differences between higher volume hospitals and lower volume hospitals persisted even after adjustment for age, comorbidity index and tumor stage. However, the mediators for differences in mortality by hospital volume are not readily identifiable and the authors hypothesized that the differences may be due to hospital-level structures such as staffing models and technical resources. This study further highlighted the paucity of information on hospital-level structural variability and its impact on outcomes. Recent data from Cancer Care Ontario also show variation in 30d mortality following colorectal cancer surgery in hospitals across the province (Figure 1). However, from these data, it is difficult to make conclusions about statistically significant differences in 30d mortality due to the small sample size with resulting wide confidence intervals (25). Furthermore, these crude data lack risk adjustment and therefore do not account for selection bias (i.e. the difference in patients between hospital sites). This example demonstrates the challenges in identifying what may be the best or worst hospitals. 10

21 Figure 1: Variation in 30 day mortality among Ontario Hospitals (CCO Data) d mortality including 95% confidence interval Institutions performing CRC surgery Beyond the Volume Outcome relationship The most common structural characteristic of surgical care evaluated in health services research is surgical volume (26). A large body of research has shown that the outcomes of surgical procedures are better when done in an environment where many similar procedures are performed. This is true for hospitals (27, 28) as well as individual surgeons (27-29). The first widespread publication identifying the volume-outcome relationship was published in 1979 (30). In this study, Luft et al examined discharge data on 12 surgical procedures from 1,498 hospitals. They found that for certain operations (CABG, open heart surgery, vascular surgery and TURP), hospitals that performed more than 200 procedures per year had adjusted death rates that were 25-41% lower than hospitals with fewer than 200 procedures. Of note, in this first sentinel study, no relationship was found for colon cancer surgery. Since then, over 125 articles 11

22 have been published focusing on the measurement of this relationship as they relate to both surgical and clinical procedures, the large majority of which report a significant relationship between provider volume and outcomes (26). This includes improved perioperative mortality and long-term survival for patients undergoing complex cancer operations at high volume hospitals compared with low-volume hospitals. The largest study to date (27) reviewed the results of 2.5 million Medicare patients who underwent 1 of 14 cancer or cardiovascular procedures between 1994 and Mortality and volume were inversely related for all of these procedures, but the magnitude of difference between high and low volume providers varied substantially. Birkmeyer et al estimated that high-volume providers have mortality rates that are 20 to 50% lower than low-volume providers for procedures such as CABG, carotid endarterectomy and abdominal aortic aneurysm repair, however colon cancer was not identified as an area with significant volume-outcome differences (31). Furthermore, a recent large study from the National Cancer Database (32) evaluated 243,103 patients undergoing surgery for non-metastatic colon, esophageal, gastric, liver, lung, pancreatic or rectal cancer. Both risk-adjusted peri-operative mortality (within 60 days post op) and long term conditional survival (5-year survival) worsened as hospital surgical volume decreased in all subgroups of surgical procedures. Of note, a recent study of Ontario data (33), published in 2006, evaluated the influence of hospital volume on operative death after major cancer surgery in the province. The study found no statistically significant difference in operative death or long-term survival in patients undergoing CRC surgery in a low- or high-volume hospital. The widespread publication of studies showing improved outcomes with higher volumes has led to the advent of volume-based referral strategies. In the U.S., the Leapfrog Group was founded in 12

23 2000 as a nonprofit business coalition made up of several large employers and health-care purchasers in the United States (34). This group focuses on hospital safety and quality through several mandates, one of which is to implement volume standards for 5 selected high-risk procedures (Coronary-artery bypass graft, abdominal aortic aneurysm repair, coronary angioplasty, esophagectomy and carotid endarterectomy). This has been postulated as an immediate and feasible approach to quality improvement that theoretically rapidly results in better outcomes (35). One of the first studies about the Leapfrog initiative estimated that annually, it could save over 2500 lives (36). However, it limits a broader, more all-encompassing continuous quality improvement approach. Most importantly, although the determinations of volume thresholds appear somewhat arbitrary in most published studies, these thresholds have been extracted and used by insurers and regulators to impose minimum volume requirements (35). Importantly, we cannot necessarily extrapolate that the data from the United States applies to Canada. A Canadian study (37) evaluating the number of lives potentially saved through regionalization estimated the annual number of operative deaths that could potentially be avoided if 5 major surgical procedures were regionalized. The authors calculated the number of operative deaths among the 75% of persons treated at the low volume hospitals and compared them to the 25% of persons treated at the high volume hospitals. Specifically for patients undergoing surgery for CRC, the study concluded that a regionalization strategy would not have saved any lives and, in fact, 17 (95% CI, 36 to -3) lives would potentially have been lost. 13

