Reducing uncertainty in evidence‐based health policy by integrating empirical and theoretical evidence: An EbM+theory approach

Abstract

AbstractBackgroundTo reduce their decisional uncertainty, health policy decision‐makers rely more often on experts or their intuition than on evidence‐based knowledge, especially in times of urgency. However, this practice is unacceptable from an evidence‐based medicine (EbM) perspective. Therefore, in fast‐changing and complex situations, we need an approach that delivers recommendations that serve decision‐makers' needs for urgent, sound and uncertainty‐reducing decisions based on the principles of EbM.AimsThe aim of this paper is to propose an approach that serves this need by enriching EbM with theory.Materials and MethodsWe call this the EbM+theory approach, which integrates empirical and theoretical evidence in a context‐sensitive way to reduce intervention and implementation uncertainty.ResultsWithin this framework, we propose two distinct roadmaps to decrease intervention and implementation uncertainty: one for simple and the other for complex interventions. As part of the roadmap, we present a three‐step approach: applying theory (step 1), conducting mechanistic studies (EbM+; step 2) and conducting experiments (EbM; step 3).DiscussionThis paper is a plea for integrating empirical and theoretical knowledge by combining EbM, EbM+ and theoretical knowledge in a common procedural framework that allows flexibility even in dynamic times. A further aim is to stimulate a discussion on using theories in health sciences, health policy, and implementation.ConclusionThe main implications are that scientists and health politicians – the two main target groups of this paper—should receive more training in theoretical thinking; moreover, regulatory agencies like NICE may think about the usefulness of integrating elements of the EbM+theory approach into their considerations.