PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Cancer. Author manuscript; available in PMC Jun 15, 2011.
Published in final edited form as:
PMCID: PMC2889919
NIHMSID: NIHMS189700
Association of Local Capacity for Endoscopy with Individual Use of Colorectal Cancer Screening and Stage at Diagnosis
Jennifer S. Haas, MD, MSPH, Phyllis Brawarsky, MPH, Aarthi Iyer, MPH, Garrett M. Fitzmaurice, ScD, Bridget A. Neville, MPH, Craig Earle, MD MSc FRCP(C), and Celia Patricia Kaplan, DrPH, MA
Jennifer S. Haas, Division of General Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School;
Address Correspondence: Dr. Jennifer Haas, Division of General Medicine and Primary Care, Brigham and Women’s Hospital, 1620 Tremont Street, Boston, MA 02120-1613. Telephone: 617-525-6652. Fax: 617-732-7072. jhaas/at/partners.org
Background
Limited capacity for endoscopy in areas where African-Americans and Hispanics live may be a reason for persistent disparities in colorectal cancer (CRC) screening and stage at diagnosis.
Methods
We linked data from the National Health Interview Survey (NHIS) on the use of CRC screening and data from SEER-Medicare on CRC stage with measures of county capacity for colonoscopy and sigmoidoscopy (“endoscopy”) derived from Medicare claims.
Results
Hispanics lived in counties with less capacity for endoscopy than African-Americans or whites (for NHIS, an average of 1,224, 1,569, and 1,628 procedures per 100,000 individuals age 50 and above respectively). Individual use of CRC screening increased modestly as county capacity increased. For example, as the number of endoscopies per 100,000 residents increased by 750, the odds of being screened increased by 4%. Disparities in screening were mitigated or diminished by adjustment for area endoscopy capacity, racial/ ethnic composition, and socioeconomic status. Similarly, among individuals with CRC, those who lived in counties with less endoscopy capacity were marginally less likely to be diagnosed at an early stage. Adjustment for area characteristics diminished disparities in stage for Hispanics compared to whites but not African-Americans.
Conclusions
Increasing the use of CRC screening may require interventions to improve capacity for endoscopy in some areas. The characteristics of the area where an individual resides may in part mediate disparities in CRC screening use for both African-Americans and Hispanics, and disparities in cancer stage for Hispanics.
Keywords: colorectal cancer, screening, disparities, regional variation
Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the United States US).1 Screening for CRC is firmly established to reduce CRC mortality, both by decreasing incidence and by detecting cancers at an earlier, more treatable stage.2 It is therefore widely endorsed by professional societies and expert panels for average-risk adults over the age of 50 years.37 Although there are several established options for CRC screening for average-risk persons age 50 and above, including fecal occult blood testing (FOBT), sigmoidoscopy and colonoscopy, CRC screening is underused,1, 810 and there is significant area-level variation in CRC screening.11 There are also important disparities in CRC screening by race/ ethnicity. Studies have consistently shown that African-Americans and Hispanics are less likely than whites to use CRC screening.1219 Population-based studies have also demonstrated that African-Americans present with later stage CRC than whites, in part because of disparities in the use of CRC screening.20
Colonoscopy is an increasingly important screening modality because it can be used to screen for, as well as remove, suspicious lesions, examines the entire colon, and is required as follow-up after all positive FOBT’s. In recognition of this importance, Medicare has covered screening colonoscopy for average-risk adults since 2001 (previously Medicare reimbursement was limited to FOBT and sigmoidoscopy for these beneficiaries). This change in coverage has led to a modest increase in the use of colonoscopy,2123 although coverage has not reduced disparities in use by race/ ethnicity.14, 23, 24 While there are several potential reasons that disparities have not diminished with this important policy change, one possibility is more limited capacity for colonoscopy in areas where African-Americans and Hispanics live.
The objective of our analysis was to examine whether capacity for CRC screening in an area where an individual resides is associated with use of CRC screening and stage at diagnosis; and whether racial/ ethnic disparities in the use of CRC screening and stage at diagnosis are reduced by controlling for the capacity of CRC screening and the sociodemographic characteristics of the area where an individual resides.