24 Regionalization also has several limitations. These include: for the patients (loss of continuity with primary physician, preference for local care), for low-volume hospitals (closure of related services, unfair stigmatization, and financial viability) and for high-volume hospitals (inability to increase capacity and maintain quality). Because of these limitations, it is more important to identifying the underlying reasons for this ubiquitous volume-outcome relationship. Hospital volume is, in fact, only a proxy for unmeasured variation in structural features and processes of care (38, 39). Finally, the volume-outcome relationship is well recognized to be an imperfect relationship (38, 40-45). The large majority of studies published are observational and based on administrative data and therefore they cannot establish a causative relationship, but rather can only demonstrate an association. These studies are not prospective experimental studies, but most are descriptive reports based on administrative data collected for non-research purposes. Part of the variation in outcomes likely reflects differences in case mix, coding of coexisting conditions, and thresholds for diagnostic testing in addition to differences in the quality of care (38). Specific to cancer treatment, the volume-outcome relationship seems to exist primarily for more complex and less frequently performed procedures (16, 27, 46, 47) suggesting that regionalization is not the appropriate approach for the improving quality in the surgical management of common types of cancers, such as CRC. Most importantly, aside from regionalization, these studies suggest no actionable quality of care strategies to improve outcomes in both high- and low-volume hospitals. Several studies have shown that surgical services with lower than expected riskadjusted mortality had higher quality of care, better resources and more effective processes for 14

25 coordinating surgical care (39, 43, 48), which emphasizes the importance of the underlying structures and processes of care. Exploring Quality of Care Why does variation exist? Although much has been published on variation in patient outcomes, and on the relationship between volume and outcome, the fact that variation has been identified provides an opportunity to assess and improve the overall quality of care in colorectal cancer surgery. Avedis Donabedian described the conceptual model that is most often used to study and understand quality of care: structure, process and outcomes (49). Structure refers to the attributes of the settings in which care occurs, including attributes of material resources (facilities, equipment and money), human resources (number and qualifications of personnel), and organizational structure (medical staff organization, methods of peer review and methods of reimbursement). Process denotes what is actually done in giving and receiving care, including the patient s activities in seeking care as well as the practitioner s activities in making a diagnosis and recommending or implementing treatment. Outcome denotes the effects of heath care on the health status of patients and populations. While there is a large body of research on variations in the outcomes of surgical care, and of cancer surgery in particular, there is very little information on the structures and processes of care that are associated with improved outcomes. 15

26 Figure 2: Examples of Structures, Processes and Outcomes in the Donabedian Model (49) A deeper understanding of structures and processes might potentially enable health care providers and managers to improve outcomes. By deconstructing the relationships between structures, processes and outcomes, we may be able to discover the factors that are most strongly associated with outcome, and understand where to focus quality improvement and research. Very few studies have approached the problem of variation in outcomes using the Donabedian model. A recent study by Itani et al (43) took this approach to explore the episode of care for patients undergoing colorectal surgery in Veterans Affairs (VA) hospitals with higher than expected mortality rates. This study investigated structures and processes of care contributing the higher mortality rate in patients undergoing elective colorectal surgery in 8 VA hospitals. The results reported that volume was not correlated to mortality, and uncovered that the higher 16

