How can the Quality of Medical Data in Pharmacovigilance, Pharmacoepidemiology and Clinical Studies be Guaranteed?

¹ Université de Lorraine, Nancy, France
² Laboratoire Lilly France, Neuilly-sur-Seine, France
³ Université Pierre et Marie Curie, Paris, France
⁴ Laboratoire AstraZeneca, Rueil-Malmaison, France
⁵ Laboratoire Ax-Pharma, Paris, France
⁶ Laboratoire Merck Serono, Lyon, France
⁷ DRCD, Paris, France
⁸ Laboratoire Pierre Fabre Médicament, Castres, France
⁹ F-CRIN, Toulouse, France
¹⁰ Laboratoire Novartis, Rueil-Malmaison, France
¹¹ URC Pitié-Salpétrière, AP-HP, Paris, France
¹² Laboratoire Merck Sharp Dohme, Courbevoie, France
¹³ Université Paris 7, Paris, France
¹⁴ DRCD Île-de-France, Paris, France
¹⁵ Pharmacologie clinique, CHU, Lyon, France
¹⁶ DRCD, Paris, France
¹⁷ DRCD, Pôle vigilance, Paris, France
¹⁸ Centre régional de Pharmacovigilance, CHU, Bordeaux, France
¹⁹ Assistance Publique – Hôpitaux de Paris, Paris, France
²⁰ Laboratoire GlaxoSmithKline, Marly-le-Roi, France

Correspondence and offprints: François Alla, Centre d’Épidémiologie clinique, Inserm-CHU de Nancy, Allée du Morvan, 54500 Vandœuvre-les-Nancy, France. E-mail: f.alla@chu-nancy.fr

Received: 15 March 2013
Accepted: 7 May 2013

Abstract

The development of medicinal products is subject to quality standards aimed at guaranteeing that database contents accurately reflect the source documents. Paradoxically, these standards hardly address the quality of the source data itself. The objective of this work was to propose recommendations to improve data quality in three fields (pharmacovigilance, pharmacoepidemiology and clinical studies). The analysis was focused on the data and on the critical stages presenting critical quality problems, for which the current guidelines are insufficiently detailed, unsuitable and/or poorly applied. Finally, recommendations have been proposed, mainly focused on the origin of the data and its transcription.