{"id":6600,"date":"2016-08-10T00:00:00","date_gmt":"2016-08-10T04:00:00","guid":{"rendered":"https:\/\/icesontario.wpengine.com\/journal-articles\/application-of-recursive-partitioning-to-derive-and-validate-a-claims-based-algorithm-for-identifying-keratinocyte-carcinoma-nonmelanoma-skin-cancer\/"},"modified":"2023-06-14T20:11:22","modified_gmt":"2023-06-15T00:11:22","slug":"application-of-recursive-partitioning-to-derive-and-validate-a-claims-based-algorithm-for-identifying-keratinocyte-carcinoma-nonmelanoma-skin-cancer","status":"publish","type":"journal_article","link":"https:\/\/www.ices.on.ca\/fr\/publications\/journal-articles\/application-of-recursive-partitioning-to-derive-and-validate-a-claims-based-algorithm-for-identifying-keratinocyte-carcinoma-nonmelanoma-skin-cancer\/","title":{"rendered":"Application of recursive partitioning to derive and validate a claims-based algorithm for identifying keratinocyte carcinoma (nonmelanoma skin cancer)"},"content":{"rendered":"<p><strong>Importance<\/strong> &#x2014; Keratinocyte carcinoma (nonmelanoma skin cancer) accounts for substantial burden in terms of high incidence and healthcare costs but is excluded by most cancer registries in North America. Administrative health insurance claims databases offer an opportunity to identify these cancers using diagnosis and procedural codes submitted for reimbursement purposes.<\/p>\n<p><strong>Objective<\/strong> &#x2014; To apply recursive partitioning to derive and validate a claims-based algorithm for identifying keratinocyte carcinoma with high sensitivity and specificity.<\/p>\n<p><span class=\"bold\">Design, Setting, and Participants <\/span>&#x2014; Retrospective study using population-based administrative databases linked to 602&#x202f;371 pathology episodes from a community laboratory for adults residing in Ontario, Canada, from January 1, 1992, to December 31, 2009. The final analysis was completed in January 2016. We used recursive partitioning (classification trees) to derive an algorithm based on health insurance claims. The performance of the derived algorithm was compared with 5 prespecified algorithms and validated using an independent academic hospital clinic data set of 2082 patients seen in May and June 2011.<\/p>\n<p><span class=\"bold\">Main Outcomes and Measure <\/span>&#x2014; Sensitivity, specificity, positive predictive value, and negative predictive value using the histopathological diagnosis as the criterion standard. We aimed to achieve maximal specificity, while maintaining greater than 80% sensitivity.<\/p>\n<p><strong>Results <\/strong>&#x2014; Among 602&#x202f;371 pathology episodes, 131&#x202f;562 (21.8%) had a diagnosis of keratinocyte carcinoma. Our final derived algorithm outperformed the 5 simple prespecified algorithms and performed well in both community and hospital data sets in terms of sensitivity (82.6% and 84.9%, respectively), specificity (93.0% and 99.0%, respectively), positive predictive value (76.7% and 69.2%, respectively), and negative predictive value (95.0% and 99.6%, respectively). Algorithm performance did not vary substantially during the 18-year period.<\/p>\n<p><span class=\"bold\">Conclusions and Relevance <\/span>&#x2014; This algorithm offers a reliable mechanism for ascertaining keratinocyte carcinoma for epidemiological research in the absence of cancer registry data. Our findings also demonstrate the value of recursive partitioning in deriving valid claims-based algorithms.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Importance &#x2014; Keratinocyte carcinoma (nonmelanoma skin cancer) accounts for substantial burden in terms of high incidence and healthcare costs but is excluded by most cancer registries in North America. Administrative health insurance claims databases offer an opportunity to identify these cancers using diagnosis and procedural codes submitted for reimbursement purposes. Objective &#x2014; To apply recursive [&hellip;]<\/p>\n","protected":false},"template":"","migration-helper-automated":[],"migration-manual":[],"topic":[38],"migration-helper-qa-sample-set":[],"class_list":["post-6600","journal_article","type-journal_article","status-publish","hentry","topic-cancer-and-cancer-screening"],"acf":{"citation":"Chan AW, Fung K, Tran JM, Kitchen J, Austin PC, Weinstock MA, Rochon PA. <em>JAMA Dermatol.