Data Sources
These analyses utilized several data sources: (1) the 2000 and 2003 National Health Interview Surveys (NHIS) were used to examine utilization of CRC screening; (2) the Surveillance, Epidemiology and End Results (SEER)-Medicare File, for cancers diagnosed 1998–2002, was used for analyses of stage at diagnosis; (3) Medicare claims data, specifically the 2000 National Claims History (NCH or Carrier File), and Outpatient File, collected by Centers for Medicare and Medicaid Services (CMS) were used to create a measure of county CRC capacity; and (4) the Area Resource File (ARF) was used to create measures of county primary care physician (PCP) capacity, racial/ ethnic composition and socio-economic status (SES). This study was reviewed and approved by the Institutional Review Board of Partners HealthCare.
NHIS, conducted by the National Center for Health Statistics of the Centers for Disease Control and Prevention (CDC), was used for the analyses of CRC screening use. NHIS is a nationally representative household survey that collects information about demographic characteristics, chronic health conditions, health insurance, and health behaviors from the civilian, non-institutionalized U.S. population (www.cdc.gov/nchs/nhis.htm). In 2000 and 2003, the NHIS included a Cancer Control Supplement, which asked respondents about the use of CRC screening.25 Because these analyses required merging NHIS with the area-level variables described below, all analyses were conducted through the Research Data Center of the National Center for Health Statistics.
SEER-Medicare data were used for analyses of stage at diagnosis. The SEER program collects information on all incident cancer cases for persons with cancer residing in SEER program areas (California, Connecticut, Hawaii, Iowa, Kentucky, Louisiana, New Jersey, New Mexico and Utah, rural Georgia, and the metropolitan areas of Detroit, Atlanta, and Seattle).26 SEER data include primary tumor site, stage at diagnosis, based on the modified American Joint Committee on Cancer (AJCC) staging system, and patient demographics and are linked to Medicare claims data by the National Cancer Institute. A restricted access version of these data was obtained so that the area-level characteristics could be appended.
Medicare claims, specifically the Carrier and Outpatient Files, for persons who had a screening sigmoidoscopy or colonoscopy were used to create aggregate measures of CRC screening capacity in the county where an individual resided. Data from the ARF was used to create a year 2000 county-level measure of PCP capacity and measures of area racial/ ethnic composition and SES. The ARF includes the number of physicians by specialty type and work setting in each county, the population by age in each county, the percentage of each county that is African-American and Hispanic and the median income for each county.
Study Subjects
For the analyses of screening utilization, we used the NHIS data and included adults age 50 and older, who had not previously been diagnosed with colorectal cancer, whose race/ethnicity was reported as white, African-American or Hispanic, and who responded to questions regarding the use of CRC screening (n=23,229).
For the analyses of cancer stage, we used the SEER-Medicare data and included adults age 65 to 95, whose race/ethnicity was reported as white, black or Hispanic and who were diagnosed with modified AJCC Stage I, II, III or IV CRC as a single primary from 1998 to 2002 (n= 52,317).
Variables
Individual Variables
In both the NHIS and SEER-Medicare samples, individual level variables included sex, age (10-year intervals), race/ ethnicity (white, African-American, Hispanic), marital status (married or living with a partner vs. other) and comorbidity. Comorbidity was measured slightly differently in the two datasets because of different data availability. In the NHIS dataset, participants were asked to endorse a variety of chronic conditions (e.g., arthritis, peptic ulcer disease, chronic lung disease). These were counted and categorized as 0, 1, 2, ≥ 3). For SEER-Medicare, claims data were used to calculate the modified Charlson comorbidity index (also categorized as 0, 1, 2, ≥ 3).27
Additional individual variables available in the NHIS included education (grade school or middle school, high school graduate or vocational school, some college, college graduate), prior history of cancer other than CRC, and health insurance (uninsured, Medicare with private supplemental insurance or private insurance, Medicare without supplemental coverage, and Medicaid or duel eligibility for Medicare and Medicaid). We also included health-care-seeking behavior, defined as having a usual source of care, evidenced by a visit to any health care professional in the past year, and the number of behavioral risk factors for CRC, including current cigarette use, heavy drinking (consuming 60 or more alcoholic drinks per month for men and 30 or more for women), and lack of regular exercise.28, 29
Additional individual-level independent variables in the SEER-Medicare dataset included whether an individual was of “low income” (based on eligibility for state assistance with Medicare premiums and co-payments), cancer type (colon, rectal), year of diagnosis, and an indicator of whether someone had non-continuous Medicare coverage or was in an HMO in the 13 months prior to diagnosis, in order to adjust for potentially incomplete data about chronic conditions for these individuals.
