Rugged landscapes: complexity and implementation science
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METHODOLOGY
Open Access
Rugged landscapes: complexity and implementation science Joseph T. Ornstein1,2* , Ross A. Hammond1,3 , Margaret Padek1,4,5 , Stephanie Mazzucca1 and Ross C. Brownson1 Abstract Background: Mis-implementation—defined as failure to successfully implement and continue evidence-based programs—is widespread in public health practice. Yet the causes of this phenomenon are poorly understood. Methods: We develop an agent-based computational model to explore how complexity hinders effective implementation. The model is adapted from the evolutionary biology literature and incorporates three distinct complexities faced in public health practice: dimensionality, ruggedness, and context-specificity. Agents in the model attempt to solve problems using one of three approaches—Plan-Do-Study-Act (PDSA), evidence-based interventions (EBIs), and evidence-based decision-making (EBDM). Results: The model demonstrates that the most effective approach to implementation and quality improvement depends on the underlying nature of the problem. Rugged problems are best approached with a combination of PDSA and EBI. Context-specific problems are best approached with EBDM. Conclusions: The model’s results emphasize the importance of adapting one’s approach to the characteristics of the problem at hand. Evidence-based decision-making (EBDM), which combines evidence from multiple independent sources with on-the-ground local knowledge, is a particularly potent strategy for implementation and quality improvement. Keywords: Complexity, Agent-based modeling, Evidence-based decision-making, Mis-implementation
Background Contributions to the literature
• Identifies the conditions under which mis-implementation is more or less likely to occur • Provides a theoretical foundation for approaches like evidence-based decision-making • Develops an agent-based model with fully open-source code that scholars can replicate and incorporate into their own research
*Correspondence: [email protected] Brown School, Washington University in St. Louis, Brookings Drive, St. Louis, MO, USA Full list of author information is available at the end of the article 1
Mis-implementation is an emerging area of interest for public health researchers and practitioners [1–3]. The term refers to the premature termination of evidencebased programs or the failure to de-implement nonevidence-based programs [1], and recent evidence suggests that it is a widespread problem in public health practice. Only 58 to 62% of public health programs are evidence-based [4, 5], and 37% of chronic disease prevention staff in state health departments report discontinuing evidence-based programs [3]. While the field of implementation science has explored de-implementation of unnecessary, low-value, or overused care [6–9], there has been little study of the processes that sustain nonevidence-based programs [3, 7]. One such example is the widespread continuation of the DARE (Drug Abuse
© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Att
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