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Morbidity related controlling of pharmaceutical expenditures using prescription data

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Abstract

The controlling of outpatient drug costs in Germany is implemented almost entirely on the federal state level. Each year the regional representatives of the Statutory Health Insurances (SHI) and the Association of SHI Physicians in all federal states have to define an upper limit for pharmaceutical expenditures. In the most northern federal state (Schleswig-Holstein) the regional parties agreed on a morbidity related approach solely based on prescription data to meet with the spending target. The underlying patient-related classification system is called Morbidity Related Groups (MRG). Introductory the underlying data, the present model for controlling measures and the hard-/software used today will be discussed. Subsequently improvements and extensions to the MRG classification system leading to a generalized model of drug resourcing are suggested.

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Notes

  1. With minor changes all equations in this paper originate from [6].

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Authors and Affiliations

  1. Chair of Department of Prescription Analysis, Association of Statutory Health Insurance Physicians, Bad Segeberg, Germany

    Timo Emcke

  2. Chair of Research Methodology and Statistics in Psychology, Witten/Herdecke University, Witten, Germany

    Thomas Ostermann

  3. Medical Advisory Board of Statutory Health Insurance in Northern Germany, Lübeck, Germany

    Marc Heidbreder

  4. Chair of Department of Health Economics, Epidemiology and Medical Informatics, Medical Advisory Board of Statutory Health Insurance in Northern Germany, Lübeck, Germany

    Reinhard Schuster

Authors
  1. Timo Emcke
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  2. Thomas Ostermann
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  3. Marc Heidbreder
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  4. Reinhard Schuster
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Correspondence to Timo Emcke.

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All four authors declare that they have no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Emcke, T., Ostermann, T., Heidbreder, M. et al. Morbidity related controlling of pharmaceutical expenditures using prescription data. Health Technol. 8, 353–359 (2018). https://doi.org/10.1007/s12553-018-0262-2

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  • DOI: https://doi.org/10.1007/s12553-018-0262-2

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