Area Variables
CRC Screening Capacity
To create a measure of regional capacity for CRC screening, we first selected records from the 2000 Carrier and Outpatient Files that included a bill for screening sigmoidoscopy (Health Care Common Procedure Coding System (HCPCS): G0104, or Current Procedural Terminology (CPT) codes: 45305, 45308, 45309, 45315, 45320, 45331) or screening colonoscopy (HCPCS: G0105, G0121; CPT: 45380, 45384, 45385).30 There were a total of 1,198,597 unique Carrier and Outpatient records (multiple records actually make up a claim) based on patient identifier, procedure code and date of procedure for the 50 United States. Claims for the same procedure within 7 days were considered to be duplicates for the same procedures and the duplicate claim was deleted (n=8,976). Next, we identified the performing physician and zip code from the Carrier File, or the facility and county from the Outpatient File. Carrier Files with missing zip codes or with incorrect zip codes and Outpatient Files without county were deleted (n = 2,757), for a total of 1,186,864 records. Physicians who performed a colonoscopy or sigmoidoscopy were assigned to a county using zip code. If a zip code crossed county lines, it was assigned to the county with the greatest percentage of its population. Approximately 85% of zip codes were wholly contained within one county. Finally, we tabulated the number of sigmoidoscopies and colonoscopies performed in each county. We defined the screening capacity of the county as the number of colonoscopies and sigmoidoscopies performed in the county, per 100,000 residents age 50 and older. This measure was merged to the SEER and NHIS datasets by county.
PCP Capacity
Because PCPs are typically a gateway to CRC screening, we used data from the ARF for the number of PCPs in each county, defined as office-based physicians practicing the specialties of general practice, family practice, general internal medicine, or obstetrics/gynecology.31 We then calculated the number of PCPs per 100,000 residents age 50 and above for each county as our measure of PCP capacity. This measure was merged to the SEER and NHIS datasets by county. There were 844 counties included in the NHIS sample and 463 in the SEER-Medicare sample.
Racial/ ethnic Composition and SES
For NHIS, we used data from the ARF for the county racial/ethnic composition, defined as the percentage of the county that was African-American and Hispanic, and county SES, measured by median household income. The same measures were used, but at the census tract level, for the SEER-Medicare data.
Outcome Variables
Use of CRC Screening
Respondents to the NHIS were asked several questions about their use of CRC screening. Our measure for the use of CRC screening was whether an individual reported that they had ever been screened for CRC, using FOBT, sigmoidoscopy or colonoscopy. In a secondary analysis, we also examined whether an individual’s CRC screening had been done with either a sigmoidoscopy or colonoscopy.
Stage at Diagnosis
Stage at diagnosis was defined using the AJCC classification method that is available in the SEER-Medicare data (categorized as stage I, II, III or IV).
