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A framework for scaling up health interventions: lessons from large-scale improvement initiatives in Africa

Overview of attention for article published in Implementation Science, January 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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2 policy sources
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87 X users
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1 Facebook page

Citations

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245 Dimensions

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502 Mendeley
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Title
A framework for scaling up health interventions: lessons from large-scale improvement initiatives in Africa
Published in
Implementation Science, January 2016
DOI 10.1186/s13012-016-0374-x
Pubmed ID
Authors

Pierre M. Barker, Amy Reid, Marie W. Schall

Abstract

Scaling up complex health interventions to large populations is not a straightforward task. Without intentional, guided efforts to scale up, it can take many years for a new evidence-based intervention to be broadly implemented. For the past decade, researchers and implementers have developed models of scale-up that move beyond earlier paradigms that assumed ideas and practices would successfully spread through a combination of publication, policy, training, and example. Drawing from the previously reported frameworks for scaling up health interventions and our experience in the USA and abroad, we describe a framework for taking health interventions to full scale, and we use two large-scale improvement initiatives in Africa to illustrate the framework in action. We first identified other scale-up approaches for comparison and analysis of common constructs by searching for systematic reviews of scale-up in health care, reviewing those bibliographies, speaking with experts, and reviewing common research databases (PubMed, Google Scholar) for papers in English from peer-reviewed and "gray" sources that discussed models, frameworks, or theories for scale-up from 2000 to 2014. We then analyzed the results of this external review in the context of the models and frameworks developed over the past 20 years by Associates in Process Improvement (API) and the Institute for Healthcare improvement (IHI). Finally, we reflected on two national-scale improvement initiatives that IHI had undertaken in Ghana and South Africa that were testing grounds for early iterations of the framework presented in this paper. The framework describes three core components: a sequence of activities that are required to get a program of work to full scale, the mechanisms that are required to facilitate the adoption of interventions, and the underlying factors and support systems required for successful scale-up. The four steps in the sequence include (1) Set-up, which prepares the ground for introduction and testing of the intervention that will be taken to full scale; (2) Develop the Scalable Unit, which is an early testing phase; (3) Test of Scale-up, which then tests the intervention in a variety of settings that are likely to represent different contexts that will be encountered at full scale; and (4) Go to Full Scale, which unfolds rapidly to enable a larger number of sites or divisions to adopt and/or replicate the intervention. Our framework echoes, amplifies, and systematizes the three dominant themes that occur to varying extents in a number of existing scale-up frameworks. We call out the crucial importance of defining a scalable unit of organization. If a scalable unit can be defined, and successful results achieved by implementing an intervention in this unit without major addition of resources, it is more likely that the intervention can be fully and rapidly scaled. When tying this framework to quality improvement (QI) methods, we describe a range of methodological options that can be applied to each of the four steps in the framework's sequence.

X Demographics

X Demographics

The data shown below were collected from the profiles of 87 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 502 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 <1%
South Africa 1 <1%
Sierra Leone 1 <1%
Canada 1 <1%
United States 1 <1%
Unknown 495 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 105 21%
Student > Master 67 13%
Student > Ph. D. Student 63 13%
Other 43 9%
Student > Doctoral Student 34 7%
Other 87 17%
Unknown 103 21%
Readers by discipline Count As %
Medicine and Dentistry 129 26%
Social Sciences 73 15%
Nursing and Health Professions 61 12%
Psychology 20 4%
Agricultural and Biological Sciences 15 3%
Other 75 15%
Unknown 129 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 63. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 April 2024.
All research outputs
#689,457
of 25,959,914 outputs
Outputs from Implementation Science
#63
of 1,821 outputs
Outputs of similar age
#12,342
of 410,350 outputs
Outputs of similar age from Implementation Science
#3
of 37 outputs
Altmetric has tracked 25,959,914 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,821 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 410,350 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.