External Validation of a Claims-Based Algorithm for Classifying Kidney-Cancer Surgeries

BACKGROUND: Unlike other malignancies, there is no literature supporting the accuracy of medical claims data for identifying surgical treatments among patients with kidney cancer. The authors sought to validate externally a previously published Medicare-claims-based algorithm for classifying surgical treatments among patients with early-stage kidney cancer. To achieve this aim, they compared procedure assignments based on Medicare claims with the type of surgery specified in SEER registry data and clinical operative reports. METHODS: Using linked SEER-Medicare data, the authors calculated the agreement between Medicare claims and SEER data for identification of cancer-directed surgery among 6,515 patients diagnosed with early-stage kidney cancer. Next, for a subset of 120 cases, they determined the agreement between the claims algorithm and the medical record. Finally, using the medical record as the reference-standard, the authors calculated the sensitivity, specificity, and positive and negative predictive values of the claims algorithm. RESULTS: Among 6,515 cases, Medicare claims and SEER data identified 5,483 (84.1%) and 5,774 (88.6%) patients, respectively, who underwent cancer-directed surgery (observed agreement = 93%, kappa = 0.69, 95% CI 0.66 - 0.71). The two data sources demonstrated 97% agreement for classification of partial versus radical nephrectomy (kappa = 0.83, 95% CI 0.81 - 0.86). The authors observed 97% agreement between the claims algorithm and clinical operative reports; the positive predictive value of the claims algorithm exceeded 90% for identification of both partial nephrectomy and laparoscopic surgery. CONCLUSION: Medicare claims represent an accurate data source for ascertainment of population-based patterns of surgical care among patients with early-stage kidney cancer.