Data Analysis
We used bivariate analyses to examine the associations of an individual’s race/ethnicity with demographic, area and outcome variables; chi-square tests and univariate linear regression models were used to determine statistical significance. To examine the effect of CRC screening capacity in an individual’s county of residence on individual screening, we constructed multi-level logistic regression models that accounted for clustering of individuals in the counties. To examine the effect of CRC screening capacity on stage at diagnosis, we constructed ordinal logistic regression models, clustered by county. In both sets of models, we included independent variables that we believed, a priori, could potentially affect the outcomes, based on our prior work and previous studies in the literature. The analyses of the NHIS also accounted for the survey sample weights. All area-level variables were modeled for a change of approximately 1 standard deviation (increments of 750 procedures per 100,000 individuals for CRC capacity, increments of 100 PCPs per 100,000 individuals, increments of 5% for the measures of racial/ ethnic composition, and increments of $20,000 for median household income). We tested correlations between the capacity measures and area racial/ethnic composition, and we tested for non-linear associations of both capacity measures with the outcomes by including a squared term for each measure in the models; in the model of CRC screening these quadratic trends were statistically discernable because of the large sample size but had a small magnitude of effect (e.g., odds ratio of 0.99) so, for ease of interpretation, the final models report only the linear trend. All analyses were done using SAS version 9.1 (SAS Institute, Cary, NC).
In order to examine whether area CRC screening or PCP capacity mediated any racial/ethnicity disparities in screening or stage at diagnosis, we built a sequence of models. First, we constructed models that included only individual-level variables. Specifically, the first CRC screening model included individual variables of age, sex, race, educational attainment, marital status, previous history of cancer, chronic conditions, behavioral risk factors for CRC, health insurance, usual source of care and whether the subject had a dental visit in the past year, and the year of the NHIS survey. The first stage at diagnosis model included the individual-level variables of age, sex, race, marital status, colon or rectal cancer, chronic conditions, whether an individual had ever been eligible for state buy-in insurance, and whether the individual was an HMO member or did not have Medicare for the 13 months prior to diagnosis, and year of diagnosis. For both outcomes, a second set of models added the measures of county CRC screening capacity, PCP capacity, and measures of the area racial/ ethnic and SES.
Description of the Study Samples
Subjects in both samples were predominately white (Table 1). In order to take into account the recommended starting age for CRC screening for average risk individuals, the age range was younger in the NHIS dataset (age 50 and older) than the SEER-Medicare dataset (age 65 and older). In both datasets, whites were older than African-Americans and Hispanics. In the NHIS dataset, whites were more likely to have graduated from college (24.0%), compared to African-Americans (13.7%) and Hispanics (9.2%). Educational attainment was not available in the SEER-Medicare dataset. In both samples, African-Americans had more comorbidity than whites and Hispanics. In the NHIS sample, Hispanics were most likely to be uninsured and were also least likely to have a usual place of care. Details of health insurance were not available in the SEER-Medicare data, although African-Americans and Hispanics were more likely to have eligibility for state buy-in coverage.
Table 1
Table 1
Description of study samples by race/ ethnicity.
Whites were most likely (54.3%) and Hispanics least likely (33.4%) to have ever been screened for CRC by any method. Among those screened, African-Americans were less likely to have had a sigmoidoscopy or colonoscopy, than whites or Hispanics. Whites and Hispanics were more likely to be diagnosed with CRC at an earlier stage than African-Americans (e.g., 17.7% of Hispanics, 17.0% of whites and 24.5% of African-Americans were diagnosed at stage IV).
Description of the Characteristics Where Subjects Reside
In both the NHIS and SEER-Medicare samples, African-Americans and Hispanics lived in counties with a greater number of PCP’s per 100,000 people than whites (Table 2). Conversely, Hispanics lived in counties with fewer CRC screening procedures per 100,000 people than either whites or African-Americans. African-Americans and Hispanics lived in areas where there were a higher percentage of individuals of the similar racial/ ethnic group. In both samples, African-Americans lived in areas with the lowest average household income and whites in areas with the highest. Measures of CRC screening capacity were not significantly correlated with measures of area race/ethnicity or SES.
Table 2
Table 2
Characteristics of Area of Residence
Use of CRC Screening
Overall, individual use of CRC screening increased modestly as county screening capacity increased (Table 3). For example, as the number of colonoscopies and sigmoidoscopies per 100,000 residents in the county age 50 and above increased by 750, the odds of being screened increased by 4%. There was no association between PCP capacity and screening. In the secondary analyses, where we examined whether an individual had ever been screened using sigmoidoscopy or colonoscopy, as opposed to having been screened by FOBT only, we found that an individual’s use of sigmoidoscopy or colonoscopy increased as county capacity for these procedures increased (OR 1.04, CI 1.02–1.07). PCP capacity was not associated with screening by sigmoidoscopy or colonoscopy. As the percentage of African-Americans or Hispanics in the county of residence increased, there was a modest decline in the use of CRC screening by the individuals who lived there. As the average household income of the county increased, use of screening increased.
