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Planning health care capacities with a gravity equation

Author

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  • Wende, Danny
  • Kopetsch, Thomas
  • Richter, Wolfram F.

Abstract

The planning of health care capacities is in practice constrained by sectoral and regional boundaries and it remains difficult to ensure an adequate and even access to health care. Moreover, standard planning approaches lack the choice-theoretic grounding necessary for making reliable statements about the demand for health care. This paper presents a model based on the idea of gravity in supply and demand linkages and designed to overcome such shortcomings. Empirical estimation equations are derived for the size of catchment areas, the spatial access to health care and the demand for specialist treatment. The floating catchment area (FCA) method commonly used to measure access to care is shown to be a special, yet often misleading case. This is demonstrated by the example of Germany, where rural areas are shown to suffer from access deficits.

Suggested Citation

  • Wende, Danny & Kopetsch, Thomas & Richter, Wolfram F., 2020. "Planning health care capacities with a gravity equation," Ruhr Economic Papers 888, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    • Handle: RePEc:zbw:rwirep:888
    DOI: 10.4419/969730270
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    References listed on IDEAS

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    More about this item

    Keywords

    Health care capacity planning; choice-theoretic foundation; gravity equation; spatial multiple equation model;
    All these keywords.

    JEL classification:

    • H72 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Budget and Expenditures
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

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