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Potential gains from hospital mergers in Denmark

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Abstract

The Danish hospital sector faces a major rebuilding program to centralize activity in fewer and larger hospitals. We aim to conduct an efficiency analysis of hospitals and to estimate the potential cost savings from the planned hospital mergers. We use Data Envelopment Analysis (DEA) to estimate a cost frontier. Based on this analysis, we calculate an efficiency score for each hospital and estimate the potential gains from the proposed mergers by comparing individual efficiencies with the efficiency of the combined hospitals. Furthermore, we apply a decomposition algorithm to split merger gains into technical efficiency, size (scale) and harmony (mix) gains. The motivation for this decomposition is that some of the apparent merger gains may actually be available with less than a full-scale merger, e.g., by sharing best practices and reallocating certain resources and tasks. Our results suggest that many hospitals are technically inefficient, and the expected “best practice” hospitals are quite efficient. Also, some mergers do not seem to lower costs. This finding indicates that some merged hospitals become too large and therefore experience diseconomies of scale. Other mergers lead to considerable cost reductions; we find potential gains resulting from learning better practices and the exploitation of economies of scope. To ensure robustness, we conduct a sensitivity analysis using two alternative returns-to-scale assumptions and two alternative estimation approaches. We consistently find potential gains from improving the technical efficiency and the exploitation of economies of scope from mergers.

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Notes

  1. There are very few commercial hospitals.

  2. In February 2010 the National Board of Health has announced the historically largest restructuring of Danish hospitals, in part as a consequence of the hospital restructuring.

  3. The advantages and disadvantages of SFA and DEA have been discussed in several papers, see for instance [33, 34]. Compared to SFA the drawback of DEA is the inability to test for assumptions about the frontier and the error term as well as endogeneity bias. Furthermore, DEA does not distinguish random factors from efficiency variation. In contrast, the advantage of DEA is that it does not require specification of the functional form of the cost function or explicit assumptions about the production correspondence. DEA requires only an assumption of convexity of the production possibilities set, and uses a postulate of minimum extrapolation from observed data to estimate production correspondence. Another advantage over SFA is that DEA allows for analysis of production characteristics in specific segments of the production possibilities and models multiple-output multiple input technologies.

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Acknowledgement

We are grateful to three anonymous referees for insightful comments on a previous version of the manuscript. All omissions and errors are the sole responsibility of the authors.

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Authors and Affiliations

  1. Institute of Public Health, Department of Health Economics, Faculty of Social Sciences, University of Southern Denmark, Windsløwparken 9B, 5000, Odense C., Denmark

    Troels Kristensen & Kjeld Moeller Pedersen

  2. Department of Economics, Copenhagen Business School, Porcelænshaven 16, DK-2000, Frederiksberg, Denmark

    Peter Bogetoft

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  1. Troels Kristensen
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Correspondence to Troels Kristensen.

Electronic supplementary materials

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Supplement 1

DEA-ranked technical efficiency scores under different assumptions about technology (Types of technology: VRS, VRS including bias correction, NDRS and NDRS including bias correction) (DOC 110 kb)

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Kristensen, T., Bogetoft, P. & Pedersen, K.M. Potential gains from hospital mergers in Denmark. Health Care Manag Sci 13, 334–345 (2010). https://doi.org/10.1007/s10729-010-9133-8

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