Table 3
Table 3
Factors associated with Ever Being Screened for CRC, NHIS.
African-Americans were less likely than whites to have ever been screened for CRC after adjustment for individual-level variables (odds ratio (OR 0.87, 95% confidence interval (CI) 0.78–0.96). This disparity was mitigated by adjustment for area capacity for colonoscopy and sigmoidoscopy, capacity for PCPs, racial/ ethnic composition and SES (OR 0.93, CI 0.83–1.04). After adjustment for individual-level factors, Hispanics were also less likely than whites to be screened for CRC (0.68; 0.60–0.77). Although this disparity persisted, it was diminished 7% after accounting for differences in area characteristics.
Stage at Diagnosis
Among individuals with CRC, those who lived in counties with less CRC screening capacity were marginally less likely to be diagnosed at an early stage (OR 0.98, CI 0.97–1.00) (Table 4). Individuals with CRC who lived in counties with more PCPs were marginally more likely to be diagnosed at a later stage. As the household income of the area increased, diagnosis with late-stage CRC declined. There was no association between the racial/ ethnic composition of the area where an individual resided and stage at diagnosis.
Table 4
Table 4
Factors Associated with Later Stage Diagnosis of CRC, SEER-Medicare
After adjustment for individual-level factors, African-Americans were more likely to be diagnosed at a later stage of CRC than whites (odds ratio (OR) 1.38, 95% CI (CI) 1.30–1.46). This difference persisted, largely unchanged with adjustment for both area screening capacity and area demographic characteristics. After adjustment for individual factors, Hispanics were modestly more likely than whites to have a late stage diagnosis (OR 1.06, CI 1.00–1.13). However, further adjustment for area screening capacity and socioeconomic characteristics eliminated any differences between Hispanics and whites (OR1.02, CI 0.94–1.10).
These results suggest that individuals who live in counties with greater capacity for CRC screening are modestly more likely to receive screening and less likely to be diagnosed with late-stage CRC than individuals who live in counties with less capacity for CRC screening. There was no association between the capacity of PCPs and these outcomes. Adjustment for the characteristics of the area where an individual resides was associated with reduction of the racial/ ethnic disparities in CRC screening for both African-Americans and Hispanics compared to whites, and for late stage diagnosis of CRC for Hispanics compared to whites but not for African-Americans.
Prior work on the national level suggests that capacity for colonoscopy and sigmoidoscopy may limit the use of CRC screening,32, 33 and that there is substantial regional variation in the use of CRC screening.11, 30, 34 Studies of screening capacity in specific states demonstrate some variation in capacity for colonoscopy. A survey of endoscopy facilities in Montana found that capacity is adequate for current levels of screening but is not adequate to screen all eligible residents.35 A survey of endoscopy sites in New Hampshire found that demand for screening colonoscopy was twice the available capacity in 2002.36 Our work extends this literature by demonstrating that regional variation in CRC screening capacity is associated with regional variation in an individual’s use of screening and stage at diagnosis. This finding is important because it suggests that improving the availability of colonoscopy and sigmoidoscopy in areas with low capacity may result in some improvements in the use of CRC screening and stage of diagnosis for CRC, particularly at the population level. Similar work, examining the role of physician supply on stage of diagnosis for breast cancer in Florida, found that overall physician supply was not associated with stage, but found a modest association between the supply of primary care physicians and early stage breast cancer diagnosis.37
Prior work has also demonstrated substantial racial/ ethnic disparities in the use of CRC screening,10, 19, 38 that have persisted despite expanded coverage for colonoscopy by Medicare.17 Our results suggest that differences in the characteristics of the area where an individual resides may mediate some, but not all, of these disparities. The importance of the racial/ ethnic and sociodemographic characteristics of the area where one resides to the use of cancer-related care is supported by prior work.39 This suggests that interventions designed to reduce disparities in the use of CRC screening or stage at diagnosis should consider not only improving local capacity for screening but also address other characteristics of the areas that may limit the dissemination of information about the importance of CRC screening.
