Application of Recursive Partitioning to Derive and Validate a Claims-Based Algorithm for Identifying Keratinocyte Carcinoma (Nonmelanoma Skin Cancer).
Importance: Keratinocyte carcinoma (nonmelanoma skin cancer) accounts for substantial burden in terms of high incidence and health care costs but is excluded by most cancer registries in North America. Administrative health insurance claims databases offer an opportunity to identify these cancers us...
| Publicado en: | JAMA Dermatology Vol. 152; no. 10; pp. 1122 - 1128 |
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| Autores principales: | , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
American Medical Association
Oct2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=118881766&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 118881766 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 21686068 FTFQ jtl: JAMA Dermatology issn: 21686068 maglogo: N pubinfo: dt: Oct2016 vid: 152 iid: 10 pid: 30 pub: American Medical Association place: Chicago, Illinois artinfo: ui: 118881766 118881766 NLM27533718 118881766 10.1001/jamadermatol.2016.2609 NLM27533718 118881766 ppf: 1122 ppct: 6 formats: tig: atl: Application of Recursive Partitioning to Derive and Validate a Claims-Based Algorithm for Identifying Keratinocyte Carcinoma (Nonmelanoma Skin Cancer). aug: au: An-Wen Chan Kinwah Fung Tran, Jennifer M. Kitchen, Jessica Austin, Peter C. Weinstock, Martin A. Rochon, Paula A. Chan, An-Wen Fung, Kinwah affil: Women's College Research Institute,Women's College Hospital, Toronto, Ontario, Canada sug: subj: Skin Neoplasms Diagnosis Insurance Statistics and Numerical Data Keratinocytes Pathology Carcinoma, Basal Cell Diagnosis Carcinoma, Squamous Cell Diagnosis Ontario Incidence Skin Neoplasms Classification Human Carcinoma, Basal Cell Classification Retrospective Design Carcinoma, Squamous Cell Classification Skin Neoplasms Epidemiology Female Carcinoma, Squamous Cell Epidemiology Prognosis Reproducibility of Results Male Carcinoma, Basal Cell Epidemiology Resource Databases Predictive Value of Tests Algorithms Insurance, Health Statistics and Numerical Data Adult Sensitivity and Specificity Validation Studies Comparative Studies Evaluation Research Multicenter Studies Adult: 19-44 years Female Male ab: Importance: Keratinocyte carcinoma (nonmelanoma skin cancer) accounts for substantial burden in terms of high incidence and health care 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: To apply recursive partitioning to derive and validate a claims-based algorithm for identifying keratinocyte carcinoma with high sensitivity and specificity.Design, Setting, and Participants: Retrospective study using population-based administrative databases linked to 602 371 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.Main Outcomes and Measures: 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.Results: Among 602 371 pathology episodes, 131 562 (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.Conclusions and Relevance: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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