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Supplementary health insurance as a tool for risk-selection in mandatory basic health insurance markets

Published online by Cambridge University Press:  01 April 2007

FRANCESCO PAOLUCCI*
Affiliation:
Department of Health Policy and Management, Erasmus University Rotterdam, The Netherlands
ERIK SCHUT
Affiliation:
Department of Health Policy and Management, Erasmus University Rotterdam, The Netherlands
KONSTANTIN BECK
Affiliation:
CSS Insurance and University of Zurich, Switzerland
STEFAN GREß
Affiliation:
Department of Health Sciences, University of Applied Sciences Fulda, Germany
CARINE VAN DE VOORDE
Affiliation:
Centre for Economic Studies, Catholic University Leuven, Belgium
IRIT ZMORA
Affiliation:
Clalit Health Services, Israel
*
*Corresponding author: Francesco Paolucci, Erasmus University, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands. Tel: +31 10 408 8535; E-mail: paolucci@bmg.eur.nl
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Abstract:

As the share of supplementary health insurance (SI) in health care finance is likely to grow, SI may become an increasingly attractive tool for risk-selection in basic health insurance (BI). In this paper, we develop a conceptual framework to assess the probability that insurers will use SI for favourable risk-selection in BI. We apply our framework to five countries in which risk-selection via SI is feasible: Belgium, Germany, Israel, the Netherlands, and Switzerland. For each country, we review the available evidence of SI being used as selection device. We find that the probability that SI is and will be used for risk-selection substantially varies across countries. Finally, we discuss several strategies for policy makers to reduce the chance that SI will be used for risk-selection in BI markets.

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Articles
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Copyright © Cambridge University Press 2006
Figure 0

Figure 1.Defining health insurance schemes

Figure 1

Table 1Main features of SI in the 5 countries*

Figure 2

Table 2.Strength of incentives for risk-selection in BI

Figure 3

Table 3.Usefulness of SI for risk-selection in BI

Figure 4

Table 4Probability and evidence of risk-selection in BI via SI