title: Colorectal Cancer Identification Methods Among Kansas Medicare Beneficiaries, 2008-2010.
abstract: BACKGROUND
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: 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. Email: slai@kumc.edu.
authors.forename: Sue-Min
authors.initials: SM
authors.lastname: Lai
authors.affiliation: Kansas Cancer Registry, Department of Preventive Medicine and Public Health, University of Kansas Medical Center, Kansas City, Kansas.
authors.forename: Jessica
authors.initials: J
authors.lastname: Jungk
authors.affiliation: Kansas Cancer Registry, Department of Preventive Medicine and Public Health, University of Kansas Medical Center, Kansas City, Kansas.
authors.forename: Sarma
authors.initials: S
authors.lastname: Garimella
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003113:Colonoscopy / Q000379:methods*; D015179:Colorectal Neoplasms / Q000175:diagnosis* / Q000453:epidemiology / Q000473:pathology; D055088:Early Detection of Cancer / Q000379:methods*; D005006:Ethnicity / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data; D007615:Kansas / Q000453:epidemiology; D016015:Logistic Models; D008297:Male; D008403:Mass Screening / Q000379:methods; D016344:Medicare Part A / Q000706:statistics & numerical data*; D016345:Medicare Part B / Q000706:statistics & numerical data*; D015999:Multivariate Analysis; D009367:Neoplasm Staging; D010043:Outcome and Process Assessment, Health Care; D011159:Population Surveillance; D011314:Preventive Health Services / Q000706:statistics & numerical data; D012042:Registries; D012424:Rural Population / Q000706:statistics & numerical data; D018426:SEER Program; D012959:Socioeconomic Factors; D014481:United States; D014505:Urban Population / Q000706:statistics & numerical data