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The European Journal of Health Economics
Published in: The European Journal of Health Economics 6/2011

Open Access 01-12-2011 | Original Paper

Market structure and hospital–insurer bargaining in the Netherlands

Authors: R. S. Halbersma, M. C. Mikkers, E. Motchenkova, I. Seinen

Published in: The European Journal of Health Economics | Issue 6/2011

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Abstract

In 2005, competition was introduced in part of the hospital market in the Netherlands. Using a unique dataset of transactions and list prices between hospitals and insurers in the years 2005 and 2006, we estimate the influence of buyer and seller concentration on the negotiated prices. First, we use a traditional structure–conduct–performance model (SCP-model) along the lines of Melnick et al. (J Health Econ 11(3): 217–233, 1992) to estimate the effects of buyer and seller concentration on price–cost margins. Second, we model the interaction between hospitals and insurers in the context of a generalized bargaining model similar to Brooks et al. (J Health Econ 16: 417–434, 1997). In the SCP-model, we find that the market shares of hospitals (insurers) have a significantly positive (negative) impact on the hospital price–cost margin. In the bargaining model, we find a significant negative effect of insurer concentration, but no significant effect of hospital concentration. In both models, we find a significant impact of idiosyncratic effects on the market outcomes. This is consistent with the fact that the Dutch hospital sector is not yet in a long-run equilibrium.
Footnotes
1
To be more precise, competition here is reflected in prices (higher for more concentrated sellers, lower for more concentrated buyers).
 
2
In the near future, we do expect to obtain complete patient-level data of the entire Dutch hospital sector, opening the possibilities to go beyond the reduced form models in this paper.
 
3
The method of defining relevant markets for health care markets is not undisputed. See, for example, Gaynor and Vogt [23]. But owing to lack of data, we were not able to test alternative approaches to determine geographical markets. This restricted us to base the estimations on the results of already published analysis by Prismant [32] based on the Elzinga–Hogarty test.
 
4
The remaining DBCs are merely theoretical combinations of diagnoses and treatments.
 
5
One may argue that the market share variable (M) is not exogenous in this expression, since there might be a correlation between market shares of the firms and the prices they are able to charge. This could cause an endogeneity problem, which in principle is possible to cure using the IV techniques (for example, using lagged values of the same variables—i.e. market shares of 2005). However, in our case endogeneity is not really severe, since we are considering only the short run (first 2 years after the institutional change) where the putative reverse relationship between market shares and prices is not established yet. Moreover, market shares of the hospitals are calculated based on the data from the regulated segment.
 
6
A similar interpretation of the regression coefficients is employed in Bos [3], who studies the effect of concentration in Dutch banking market on banks’ performance. Bos [3] also provides a formal theoretical model that connects regression coefficient of market share (M) to the conjectural variation parameter in Cournot model.
 
7
The direct analysis of collusion is not possible with our data set and would also require an underlying structural model. To the best of our knowledge, there is no existing literature that directly tests the hypothesis of collusion versus bargaining power.
 
8
P T , the price that the insurer pays for an episode of inpatient care if the insurer has no bargaining power can also be viewed as the maximum price that can be asked by the hospital in case it has monopoly power in the relevant market. This price represents the upper bound of the interval of gains from trade between hospital and insurer. We believe that the list price in our sample can be a good approximation for this upper bound of the gains from trade, since the list price represents the price that can be asked by the hospital from a consumer who does not have an option to bargain for a reduced price.
 
9
Unfortunately, the interpretation of the model with log-transformed variables on the RHS is more difficult. So we cannot really compare the magnitude of the coefficients of the two above-described models (only can make comparisons of their sign and significance). Another alternative would be to rescale the variable on the LHS and do the usual OLS of the log-linear model, where coefficients can be interpreted in terms of elasticities.
 
10
These 12 “front-runner” hospitals give a fairly representative sample of the total 98 hospitals and are not systematically different from the rest in terms of size or volumes of production.
 
11
Their analysis is based on micro-level data from the previous medical registration and performed for different product markets. We used the analysis for uncomplicated, elective, care products. The Prismant analysis is based on patient locations indexed by zipcode areas. For some metropolitan areas, we had to correct these results for adjacent hospitals located in the same zipcode area, which would otherwise result in completely overlapping geographic markets.
 
12
Formal diagnostic testing with the Kolmogorov–Smirnov and Shapiro–Wilk tests rejected the null-hypothesis of normally distributed residuals of the linear model specification.
 
13
A similar result was obtained by Melnick et al. [29].
 
14
In a regression with on the RHS b1 * HHI + b2 * (market share—HHI), the net impact of the HHI is (b1 − b2) * HHI. In our estimation, b1 does not significantly differ from b2, so the net impact of the HHI is not significantly different from zero.
 
15
For more formal representation, see expression (9).
 
16
See Dranove and Satterthwaite [15] for an overview of the industrial organization of health care markets in the US.
 
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Metadata
Title
Market structure and hospital–insurer bargaining in the Netherlands
Authors
R. S. Halbersma
M. C. Mikkers
E. Motchenkova
I. Seinen
Publication date
01-12-2011
Publisher
Springer-Verlag
Published in
The European Journal of Health Economics / Issue 6/2011
Print ISSN: 1618-7598
Electronic ISSN: 1618-7601
DOI
https://doi.org/10.1007/s10198-010-0273-z

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