SUPPORT Tools for evidence-informed health Policymaking (STP) 17: Dealing with insufficient research evidence

Abstract

This article is part of a series written for people responsible for making decisions about health policies and programmes and for those who support these decision makers. In this article, we address the issue of decision making in situations in which there is insufficient evidence at hand. Policymakers often have insufficient evidence to know with certainty what the impacts of a health policy or programme option will be, but they must still make decisions. We suggest four questions that can be considered when there may be insufficient evidence to be confident about the impacts of implementing an option. These are: 1. Is there a systematic review of the impacts of the option? 2. Has inconclusive evidence been misinterpreted as evidence of no effect? 3. Is it possible to be confident about a decision despite a lack of evidence? 4. Is the option potentially harmful, ineffective or not worth the cost?

Figure 1

Two problems with classifying results as 'statistically non-significant' or 'negative'. The blue dots in the Figure above indicate the estimated effect for each study and the horizontal lines indicate the 95% confidence intervals. A 95% confidence interval means that we can be 95% confident that the true size of the effect is between the lower and upper confidence limit (the two ends of the horizontal lines). Conversely, there is a 5% chance that the true effect is outside this range.