title: Development of a claims-based algorithm to identify colorectal cancer recurrence.
abstract: OBJECTIVE
  To examine the validity of claims data to identify colorectal cancer (CRC) recurrence and determine the extent to which misclassification of recurrence status affects estimates of its association with overall survival in a population-based administrative database.
  
  
  METHODS
  We calculated the accuracy of claims data relative to medical records from one large tertiary hospital to identify CRC recurrence. We estimated the effect of misclassifying recurrence on survival by applying these findings to the linked Surveillance, Epidemiology, and End Results-Medicare data.
  
  
  RESULTS
  Of 174 eligible CRC patients identified through medical records, 32 (18.4%) had a recurrence. A claims-based algorithm of secondary malignancy codes yielded a sensitivity of 81% and specificity of 99% for identifying recurrence. Agreement between data sources was almost perfect (kappa: 0.86). In a model unadjusted for misclassification, CRC patients with recurrence were 3.04 times (95% confidence interval: 2.92-3.17) more likely to die of any cause than those without recurrence. In the corrected model, CRC patients with recurrence were 3.47 times (95% confidence interval: 3.06-4.14) more likely to die than those without recurrence.
  
  
  CONCLUSIONS
  Identifying recurrence in CRC patients using claims data is feasible with moderate sensitivity and high specificity. Future studies can use this algorithm with Surveillance, Epidemiology, and End Results-Medicare data to study treatment patterns and outcomes of CRC patients with recurrence.
authors: Division of General Medical Sciences, Department of Medicine, School of Medicine, Washington University in St. Louis, St. Louis, MO. Electronic address: adeshpan@dom.wustl.edu.
authors: Anjali D
authors: AD
authors: Deshpande
authors: Department of Epidemiology, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO.
authors: Mario
authors: M
authors: Schootman
authors: Department of Epidemiology, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO.
authors: Allese
authors: A
authors: Mayer
mesh_terms: D000368:Aged; D000465:Algorithms; D015179:Colorectal Neoplasms / Q000453:epidemiology* / Q000401:mortality; D005260:Female; D006801:Humans; D007345:Insurance Claim Review / Q000592:standards; D008297:Male; D012008:Recurrence; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Claims-based algorithm; Colorectal cancer; Misclassification; Recurrence