External validation of a claims-based algorithm for classifying kidney-cancer surgeries
<p>Abstract</p> <p>Background</p> <p>Unlike other malignancies, there is no literature supporting the accuracy of medical claims data for identifying surgical treatments among patients with kidney cancer. We sought to validate externally a previously published Medicare-...
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doaj-a3c1a96ebfca44868c6b577953b79f992020-11-24T22:17:23ZengBMCBMC Health Services Research1472-69632009-06-01919210.1186/1472-6963-9-92External validation of a claims-based algorithm for classifying kidney-cancer surgeriesDeapen DennisLeventhal MerylWarren Joan LSaigal Christopher SMiller David CBanerjee MousumiLai JulieHanley JanLitwin Mark S<p>Abstract</p> <p>Background</p> <p>Unlike other malignancies, there is no literature supporting the accuracy of medical claims data for identifying surgical treatments among patients with kidney cancer. We 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, we compared procedure assignments based on Medicare claims with the type of surgery specified in SEER registry data and clinical operative reports.</p> <p>Methods</p> <p>Using linked SEER-Medicare data, we 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, we determined the agreement between the claims algorithm and the medical record. Finally, using the medical record as the reference-standard, we calculated the sensitivity, specificity, and positive and negative predictive values of the claims algorithm.</p> <p>Results</p> <p>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%, κ = 0.69, 95% CI 0.66 – 0.71). The two data sources demonstrated 97% agreement for classification of partial versus radical nephrectomy (κ = 0.83, 95% CI 0.81 – 0.86). We 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.</p> <p>Conclusion</p> <p>Medicare claims represent an accurate data source for ascertainment of population-based patterns of surgical care among patients with early-stage kidney cancer.</p> http://www.biomedcentral.com/1472-6963/9/92 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Deapen Dennis Leventhal Meryl Warren Joan L Saigal Christopher S Miller David C Banerjee Mousumi Lai Julie Hanley Jan Litwin Mark S |
spellingShingle |
Deapen Dennis Leventhal Meryl Warren Joan L Saigal Christopher S Miller David C Banerjee Mousumi Lai Julie Hanley Jan Litwin Mark S External validation of a claims-based algorithm for classifying kidney-cancer surgeries BMC Health Services Research |
author_facet |
Deapen Dennis Leventhal Meryl Warren Joan L Saigal Christopher S Miller David C Banerjee Mousumi Lai Julie Hanley Jan Litwin Mark S |
author_sort |
Deapen Dennis |
title |
External validation of a claims-based algorithm for classifying kidney-cancer surgeries |
title_short |
External validation of a claims-based algorithm for classifying kidney-cancer surgeries |
title_full |
External validation of a claims-based algorithm for classifying kidney-cancer surgeries |
title_fullStr |
External validation of a claims-based algorithm for classifying kidney-cancer surgeries |
title_full_unstemmed |
External validation of a claims-based algorithm for classifying kidney-cancer surgeries |
title_sort |
external validation of a claims-based algorithm for classifying kidney-cancer surgeries |
publisher |
BMC |
series |
BMC Health Services Research |
issn |
1472-6963 |
publishDate |
2009-06-01 |
description |
<p>Abstract</p> <p>Background</p> <p>Unlike other malignancies, there is no literature supporting the accuracy of medical claims data for identifying surgical treatments among patients with kidney cancer. We 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, we compared procedure assignments based on Medicare claims with the type of surgery specified in SEER registry data and clinical operative reports.</p> <p>Methods</p> <p>Using linked SEER-Medicare data, we 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, we determined the agreement between the claims algorithm and the medical record. Finally, using the medical record as the reference-standard, we calculated the sensitivity, specificity, and positive and negative predictive values of the claims algorithm.</p> <p>Results</p> <p>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%, κ = 0.69, 95% CI 0.66 – 0.71). The two data sources demonstrated 97% agreement for classification of partial versus radical nephrectomy (κ = 0.83, 95% CI 0.81 – 0.86). We 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.</p> <p>Conclusion</p> <p>Medicare claims represent an accurate data source for ascertainment of population-based patterns of surgical care among patients with early-stage kidney cancer.</p> |
url |
http://www.biomedcentral.com/1472-6963/9/92 |
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