Patient-physician interaction in general practice and health inequalities in a multidisciplinary study: design, methods and feasibility in the French INTERMEDE study
1 UMR INSERM 558 Epidémiologie et analyses en santé publique, Faculté de medicine, F-31073 Toulouse, France
2 IRDES, 75018 Paris, France
3 Laboratoire de santé publique, CHU de Nantes, 44093 Nantes, France
BMC Health Services Research 2009, 9:66 doi:10.1186/1472-6963-9-66Published: 22 April 2009
The way in which patients and their doctors interact is a potentially important factor in optimal communication during consultations as well as treatment, compliance and follow-up care. The aim of this multidisciplinary study is to use both qualitative and quantitative methods to explore the 'black box' that is the interaction between the two parties during a general practice consultation, and to identify factors therein that may contribute to producing health inequalities. This paper outlines the original multidisciplinary methodology used, and the feasibility of this type of study.
Methods and design
The study design combines methodologies on two separate samples in two phases. Firstly, a qualitative phase collected ethnographical and sociological data during consultation, followed by in-depth interviews with both patients and doctors independently. Secondly, a quantitative phase on a different sample of patients and physicians collected data via several questionnaires given to patients and doctors consisting of specific 'mirrored' questions asked post-consultation, as well as collecting information on patient and physician characteristics.
The design and methodology used in this study were both successfully implemented, and readily accepted by doctors and patients alike. This type of multidisciplinary study shows great potential in providing further knowledge into the role of patient/physician interaction and its influence on maintaining or producing health inequalities. The next challenge in this study will be implementing the multidisciplinary approach during the data analysis.