This work has several potential limitations. Our measure of CRC screening capacity was constructed using claims data. Thus it reflects actual practice patterns, not potential capacity. Prior work suggests current demand for colonoscopy exceeds or approaches potential capacity,36, 40 suggesting that our measure reflects capacity during the timeframe of this study. Use of colonoscopy in an area may be influenced by other factors beyond potential capacity of the providers, including the dissemination of information about the benefits of CRC screening. It is also possible that the lesser capacity for endoscopy may be in response to lesser demand, rather than the other way around, or that capacity is related to other factors such as regional variation in managed care market share which we did not assess. As our measure is derived from Medicare claims, it may underestimate total capacity, although prior work has shown strong correlation between measures based on Medicare claims alone compared to total utilization.41 Finally, we recognize potential biases inherent in the linkage of these various data sources, each defined by somewhat different time periods. Our estimate of the effect of CRC screening capacity on use of colonoscopy may therefore be conservative because migration of people into or out of geographic areas may decrease our ability to detect an association. A strength of this analysis is that we found consistent associations between endoscopy capacity and both use of screening and stage at diagnosis, measured in two different datasets.
Increasing the use of CRC screening may require interventions to improve capacity for colonoscopy and sigmoidoscopy in areas with lower utilization of these procedures. The characteristics of the area where an individual resides, including capacity for CRC screening, racial/ ethnic composition and socioeconomic status, may in part mediate racial/ ethnic disparities in CRC screening use for both African-Americans and Hispanics and disparities in late stage diagnosis for Hispanics.
Acknowledgment
Supported by grants from the American Cancer Society (RSGT CPHPS-114979) and the National Cancer Institute (R01 CA112451).
Contributor Information
Jennifer S. Haas, Division of General Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School.
Phyllis Brawarsky, Division of General Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital.
Aarthi Iyer, Division of General Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School.
Garrett M. Fitzmaurice, Laboratory for Psychiatric Biostatistics, McLean Hospital and Harvard Medical School.
Bridget A. Neville, Department of Medical Oncology, Dana-Farber Cancer Institute.
Craig Earle, Director, Health Services Research Program, Cancer Care Ontario and the Ontario Institute for Cancer Research.
Celia Patricia Kaplan, Medical Effectiveness Research Center, Division of General Internal Medicine, Department of Medicine University of California, San Francisco.