27 mortality in these centres was due in part to delay in diagnosis or surgery, suboptimal surgical procedure or system issues, emphasizing that it was in fact the variation in underlying structures and processes that resulted in the higher hospital mortality. Another study, published in 2009, evaluated the association between hospital volume and hospital clinical resources (50). This study was based on the hypothesis that clinical support of the surgeon is important in achieving optimal outcomes in pancreatic resection. 434 U.S. hospitals performing pancreatic resections were included in the study. The results, which evaluated several structures including ICU staffing, association with a residency program and presence of interventional radiology, showed that hospital volume predicted the presence of the clinical resources available. In summary, there is a paucity of studies which explore non-volume related hospital-level structural variation, and therefore a lack of information on how this variation impacts patient outcomes (51). Specifically in Ontario, variability in the type of surgery and the outcomes of surgery is well established; however, we have not identified clear and consistent factors that are responsible for this variation and little is known about variation in relevant structures of care in hospitals performing CRC surgery across the province. Using the available administrative data, we can describe hospital-level structural variability and explore the impact of this variability on patient outcomes. Examining processes of care at the hospital-level requires a large amount of prospective data collection. Therefore, by first identifying structural variables that are either highly variable or that have a significant impact on patient outcomes we will be able to determine, in the future, areas on which to focus to investigate the underlying processes related to these structures. 17

28 Hospital-level structures of interest Specific to CRC surgery, few structures have been described or investigated with respect to their impact on outcomes. However, because of the complex pathway of care of a colorectal surgery patient (especially one who has complications), it is likely that the presence or absence of certain structures has an impact on patient outcomes. We developed an inventory of hospital-level structures of interest based on the limited current literature and also through discussion with 4 surgeon scientists with familiarity of the available administrative data in Ontario. We also reviewed the results of a recent qualitative study that conducted interviews with 44 surgical care leaders and members of the surgical team at 6 National Surgical Quality Improvement Program (NSQIP) hospitals (52). Because of our use of administrative data, we could not investigate the many processes of care identified in this study; however, several of our identified structures were consistent with the results of their interviews, including access to certain types of anesthesia services, affiliation with a university, ICU characteristics and availability of technology and equipment. Through our literature review, we identified access to these additional hospital-level structures as structures of interest: MRI, certain types of Anesthesia services, ICU characteristics (presence of a Level 3 ICU Unit, closed model of care), availability of a high-volume surgeon and affiliation with a university. Pre-operative MRI for rectal cancer is postulated to have several benefits (53). It allows for preoperative classification of patients into different risk groups for local recurrence, which allows 18

29 for individualized planning for neoadjuvant treatment. Pre-operative MRI can provide a more accurate anatomical road map for the surgeon, allowing for superior operative planning. It has also been suggested that MRI can be a tool for quality assurance to assess surgical performance when the imaging is reviewed with the histological assessment of the resection specimen (53). Access to specialized anesthesia services may also affect several patient outcomes following surgery. Preoperative anesthesia consultations differ from the routine in-hospital pre-operative evaluation by the responsible anesthesiologist and may improve patient outcomes. This preoperative consultation provides an opportunity to document co morbid disease, to order appropriate pre-operative investigations and to optimize pre-existing medical conditions. A single study has evaluated the relationship of pre-operative consultation and 30-day mortality and found no significant relationship (54). There was, however, a significant reduction in mean hospital length of stay (-0.35 days, 95% CI , P <0.001) associated with pre-operative anesthesia consultation. However, these data were collected and analyzed at the patient level, not at the hospital level, therefore confounding by indication limited the evaluation of this association. We hypothesized that the availability of these services at the hospital level was important because it may be reflective of an important subgroup of available anesthesia-related structures and processes of care. More importantly, access to these services would have been available had a patient required it. Rates of epidural catheter use have also been previously been evaluated and found to be non-significant in relation to post-operative death (55). However, the relationship of epidural anesthesia to other short term outcomes, specifically in CRC patients, such as readmission, reoperation and return to emergency department has yet to be evaluated. 19

30 Evidence from a recent meta-analysis (56) suggests that an ICU model of care that includes the input of a physician trained and experienced in critical care (an intensivist ) is associated with improved patient and hospital outcomes. This type of model is termed closed. In the closed model, improvements are evident in reduced complications, lower hospital mortality, reduced lengths of stay in the ICU and the hospital, and lower costs due to reduced stays. Although these data exist, recent U.S. (48) and Canadian surveys (57) have found there is still variation in the model of ICU care and many hospitals still have open-model ICUs. Care provided by either a high volume surgeon or a surgeon specialist has been found to be associated with lower patient mortality rates (58) as well as with lower rates of local recurrence and higher disease-specific survival (15). A review of the impact of cancer care provided by specialized clinicians (59) also found that, though there were many methodological flaws in the available literature, care provided by specialized clinicians appeared to lead to lower mortality and greater adherence to process indicators such as appropriate staging and improved cancer pain management. We hypothesized that availability of a high-volume surgeon at the hospital level was important because of several reasons: First, this surgeon may serve as a resource in the operating room during complex cases or may assist in surgical decision making at the hospital. In addition, the presence of a higher-volume surgeon may also be reflective of other available structures and processes of care important in the optimal treatment of CRC. Finally, there is conflicting evidence about hospital affiliation with a university. A study evaluating data from 373 general non-federal hospitals in the U.S. found that intestinal cancer patients undergoing surgery at a hospital with significant teaching responsibility were 3.87% less 20

