Reducing uncertainty in evidence-based health policy by integrating empirical and theoretical evidence: An EbM+theory approach
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
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.
Details
Original language | English |
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Pages (from-to) | 1279-1293 |
Number of pages | 15 |
Journal | Journal of evaluation in clinical practice |
Volume | 29 |
Issue number | 8 |
Publication status | Published - Dec 2023 |
Peer-reviewed | Yes |
External IDs
Scopus | 85164591448 |
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Keywords
Sustainable Development Goals
Keywords
- Evidence-Based Medicine, Health Policy, Humans, Knowledge, Uncertainty