1. Cancer Facts and Figures. 2006. [Accessed April 1, 2006]. http://www.cancer.org/downloads/STT/CAFF2006PWSecured.pdf.
2. Levin B, Hess K, Johnson C. Screening for colorectal cancer. A comparison of 3 fecal occult blood tests. Arch Intern Med. 1997 May 12;157(9):970–976. [PubMed]
3. Screening for colorectal cancer: recommendation and rationale. Ann Intern Med. 2002 Jul 16;137(2):129–131. [PubMed]
4. Smith RA, Cokkinides V, Eyre HJ. American Cancer Society guidelines for the early detection of cancer, 2003. CA Cancer J Clin. 2003 Jan-Feb;53(1):27–43. [PubMed]
5. Winawer S, Fletcher R, Rex D, et al. Colorectal cancer screening and surveillance: clinical guidelines and rationale-Update based on new evidence. Gastroenterology. 2003 Feb;124(2):544–560. [PubMed]
6. Walsh J, Terdiman J. Colorectal cancer screening: scientific review. JAMA. 2003;289:1288–1296. [PubMed]
7. Pignone M, Rich M, Teutsch SM, Berg AO, Lohr KN. Screening for colorectal cancer in adults at average risk: a summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2002 Jul 16;137(2):132–141. [PubMed]
8. Levin B, Lieberman DA, McFarland B, et al. Screening and surveillance for the early detection of colorectal cancer and adenomatous polyps, 2008: a joint guideline from the American Cancer Society, the US Multi-Society Task Force on Colorectal Cancer, and the American College of Radiology. CA Cancer J Clin. 2008 May-Jun;58(3):130–160. [PubMed]
9. Shapiro JA, Seeff LC, Thompson TD, Nadel MR, Klabunde CN, Vernon SW. Colorectal cancer test use from the 2005 National Health Interview Survey. Cancer Epidemiol Biomarkers Prev. 2008 Jul;17(7):1623–1630. [PubMed]
10. Use of colorectal cancer tests--United States, 2002, 2004, and 2006. MMWR Morb Mortal Wkly Rep. 2008 Mar 14;57(10):253–258. [PubMed]
11. Kilmer G, Roberts H, Hughes E, et al. Surveillance of certain health behaviors and conditions among states and selected local areas--Behavioral Risk Factor Surveillance System (BRFSS), United States, 2006. MMWR Surveill Summ. 2008 Aug 15;57(7):1–188. [PubMed]
12. Cooper GS, Koroukian SM. Racial disparities in the use of and indications for colorectal procedures in Medicare beneficiaries. Cancer. 2004 Jan 15;100(2):418–424. [PubMed]
13. Shokar NK, Carlson CA, Weller SC. Prevalence of colorectal cancer testing and screening in a multiethnic primary care population. J Community Health. 2007 Oct;32(5):311–323. [PubMed]
14. Shih YC, Zhao L, Elting LS. Does Medicare coverage of colonoscopy reduce racial/ethnic disparities in cancer screening among the elderly? Health Aff (Millwood) 2006 Jul-Aug;25(4):1153–1162. [PubMed]
15. McAlearney AS, Reeves KW, Dickinson SL, et al. Racial differences in colorectal cancer screening practices and knowledge within a low-income population. Cancer. 2008 Jan 15;112(2):391–398. [PubMed]
16. Beydoun HA, Beydoun MA. Predictors of colorectal cancer screening behaviors among average-risk older adults in the United States. Cancer Causes Control. 2008 May;19(4):339–359. [PubMed]
17. Ananthakrishnan AN, Schellhase KG, Sparapani RA, Laud PW, Neuner JM. Disparities in colon cancer screening in the Medicare population. Arch Intern Med. 2007 Feb 12;167(3):258–264. [PubMed]
18. Pollack LA, Blackman DK, Wilson KM, Seeff LC, Nadel MR. Colorectal cancer test use among Hispanic and non-Hispanic U.S. populations. Prev Chronic Dis. 2006 Apr;3(2):A50. [PMC free article] [PubMed]
19. Ko CW, Kreuter W, Baldwin LM. Persistent demographic differences in colorectal cancer screening utilization despite Medicare reimbursement. BMC Gastroenterol. 2005;5:10. [PMC free article] [PubMed]
20. Clegg LX, Li FP, Hankey BF, Chu K, Edwards BK. Cancer survival among US whites and minorities: a SEER (Surveillance, Epidemiology, and End Results) Program population-based study. Arch Intern Med. 2002 Sep 23;162(17):1985–1993. [PubMed]
21. Prajapati DN, Saeian K, Binion DG, et al. Volume and yield of screening colonoscopy at a tertiary medical center after change in Medicare reimbursement. Am J Gastroenterol. 2003 Jan;98(1):194–199. [PubMed]
