Balanced Billing in the Belgian Health Care System: How to Predict the Financial Burden for Certain Groups of Patients?

Posted: 12 Jun 2007

See all articles by Ann Lecluyse

Ann Lecluyse

University of Antwerp

Diana De Graeve

University of Antwerp

Erik Schokkaert

Catholic University of Leuven (KUL)

Carine Van de Voorde

Catholic University of Leuven (KULeuven)

Tom Van Ourti

Erasmus University Rotterdam (EUR); Tinbergen Institute

Abstract

Objectives: While policymakers already debated a lot on co-payments, there is an increasing concern about the huge increase of supplements as well. In this study we investigate the distribution of the burden of supplements. We want to describe the characteristics of the payer of supplements. Methodology: We use an administrative dataset of the different sickness funds with annual data for 2003 of a representative sample of about 300,000 individuals. We define supplements as the difference between the total amount paid by the patient and the official price (reimbursements from the health insurance co-payments); or as the total amount itself if there are no reimbursements. We estimate different specifications of the model. First, we start with a benchmark: OLS of the expenditures on several independent variables. Two-part models with logistic specification in the first part and different specifications in the second part (OLS, OLS on log expenditures and gamma with log specification) are estimated as well.

Results: In general, the explanatory power of our models is rather low. Based on the OLS regression, we see a clear regional pattern in the total yearly amount of supplements paid. Older people and patients in their last year of life pay more supplements. People that are handicapped, disabled or chronically ill pay higher supplements as well. Patients that have preferential treatment (i.e. they have protection from the government for their co-payments) pay fewer supplements. In the two step model, we can see whether the reason for these patterns comes from the incidence of paying supplements or from the height of the supplements to be paid. We see that e.g. those with preferential treatment have an equal chance of paying supplements compared to the others, whereas the second part (in each specification) reveals that the absolute amount of supplements are lower. While the mean of OLS regression for supplements is - 60.77, the predicted mean of the two part model varies between 76.20 and 627.15 depending on the chosen specification.

Conclusions: While OLS is a simple model giving a good overview for policymakers, the two-part model is more complicated and gives more details on the observed pattern of supplements. We can separate out effects on the probability to pay supplements versus the amount to be paid. It is clear that the patterns in the different specifications tell us more or less the same. More of concern is the fact that the estimated values of the mean of supplements vary a lot among the models.

To be done: marginal effects will be calculated for each of the proposed models. Moreover, as the patients in the upper right tail of the distribution are the ones that are most likely to have financial problems, it is very important to see which model can best predict estimated expenditures in these regions.

Keywords: balanced billing, equity, two-part model

JEL Classification: i10

Suggested Citation

Lecluyse, Ann and De Graeve, Diana and Schokkaert, Erik and Van de Voorde, Carine and Van Ourti, Tom, Balanced Billing in the Belgian Health Care System: How to Predict the Financial Burden for Certain Groups of Patients?. iHEA 2007 6th World Congress: Explorations in Health Economics Paper, Available at SSRN: https://ssrn.com/abstract=993025

Ann Lecluyse (Contact Author)

University of Antwerp ( email )

Prinsstraat 13
Antwerp, Antwerp 2000
Belgium

Diana De Graeve

University of Antwerp ( email )

Prinsstraat 13
Antwerp, Antwerp 2000
Belgium

Erik Schokkaert

Catholic University of Leuven (KUL) ( email )

Oude Markt 13
Leuven, Vlaams-Brabant 3000
Belgium

Carine Van de Voorde

Catholic University of Leuven (KULeuven) ( email )

Naamsestraat 69
B-3000 Leuven, 3000
Belgium

Tom Van Ourti

Erasmus University Rotterdam (EUR) ( email )

Burgemeester Oudlaan 50
3000 DR Rotterdam, Zuid-Holland 3062PA
Netherlands

Tinbergen Institute ( email )

Burg. Oudlaan 50
Rotterdam, 3062 PA
Netherlands

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