domingo, 12 de julio de 2015

Colorectal Cancer Identification Methods Among Kansas Medicare Beneficiaries, 2008–2010

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Colorectal Cancer Identification Methods Among Kansas Medicare Beneficiaries, 2008–2010

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Colorectal Cancer Identification Methods Among Kansas Medicare Beneficiaries, 2008–2010



Sue-Min Lai, PhD, MS, MBA; Jessica Jungk, MS, MPH; Sarma Garimella, MBBS, MPH

Suggested citation for this article: Lai S, Jungk J, Garimella S. Colorectal Cancer Identification Methods Among Kansas Medicare Beneficiaries, 2008–2010. Prev Chronic Dis 2015;12:140543. DOI:http://dx.doi.org/10.5888/pcd12.140543.
PEER REVIEWED

Abstract

Introduction
Population-based data are limited on how often colorectal cancer (CRC) is identified through screening or surveillance in asymptomatic patients versus diagnostic workup for symptoms. We developed a process for assessing CRC identification methods among Medicare-linked CRC cases from a population-based cancer registry to assess identification methods (screening/surveillance or diagnostic) among Kansas Medicare beneficiaries.
Methods
New CRC cases diagnosed from 2008 through 2010 were identified from the Kansas Cancer Registry and matched to Medicare enrollment and claims files. CRC cases were classified as diagnostic-identified versus screening/surveillance-identified using a claims-based algorithm for determining CRC test indication. Factors associated with screening/surveillance-identified CRC were analyzed using logistic regression.
Results
Nineteen percent of CRC cases among Kansas Medicare beneficiaries were screening/surveillance-identified while 81% were diagnostic-identified. Younger age at diagnosis (65 to 74 years) was the only factor associated with having screening/surveillance-identified CRC in multivariable analysis. No association between rural/urban residence and identification method was noted.
Conclusion
Combining administrative claims data with population-based registry records can offer novel insights into patterns of CRC test use and identification methods among people diagnosed with CRC. These techniques could also be extended to other screen-detectable cancers.
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Introduction

Colorectal cancer (CRC) is the third most common cancer and third leading cause of cancer death in Kansas (1). In 2002, the US Preventive Services Task Force (USPSTF) strongly recommended that people aged 50 years or older be screened for CRC on the basis of evidence that screening is effective in reducing CRC mortality rates (2,3). As a result of this recommendation, CRC screening has been widely promoted by many groups, including the National Cancer Institute, the Centers for Disease Control and Prevention (CDC), and the American Cancer Society (ACS). Use of CRC tests among US adults has been increasing (4–6). From 2000 to 2010, the percentage of US adults aged 50 to 75 receiving any CRC screening test within recommended intervals increased from 38.6% to 59.1% (4,7). At the same time, CRC incidence has been declining and the proportion of cases diagnosed at a localized stage has been increasing, trends attributed to a combination of risk-factor reduction and increased screening rates (8). However, CRC screening rates still lag behind those for other effective cancer screening tests. In 2010, less than half of CRC cases were diagnosed at a localized stage in both Kansas (41%) and the United States (39%) (1,7,9). Although CRC screening is promoted as a key tool for improving CRC outcomes, few data are available on how often CRC cases are identified through screening or surveillance in asymptomatic patients versus diagnostic workup for symptoms, particularly at the population level. Documenting trends in CRC identification methods could provide additional insight into the contributions of screening to CRC prevention and morbidity reduction. In addition, analyses of patient and tumor characteristics by identification method could identify population subgroups not benefiting from CRC screening and tumor subgroups not amenable to identification by screening. We sought to explore the circumstances leading to the identification of CRC, to examine relationships between identification method and patient and tumor characteristics, and to develop a process for assessing CRC identification methods among Medicare-linked CRC cases from a population-based cancer registry.

Acknowledgments

This project was supported by the Kansas Department of Health and Environment and the National Program of Cancer Registries from CDC agreement no. U58/DP003889.
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Author Information

Corresponding Author: Sue-Min Lai, PhD, MS, MBA, Kansas Cancer Registry, Department of Preventive Medicine and Public Health, University of Kansas Medical Center, Mail Stop 1008, 3901 Rainbow Blvd, Kansas City, KS 66160-7313. Telephone: 913-588-2744. Email: slai@kumc.edu.
Author Affiliations: Jessica Jungk, Sarma Garimella, Kansas Cancer Registry, Department of Preventive Medicine and Public Health, University of Kansas Medical Center, Kansas City, Kansas.
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References

