- Jeremy Jones, Lecturer in health economicsa,
- Duncan Hunter, research fellowb
- aNuffield Community Care Studies Unit, Department of Epidemiology and Public Health, University of Leicester, Leicester LE1 7RH,
- bHealth Services Research Unit, Department of Public Health and Policy, London School of Hygiene and Tropical Medicine, London WC1E 7HT
- Correspondence to: Dr Jones.
Health providers face the problem of trying to make decisions in situations where there is insufficient information and also where there is an overload of (often contradictory) information. Statistical methods such as meta-analysis have been developed to summarise and to resolve inconsistencies in study findings—where information is available in an appropriate form. Consensus methods provide another means of synthesising information, but are liable to use a wider range of information than is common in statistical methods, and where published information is inadequate or non-existent these methods provide a means of harnessing the insights of appropriate experts to enable decisions to be made. Two consensus methods commonly adopted in medical, nursing, and health services research—the Delphi process and the nominal group technique (also known as the expert panel)—are described, together with the most appropriate situations for using them; an outline of the process involved in undertaking a study using each method is supplemented by illustrations of the authors' work. Key methodological issues in using the methods are discussed, along with the distinct contribution of consensus methods as aids to decision making, both in clinical practice and in health service development.
Defining consensus and consensus methods
Quantitative methods such as meta-analysis have been developed to provide statistical overviews of the results of clinical trials and to resolve inconsistencies in the results of published studies. Consensus methods are another means of dealing with conflicting scientific evidence. They allow a wider range of study types to be considered than is usual in statistical reviews. In addition they allow a greater role for the qualitative assessment of evidence (box 1). These methods, unlike those described in the other papers in this series, are primarily concerned with deriving quantitative estimates through qualitative …