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Analyzing economies of scale and scope in hospitals by use of case mix planning

Author

Listed:
  • Sebastian McRae

    (University of Augsburg)

  • Jens O. Brunner

    (University of Augsburg)

  • Jonathan F. Bard

    (The University of Texas at Austin)

Abstract

This study analyzes the effect of economies of scale and scope on the optimal case mix of a hospital or hospital system. With respect to the ideal volume and patient composition, the goal is to evaluate (i) the impact of changes in the efficiency of resource use with increasing scale, and (ii) to determine the potential effects of spreading fixed costs over a greater number of patients. The problem is formulated as a non-linear mixed integer program. It turns out that this non-linear program is too difficult to be solved with standard software. As an alternative, an iterative procedure using piecewise linear approximations to derive lower and upper bounds is proposed and shown to converge to the optimum. The procedure is applied using a public database on German hospital costs and performance statistics. Results indicate that changes in the efficiency of resource use with increasing scale have a considerable impact if similar services can be consolidated, e.g., among different departments. However, if the scope for decision-making regarding the case mix of a hospital is limited, such changes may be negligible.

Suggested Citation

  • Sebastian McRae & Jens O. Brunner & Jonathan F. Bard, 2020. "Analyzing economies of scale and scope in hospitals by use of case mix planning," Health Care Management Science, Springer, vol. 23(1), pages 80-101, March.
    • Handle: RePEc:kap:hcarem:v:23:y:2020:i:1:d:10.1007_s10729-019-09476-2
    DOI: 10.1007/s10729-019-09476-2
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    Cited by:

    1. Annika Maren Schneider & Eva-Maria Oppel & Jonas Schreyögg, 2020. "Investigating the link between medical urgency and hospital efficiency – Insights from the German hospital market," Health Care Management Science, Springer, vol. 23(4), pages 649-660, December.
    2. Ricardo Ocaña-Riola & Carmen Pérez-Romero & Mª Isabel Ortega-Díaz & José Jesús Martín-Martín, 2021. "Multilevel Zero-One Inflated Beta Regression Model for the Analysis of the Relationship between Exogenous Health Variables and Technical Efficiency in the Spanish National Health System Hospitals," IJERPH, MDPI, vol. 18(19), pages 1-18, September.
    3. Milena Grieger & Steffen Heider & Sebastian McRae & Thomas Koperna & Jens O. Brunner, 2024. "Managing the patient portfolio using mathematical programming: decision support guidelines using a real-world use case at a university hospital," Journal of Business Economics, Springer, vol. 94(9), pages 1245-1260, November.

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