  1. Kansas Cancer Registry. Multiple year report, cancer incidence in Kansas 2001–2010. http://www.kumc.edu/kcr/reports.aspx. Accessed October 1, 2014.
  2. US Preventive Services Task Force. Screening for colorectal cancer: recommendation and rationale. Ann Intern Med 2002;137(2):129–31. CrossRef PubMed
  3. Pignone M, Saha S, Hoerger T, Mandelblatt J. Cost-effectiveness analyses of colorectal cancer screening: a systematic review for the US Preventive Services Task Force. Ann Intern Med 2002;137(2):96–104. CrossRef PubMed
  4. Klabunde CN, Cronin KA, Breen N, Waldron WR, Ambs AH, Nadel MR. Trends in colorectal cancer test use among vulnerable populations in the United States. Cancer Epidemiol Biomarkers Prev 2011;20(8):1611–21. CrossRef PubMed
  5. Centers for Disease Control and Prevention. Cancer screening — United States, 2010. MMWR Morb Mortal Wkly Rep 2012;61(3):41–5. PubMed
  6. Shapiro JA, Klabunde CN, Thompson TD, Nadel MR, Seeff LC, White A. Patterns of colorectal cancer test use, including CT colonography, in the 2010 National Health Interview Survey. Cancer Epidemiol Biomarkers Prev 2012;21(6):895–904. CrossRef PubMed
  7. American Cancer Society. Cancer prevention and early detection facts and figures 2013. Atlanta (GA): American Cancer Society; 2013.
  8. Edwards BK, Ward E, Kohler BA, Eheman C, Zauber AG, Anderson RN, et al. Annual report to the nation on the status of cancer, 1975–2006, featuring colorectal cancer trends and impact of interventions (risk factors, screening, and treatment) to reduce future rates. Cancer 2010;116(3):544–73. CrossRef PubMed
  9. Howlader N, Noone AM, Krapcho M, Garshell J, Neyman N, Altekruse SF, et al. , editors. SEER Cancer Statistics Review, 1975–2010. Bethesda (MD): National Cancer Institute; 2013. http://seer.cancer.gov/csr/1975_2010. Accessed October 15, 2013.
  10. Ko CW, Dominitz JA, Neradilek M, Polissar N, Green P, Kreuter W, et al. Determination of colonoscopy indication from administrative claims data. Med Care 2014;52(4):e21–9. Published online March 23, 2012. CrossRef PubMed
  11. Klabunde CN, Legler JM, Warren JL, Baldwin LM, Schrag D. A refined comorbidity measurement algorithm for claims-based studies of breast, prostate, colorectal, and lung cancer patients. Ann Epidemiol 2007;17(8):584–90. CrossRef PubMed
  12. SEER-Medicare: calculation of comorbidity weights. Bethesda (MD): National Cancer Institute. http://healthservices.cancer.gov/seermedicare/program/comorbidity.html. Accessed March 1, 2013.
  13. RUCA Zip code approximation. Seattle (WA): Rural Health Research Center, University of Washington. http://depts.washington.edu/uwruca/ruca-download.php. Accessed March 1, 2013.
  14. Amri R, Bordeianou LG, Sylla P, Berger DL. Impact of screening colonoscopy on outcomes in colon cancer surgery. JAMA Surg 2013;148(8):747–54. CrossRef PubMed
  15. McConnell YJ, Inglis K, Porter GA. Timely access and quality of care in colorectal cancer: are they related? Int J Qual Health Care 2010;22(3):219–28. CrossRef PubMed
  16. Cancer Patient Data Program. SEER 1997: Seattle case completeness and data validity audit [review]. San Francisco (CA): University of California, San Francisco; 1998.
  17. National Program of Cancer Registries data quality evaluation: Kansas Cancer Registry. Atlanta (GA): National Program of Cancer Registries, Centers for Disease Control and Prevention; 2010.
  18. Schenck AP, Klabunde CN, Warren JL, Peacock S, Davis WW, Hawley ST, et al. Data sources for measuring colorectal endoscopy use among Medicare enrollees. Cancer Epidemiol Biomarkers Prev 2007;16(10):2118–27. CrossRef PubMed
  19. Nattinger AB, Schapira MM, Warren JL, Earle CC. Methodological issues in the use of administrative claims data to study surveillance after cancer treatment. Med Care 2002;40[supplement]:IV–69–IV–74. PubMed
  20. US Preventive Services Task Force. Screening for colorectal cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med 2008;149(9):627–37. CrossRefPubMed
  21. Wee CC, McCarthy EP, Phillips RS. Factors associated with colon cancer screening: the role of patient factors and physician counseling. Prev Med 2005;41(1):23–9. CrossRef PubMed
  22. Guerra CE, Schwartz JS, Armstrong K, Brown JS, Halbert CH, Shea JA. Barriers of and facilitators to physician recommendation of colorectal cancer screening. J Gen Intern Med 2007;22(12):1681–8. CrossRef PubMed
  23. Klabunde CN, Schenck AP, Davis WW. Barriers to colorectal cancer screening among Medicare consumers. Am J Prev Med 2006;30(4):313–9. CrossRef PubMed

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