Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2017 Sep 6;12(1):111.
doi: 10.1186/s13012-017-0640-6.

"Scaling-out" evidence-based interventions to new populations or new health care delivery systems

Affiliations
Review

"Scaling-out" evidence-based interventions to new populations or new health care delivery systems

Gregory A Aarons et al. Implement Sci. .

Abstract

Background: Implementing treatments and interventions with demonstrated effectiveness is critical for improving patient health outcomes at a reduced cost. When an evidence-based intervention (EBI) is implemented with fidelity in a setting that is very similar to the setting wherein it was previously found to be effective, it is reasonable to anticipate similar benefits of that EBI. However, one goal of implementation science is to expand the use of EBIs as broadly as is feasible and appropriate in order to foster the greatest public health impact. When implementing an EBI in a novel setting, or targeting novel populations, one must consider whether there is sufficient justification that the EBI would have similar benefits to those found in earlier trials.

Discussion: In this paper, we introduce a new concept for implementation called "scaling-out" when EBIs are adapted either to new populations or new delivery systems, or both. Using existing external validity theories and multilevel mediation modeling, we provide a logical framework for determining what new empirical evidence is required for an intervention to retain its evidence-based standard in this new context. The motivating questions are whether scale-out can reasonably be expected to produce population-level effectiveness as found in previous studies, and what additional empirical evaluations would be necessary to test for this short of an entirely new effectiveness trial. We present evaluation options for assessing whether scaling-out results in the ultimate health outcome of interest.

Conclusion: In scaling to health or service delivery systems or population/community contexts that are different from the setting where the EBI was originally tested, there are situations where a shorter timeframe of translation is possible. We argue that implementation of an EBI in a moderately different setting or with a different population can sometimes "borrow strength" from evidence of impact in a prior effectiveness trial. The collection of additional empirical data is deemed necessary by the nature and degree of adaptations to the EBI and the context. Our argument in this paper is conceptual, and we propose formal empirical tests of mediational equivalence in a follow-up paper.

Keywords: Delivery system fixed; Effectiveness; Evidence-based intervention; External validity; Implementation science; Intervention adaptation; Mediational equivalence; Multilevel mediation modeling; Population fixed; Scaling-out; Scaling-up.

PubMed Disclaimer

Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable

Competing interests

GAA is an Associate Editor and CHB is on the Editorial Board of Implementation Science. All decisions on this paper were made by another editor. NB receives salary support from a subcontract from the University of Chicago that is supported by Gilead, the maker of PrEP, which is mentioned in this paper. The authors declare that they have no other competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Schematic of scaling-out and implementation and effectiveness domains for evaluation

References

    1. Department of Health and Human Services. Dissemination and implementation research in health (R01) NIH funding opportunity: PAR-16-238. NIH grant funding opportunities; 2016. p. 2017.
    1. Campbell DT. Factors relevant to the validity of experiments in social settings. Psychol Bull. 1957;54:297–312. doi: 10.1037/h0040950. - DOI - PubMed
    1. Cook TD, Campbell DT, Day A. Quasi-experimentation: design & analysis issues for field settings. Boston: Houghton Mifflin; 1979.
    1. Cronbach LJ, Shapiro K. Designing evaluations of educational and social programs. San Francisco: Jossey-Bass; 1982.
    1. Cook TD. Social prevention and the social sciences: theoretical controversies, research problems, and evaluation strategies. Berlin: Walter de Gruyter; 1991. Meta-analysis: its potential for causal description and causal explanation within program evaluation; pp. 245–285.

Publication types

MeSH terms