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Relative effectiveness assessment of listed drugs (REAL): A new method for an early comparison of the effectiveness of approved health technologies

Published online by Cambridge University Press:  08 January 2010

Bruno Falissard ,
Valérie Izard ,
Bertrand Xerri ,
Gilles Bouvenot ,
François Meyer  and
Laurent Degos
Bruno Falissard
Affiliation:
South Paris University
Valérie Izard
Affiliation:
Haute autorité de santé
Bertrand Xerri
Affiliation:
Haute autorité de santé
Gilles Bouvenot
Affiliation:
Hôpital Sainte-Marguerite and Haute autorité de santé
François Meyer
Affiliation:
Haute autorité de santé
Laurent Degos
Affiliation:
Hôpital Saint Louis and Haute autorité de santé
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Abstract

Objectives: Post-listing assessment of pharmaceuticals depends on national habits. In England, the assessment is based on estimates of cost per quality-adjusted life-year. These are made some considerable time after listing (negative list). In France, effectiveness, and then efficiency, is assessed immediately after listing (positive list). We propose a new formal method—the REAL method—that can help make early comparisons of the effectiveness of medical treatments.

Methods: Relative efficacies are first obtained from randomized controlled trials (RCTs). Members of the Transparency Committee (French National Authority for Health) are then consulted by questionnaire on the transposability of these results to real life. The RCT results and experts’ ratings are entered into an effect model to obtain estimates of relative effectiveness, using unidimensional scaling, and bootstrap procedures.

Results: Application of the REAL method to the example of a new drug to treat Parkinson's disease and three comparators used in the same indication provided graphs of the distributions of their relative efficacy and relative effectiveness. The new drug was found to provide no added value.

Conclusions: The REAL method is a rational, transparent, and practical procedure for comparing the effectiveness of pharmaceuticals in an immediate post-listing setting.

Keywords

EffectivenessMixed comparisonsIndirect comparisonsEffect modelExperts rating
Type
METHODS
Information
International Journal of Technology Assessment in Health Care , Volume 26 , Issue 1 , January 2010 , pp. 124 - 130
Copyright
Copyright © Cambridge University Press 2010

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