22. Harewood GC, Lieberman DA. Colonoscopy practice patterns since introduction of Medicare coverage for average-risk screening. Clin Gastroenterol Hepatol. 2004 Jan;2(1):72–77. [PubMed]
23. Phillips KA, Liang SY, Ladabaum U, et al. Trends in colonoscopy for colorectal cancer screening. Med Care. 2007 Feb;45(2):160–167. [PubMed]
24. Ko CW, Kreuter W, Baldwin LM. Effect of Medicare coverage on use of invasive colorectal cancer screening tests. Arch Intern Med. 2002 Dec 9–23;162(22):2581–2586. [PubMed]
25. Hiatt RA, Klabunde C, Breen N, Swan J, Ballard-Barbash R. Cancer screening practices from National Health Interview Surveys: past, present, and future. J Natl Cancer Inst. 2002 Dec 18;94(24):1837–1846. [PubMed]
26. Warren JL, Klabunde CN, Schrag D, Bach PB, Riley GF. Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. Med Care. 2002 Aug;40(8 Suppl) IV-3-18. [PubMed]
27. Klabunde CN, Potosky AL, Legler JM, Warren JL. Development of a comorbidity index using physician claims data. J Clin Epidemiol. 2000 Dec;53(12):1258–1267. [PubMed]
28. Thygesen LC, Wu K, Gronbaek M, Fuchs CS, Willett WC, Giovannucci E. Alcohol intake and colorectal cancer: a comparison of approaches for including repeated measures of alcohol consumption. Epidemiology. 2008 Mar;19(2):258–264. [PubMed]
29. Liang PS, Chen TY, Giovannucci E. Cigarette smoking and colorectal cancer incidence and mortality: systematic review and meta-analysis. Int J Cancer. 2009 May 15;124(10):2406–2415. [PubMed]
30. Cooper GS, Koroukian SM. Geographic variation among Medicare beneficiaries in the use of colorectal carcinoma screening procedures. Am J Gastroenterol. 2004 Aug;99(8):1544–1550. [PubMed]
31. Klabunde CN, Frame PS, Meadow A, Jones E, Nadel M, Vernon SW. A national survey of primary care physicians' colorectal cancer screening recommendations and practices. Prev Med. 2003 Mar;36(3):352–362. [PubMed]
32. Seeff LC, Manninen DL, Dong FB, et al. Is there endoscopic capacity to provide colorectal cancer screening to the unscreened population in the United States? Gastroenterology. 2004 Dec;127(6):1661–1669. [PubMed]
33. Vijan S, Inadomi J, Hayward RA, Hofer TP, Fendrick AM. Projections of demand and capacity for colonoscopy related to increasing rates of colorectal cancer screening in the United States. Aliment Pharmacol Ther. 2004 Sep 1;20(5):507–515. [PubMed]
34. Seeff LC, Richards TB, Shapiro JA, et al. How many endoscopies are performed for colorectal cancer screening? Results from CDC's survey of endoscopic capacity. Gastroenterology. 2004 Dec;127(6):1670–1677. [PubMed]
35. Ballew C, Lloyd BG, Miller SH. Capacity for colorectal cancer screening by colonoscopy, Montana, 2008. Am J Prev Med. 2009 Apr;36(4):329–332. [PubMed]
36. Butterly L, Olenec C, Goodrich M, Carney P, Dietrich A. Colonoscopy demand and capacity in New Hampshire. Am J Prev Med. 2007 Jan;32(1):25–31. [PubMed]
37. Ferrante JM, Gonzalez EC, Pal N, Roetzheim RG. Effects of physician supply on early detection of breast cancer. J Am Board Fam Pract. 2000 Nov-Dec;13(6):408–414. [PubMed]
38. Trivers KF, Shaw KM, Sabatino SA, Shapiro JA, Coates RJ. Trends in colorectal cancer screening disparities in people aged 50–64 years, 2000–2005. Am J Prev Med. 2008 Sep;35(3):185–193. [PubMed]
39. Haas JS, Earle CC, Orav JE, et al. Lower use of hospice by cancer patients who live in minority versus white areas. J Gen Intern Med. 2007 Mar;22(3):396–399. [PMC free article] [PubMed]
40. Hoffman RM, Stone SN, Herman C, et al. New Mexico's capacity for increasing the prevalence of colorectal cancer screening with screening colonoscopies. Prev Chronic Dis. 2005 Jan;2(1):A07. [PMC free article] [PubMed]
41. Schrag D, Panageas KS, Riedel E, et al. Surgeon volume compared to hospital volume as a predictor of outcome following primary colon cancer resection. J Surg Oncol. 2003 Jun;83(2):68–78. discussion 78-69. [PubMed]