This is the sixth in a series of eight articles analysing the gap between research and practice

Series editors: Andrew Haines and Anna Donald

Evidence based medicine is more than just reading the results of research and applying those results to patients because patients have particular features that may make them different from the “average” patient studied in a clinical trial.1There are two types of differences. The first type of differences comprise those that affect probability (for example, the probability that treatments will have the same absolute or relative effects as those measured in the trial). The second type of differences comprise those values (or utilities) that affect how much of a side effect a person is prepared to trade off against the positive advantages of treatment.

Thus it is necessary for doctors to relate the results from a trial to their particular patient. Health professionals usually do this intuitively, but formal decision analysis provides an intellectual framework for developing an explicit decision making algorithm which can be criticised and improved. Although, currently, time constraints make it unrealistic to conduct a separate decision analysis for each patient, computer programs may soon help overcome this problem. It is, however, feasible for decision analyses to be done for categories of patients with similar clinical features and personal utilities. The results of such generic decision analyses provide a sound basis for developing clinical guidelines. Decision analysis thus provides a rational means of allowing health professionals to move from finding evidence to implementing it.