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

Abstract

Background: To 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. Aims: The aim of this paper is to propose an approach that serves this need by enriching EbM with theory. Materials and Methods: We call this the EbM+theory approach, which integrates empirical and theoretical evidence in a context-sensitive way to reduce intervention and implementation uncertainty. Results: Within 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). Discussion: This 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. Conclusion: The 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.