Collection published in Implementation Science, Implementation Science Communications
Organized by Heather T. Gold, NYU Grossman School of Medicine, USA; Gila Neta, National Cancer Institute, USA; Todd Wagner, Stanford University, USA
Economic evaluation compares the costs and benefits among distinct courses of action. Understanding the costs of evidence-based practices (e.g., interventions, policies, programs, tools) and the associated efforts that ensure their delivery and sustainment is critical for decision makers. Although many implementation science frameworks include costs as a key construct, relatively little guidance exists on how best to measure and analyse costs within these frameworks, where there may be a narrower perspective, a short time horizon, or important contextual factors. This collection of papers in Implementation Science and Implementation Science Communications considers key issues in economic evaluation in implementation science and highlights approaches and examples to inform the field.
The collection is designed to bridge the fields of implementation science, health services research, and health economics to create a shared understanding of disciplinary overlap, enhance and inform research collaborations, and improve the state of the field and hence comparisons across implementation studies for informed decision making. Given that costs are often a perceived barrier to implementing new evidence-based interventions, greater understanding of costs and economic evaluation more generally may help optimize uptake of evidence-based implementation strategies and interventions.
This collection of papers has been funded in part by the United States National Cancer Institute and the United States Department of Veterans Affairs.
Articles have undergone each journal’s standard peer-review process and the participating journal Editors declare no competing interests. Further articles will be added in due course following peer review.
Read the associated blog: Building capacity for economic evaluation in implementation science