From Chaos to Rationality: A Contingent Meta-Model for Evidence-Informed Health Policymaking in Diverse Contexts.

Abstract

Background: Evidence-informed policymaking is a complex process that requires adapting to diverse contexts characterized by varying degrees of certainty and agreement. Existing models and frameworks often lack clear guidance for dealing with such contexts. This study aimed to develop a novel contingency model to guide the context-specific use of evidence in health policymaking.

Methods: The study conducted a meta-ethnographic synthesis of 15 existing models and frameworks on evidence-informed policymaking, integrating key factors and concepts influencing the use of evidence in policy decisions. The study also adapted the Stacey Matrix, a tool for understanding the complexity of decision-making, into a quantitative scoring system to assess the levels of certainty and agreement in a given policy context.

Results: The study proposed a contingency model that delineates seven modes of decision-making based on the dimensions of certainty and agreement, ranging from rational to molasses-slow collective. For each mode, the model suggests configuring four aspects: team composition, policy idea generation, problem analysis, and consensus building. The model also highlights the multifaceted influences of evidence, interests, values, and beliefs on policy decisions.

Conclusion: The contingency model offers researchers and policymakers a flexible framework for aligning policymaking processes with available evidence. The model also underscores the importance of context-specific approaches to evidence-informed policymaking. The model could enhance evidence-informed policymaking capacity, improving health outcomes and system performance. Further research should validate and extend the model empirically across diverse contexts.