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

2023; Wiley; Volume: 29; Issue: 8 Linguagem: Inglês

10.1111/jep.13890

1365-2753

Holger Pfaff, Jochen Schmitt,

Healthcare cost, quality, practices

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.The aim of this paper is to propose an approach that serves this need by enriching EbM with theory.We call this the EbM+theory approach, which integrates empirical and theoretical evidence in a context-sensitive way to reduce intervention and implementation uncertainty.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).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.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.