M Pirson1, C Delo, D Martins, P Leclercq. 1. Département d'Economie de la Santé, CP592, Ecole de Santé Publique de l'Université Libre de Bruxelles, 806, Route de Lennik, 1070 Bruxelles, Belgium. magali.pirson@ulb.ac.be
Abstract
OBJECTIVES: Objectives of this article are to evaluate the possibility to create a CW scale by pathology on the basis of cost data from Belgian hospitals, to compare several methodologies to create this CW scale, and to evaluate the financial impact of a modification of the financing system on hospitals' income. METHODS: CW scales were elaborated according to various methodologies in order to isolate the scale allowing the most adequate financing system, i.e. approaching the real costs as much as possible. Twelve scales were created. They vary according to the type of data used, according to DRGs and severities of illness included within the scale, and according to the variable used in order to isolate outliers. RESULTS: For a similar case-mix, Hospitals H2 and H5 would see their financing increased through a prospective system based on the selected CW scale (No. 6). This modification would generate a reduction in financing going from -1 to -9% according to hospitals. CONCLUSIONS: The cost database created made it possible to create a CW scale according to a technique which could constitute the first step of a PPS if advantages of a such financing system were established. In the Belgian context, it would be probably judicious to envisage regional databases allowing diversified methodological approaches whose results would be confronted, discussed, and coordinated at the federal level.
OBJECTIVES: Objectives of this article are to evaluate the possibility to create a CW scale by pathology on the basis of cost data from Belgian hospitals, to compare several methodologies to create this CW scale, and to evaluate the financial impact of a modification of the financing system on hospitals' income. METHODS: CW scales were elaborated according to various methodologies in order to isolate the scale allowing the most adequate financing system, i.e. approaching the real costs as much as possible. Twelve scales were created. They vary according to the type of data used, according to DRGs and severities of illness included within the scale, and according to the variable used in order to isolate outliers. RESULTS: For a similar case-mix, Hospitals H2 and H5 would see their financing increased through a prospective system based on the selected CW scale (No. 6). This modification would generate a reduction in financing going from -1 to -9% according to hospitals. CONCLUSIONS: The cost database created made it possible to create a CW scale according to a technique which could constitute the first step of a PPS if advantages of a such financing system were established. In the Belgian context, it would be probably judicious to envisage regional databases allowing diversified methodological approaches whose results would be confronted, discussed, and coordinated at the federal level.