<\/em> 2016; 152(10):1122-7. Epub 2016 Aug 10.","source_url":"http:\/\/archderm.jamanetwork.com\/article.aspx?articleid=2541902","ices_scientist":[1196,1385,1340],"site":[6733,6735],"research_program":[6740,6742,6746],"news_release":[],"journal_article":[],"atlas":[],"research_report":[],"infographic":[],"video":[],"downloads":null,"links":null,"sitecore_item_id":"DAD3305E-BC92-487F-A061-F1C62D668A48","sitecore_item_name":"Application-of-recursive-partitioning-to-derive-and-validate-a-claims-based-algorithm","sitecore_field_values":"{\n  \"Title\": \"Application of recursive partitioning to derive and validate a claims-based algorithm for identifying keratinocyte carcinoma (nonmelanoma skin cancer)\",\n  \"Short title\": \"Application of recursive partitioning to\",\n  \"Summary\": \"This study found that recursive partitioning offers a reliable mechanism for ascertaining keratinocyte carcinoma for epidemiological research in the absence of cancer registry data. \",\n  \"Citation\": \"<p>Chan AW, Fung K, Tran JM, Kitchen J, Austin PC, Weinstock MA, Rochon PA. <em>JAMA Dermatol.<\/em> 2016; 152(10):1122-7. Epub 2016 Aug 10.<\/p>\",\n  \"Abstract\": \"<p><strong>Importance<\/strong> &mdash; Keratinocyte carcinoma (nonmelanoma skin cancer) accounts for substantial burden in terms of high incidence and healthcare costs but is excluded by most cancer registries in North America. Administrative health insurance claims databases offer an opportunity to identify these cancers using diagnosis and procedural codes submitted for reimbursement purposes.<\/p>n<p><strong>Objective<\/strong> &mdash; To apply recursive partitioning to derive and validate a claims-based algorithm for identifying keratinocyte carcinoma with high sensitivity and specificity.<\/p>n<p><span class=\"bold\">Design, Setting, and Participants <\/span>&mdash; Retrospective study using population-based administrative databases linked to 602\u202f371 pathology episodes from a community laboratory for adults residing in Ontario, Canada, from January 1, 1992, to December 31, 2009. The final analysis was completed in January 2016. We used recursive partitioning (classification trees) to derive an algorithm based on health insurance claims. The performance of the derived algorithm was compared with 5 prespecified algorithms and validated using an independent academic hospital clinic data set of 2082 patients seen in May and June 2011.<\/p>n<p><span class=\"bold\">Main Outcomes and Measure <\/span>&mdash; Sensitivity, specificity, positive predictive value, and negative predictive value using the histopathological diagnosis as the criterion standard. We aimed to achieve maximal specificity, while maintaining greater than 80% sensitivity.<\/p>n<p><strong>Results <\/strong>&mdash; Among 602\u202f371 pathology episodes, 131\u202f562 (21.8%) had a diagnosis of keratinocyte carcinoma. Our final derived algorithm outperformed the 5 simple prespecified algorithms and performed well in both community and hospital data sets in terms of sensitivity (82.6% and 84.9%, respectively), specificity (93.0% and 99.0%, respectively), positive predictive value (76.7% and 69.2%, respectively), and negative predictive value (95.0% and 99.6%, respectively). Algorithm performance did not vary substantially during the 18-year period.<\/p>n<p><span class=\"bold\">Conclusions and Relevance <\/span>&mdash; This algorithm offers a reliable mechanism for ascertaining keratinocyte carcinoma for epidemiological research in the absence of cancer registry data. Our findings also demonstrate the value of recursive partitioning in deriving valid claims-based algorithms.<\/p>n<p><a href=\"http:\/\/archderm.jamanetwork.com\/article.aspx?articleid=2541902\" title=\"Opens external link\">View full text<\/a><\/p>\",\n  \"Keywords\": \"{4F321D0E-F7F1-4C8D-B2FE-922AD8DE3C78}|{CDDF7B9A-B998-4F32-B509-5A4A5C703470}\",\n  \"Research Programs\": \"{46DF28D2-EDE8-4DF2-8CC0-87CEF464E435}|{BEC72DE0-BA8C-42B8-ACE5-EE29FFB2CB3B}|{CFE36C89-C969-4C23-B5E4-1BA9E5BDC273}\",\n  \"ICES Locations\": \"{4FCAABBA-14A5-42E6-8F33-BC6C2F1D9908}|{FBE2D1B1-C0BA-423F-8D16-39466B6C1424}\",\n  \"ICES Scientists\": \"{A8EA74FF-4975-4A0A-953D-EC1881EBD1B4}|{7D498E8B-5801-4F9E-AC41-11ED50F3C34E}|{14B76C34-3A35-4785-86C4-9B1633E28765}\",\n  \"Posted Date\": \"20160810T000000\",\n  \"Show on Publications Landing Page\": \"1\"\n}","previous_url":"https:\/\/www.ices.on.ca\/Publications\/Journal-Articles\/2016\/January\/Application-of-recursive-partitioning-to-derive-and-validate-a-claims-based-algorithm"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ICES | Application of recursive partitioning to derive and validate a claims-based algorithm for identifying keratinocyte carcinoma (nonmelanoma skin cancer)<\/title>\n<meta name=\"description\" content=\"Importance &#x2014; 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