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Opening Up Data Analysis for Medical Health Services: Data Integration and Analysis in Cancer Registries with CARESS

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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVI

Abstract

Dealing with cancer is one of the big challenges of the German healthcare system. Todays efforts regarding the analysis of cancer data incorporate detection of spatial clusters as well as complex health services research and quality assurance. Recently, guidelines for a unified evaluation of German cancer data were developed which demand the execution of comparative survival analyses [1].

In this paper, we present how the CARLOS Epidemiological and Statistical Data Exploration System (CARESS), a sophisticated data warehouse system that is used by epidemiological cancer registries (ECR) in several German federal states, opens up survival analysis for a wider audience. We also discuss several performance optimizations for survival estimation, and illustrate the feasibility of our approach. Moreover we present the CARLOS Record Linkage System CARELIS, a companion tool to CARESS that enables matching new data against already existent disease reports in the ECR under consideration of potential cross references.

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Notes

  1. 1.

    See http://www.onkozert.de/ [last visited 2014/03/27].

  2. 2.

    A relational database request would result in only a few hundred rows, when, for example, a rare diagnosis or a specific regional area is analyzed.

  3. 3.

    Exporting a survival analysis to Excel is performed by the ExcelExportService, which uses the CachedSurvivalAnalysisDataService via theResultService.

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Correspondence to Stefan Gudenkauf .

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Korfkamp, D. et al. (2016). Opening Up Data Analysis for Medical Health Services: Data Integration and Analysis in Cancer Registries with CARESS. In: Hameurlain, A., Küng, J., Wagner, R., Bellatreche, L., Mohania, M. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVI. Lecture Notes in Computer Science(), vol 9670. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49784-5_4

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  • DOI: https://doi.org/10.1007/978-3-662-49784-5_4

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