31 likely to die in hospital as compared to patients in non-medical school affiliated hospitals (58). A study by Kingston et al (60) in 1991 evaluated the care of 578 patients by community surgeons interested in colorectal cancer compared with university care and found no benefit from university care. A more recent 2001 study comparing NSQIP data in teaching and non-teaching hospitals found no differences in risk-adjusted morality and, in fact, higher risk-adjusted morbidity in teaching hospitals (61). To complete our list of structures of care of interest, we sought the opinions of 4 expert surgeon scientists. These clinicians were solicited to determine relevant structures of care that could feasibly be measured using the data available. These experts met, reviewed potential measures identified based on expert opinion and a literature review, and reached consensus regarding appropriate structures of care for evaluation in this thesis. The following additional structures of care were identified in this manner: CT imaging, interventional radiology, colonoscopy, Cardiology services, Thoracic and/or Vascular surgery services and urban or rural status. Availability of interventional radiology procedures has not previously been explored in the literature specifically in relation to CRC surgery outcomes, however, our group hypothesized that the availability of such services signifies a certain capacity for non-surgical interventions. A recent study exploring system clinical resources in pancreatic resection (50) also identified access to interventional radiology as a structure of interest and found it to be associated with statistically significant lower mortality (3.4% vs. 13.2%, P<.0001). 21

32 Rationale Colorectal Cancer is a common disease and most patients who are diagnosed with this disease undergo surgery. Variation exists in the surgical treatment and the outcomes following colorectal cancer surgery, both in the world published literature and, more specifically, in Ontario. Although volume has been shown to be related to outcomes, very little has been done to study the underlying structures and processes of care likely to be responsible for this relationship. By studying structures of care, we may be able to identify the underlying structures of care which may be responsible for the differences in patient outcomes. Objectives The general objective of this project is to explore the relationships between hospital structures of care and outcomes of CRC surgery. The Specific Aims are to: 1) Describe the structures of care of interest that are identifiable in administrative data for CRC surgery in Ontario; 2) Describe the variability of structures of care across Ontario hospitals; and 3) Model relationships between structures of care and post operative outcomes 22

33 Methods Overview A retrospective cohort study was performed at the Institute for Clinical Evaluative Sciences (ICES). We collected information on all patients in Ontario who underwent CRC surgery between We then collected patient-level covariates and information on hospital-level structures of care. To create the patient cohort, information was obtained from the Ontario Cancer Registry (OCR) and the following linked administrative databases: the Canadian Institutes of Health Information Discharge Abstract Database (CIHI-DAD), the Ontario Health Insurance Plan (OHIP), the ICES physician database (IPDB), the Registered Persons Database (RPDB) and the National Ambulatory Care Reporting System (NACRS). Research Ethics Board (REB) approval for this study was obtained from the University of Toronto, Sunnybrook Health Sciences Centre and was also approved by the Privacy Officer and C.E.O. at the Institute for Clinical and Evaluative Sciences (ICES). Data sources 1. The Ontario Cancer Registry (OCR) This provincial cancer registry is maintained by Cancer Care Ontario. The OCR collects information on all incident cancers in the province. The Ontario Cancer Act, originally passed in 1943, included provision for 'the adequate reporting of cancer cases and the recording and compilation of data'. Under this act, all hospitals are required to report cancer diagnoses to the registry. Widespread registration of cancer cases into the OCR began in 1972, and the registry includes data on cancer incidence, mortality, and cause of death as well as some patient-level data. Data are estimated to be 95% complete for incident cases (62). The OCR receives 23