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Grundlagen und Methoden von GKV-Routinedatenstudien

Author

Listed:
  • Neubauer, Sarah
  • Zeidler, Jan
  • Lange, Ansgar
  • Graf von der Schulenburg, J.-Matthias

Abstract

Claims data studies are becoming an increasingly important source of information for healthcare stakeholders. The importance and scientific use of claims data of the statutory health funds has further increased. We saw a general lack of elaborated recommendations for best practices in this field and a need for a thorough overview of published methods used in each step of conducting a claims data study. This discussion paper examines and compares conceptual and methodological approaches used in claims data studies aiming to stimulate discussion on quality of the studies and to promote creation of standards and guidelines for consistent and transparent claims data studies and reports. Our results emphasize the importance guidelines in the field of claims data analyses and discussed the advantages and disadvantages of different methodological approaches.

Suggested Citation

  • Neubauer, Sarah & Zeidler, Jan & Lange, Ansgar & Graf von der Schulenburg, J.-Matthias, 2014. "Grundlagen und Methoden von GKV-Routinedatenstudien," Hannover Economic Papers (HEP) dp-534, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  • Handle: RePEc:han:dpaper:dp-534
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    File URL: http://diskussionspapiere.wiwi.uni-hannover.de/pdf_bib/dp-534.pdf
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    Citations

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    Cited by:

    1. Kreis, Kristine & Neubauer, Sarah & Klora, Mike & Lange, Ansgar & Zeidler, Jan, 2016. "Status and perspectives of claims data analyses in Germany—A systematic review," Health Policy, Elsevier, vol. 120(2), pages 213-226.
    2. Jan Breitkreuz & Gabriela Brückner & Jan Pablo Burgard & Joscha Krause & Ralf Münnich & Helmut Schröder & Katrin Schüssel, 2019. "Schätzung kleinräumiger Krankheitshäufigkeiten für die deutsche Bevölkerung anhand von Routinedaten am Beispiel von Typ-2-Diabetes [Estimation of regional diabetes type 2 prevalence in the German p," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 13(1), pages 35-72, April.
    3. Ehing, Daniel & Hagist, Christian, 2015. "Dementia vs. somatic conditions in the German LTC-system: A longitudinal analysis," FZG Discussion Papers 56, University of Freiburg, Research Center for Generational Contracts (FZG).

    More about this item

    Keywords

    GKV-Routinedaten; Datenkategorien; Studiendesigns; Validierung; Datenaufbereitung; claims data; data categories; study design; validation; data pro-cessing; best practices;
    All these keywords.

    JEL classification:

    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private

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