↓ Skip to main content

Criteria to assess potential reverse innovations: opportunities for shared learning between high- and low-income countries

Overview of attention for article published in Globalization and Health, January 2017
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

policy
1 policy source
twitter
6 X users

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
130 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Criteria to assess potential reverse innovations: opportunities for shared learning between high- and low-income countries
Published in
Globalization and Health, January 2017
DOI 10.1186/s12992-016-0225-1
Pubmed ID
Authors

Onil Bhattacharyya, Diane Wu, Kathryn Mossman, Leigh Hayden, Pavan Gill, Yu-Ling Cheng, Abdallah Daar, Dilip Soman, Christina Synowiec, Andrea Taylor, Joseph Wong, Max von Zedtwitz, Stanley Zlotkin, William Mitchell, Anita McGahan

Abstract

Low- and middle-income countries (LMICs) are developing novel approaches to healthcare that may be relevant to high-income countries (HICs). These include products, services, organizational processes, or policies that improve access, cost, or efficiency of healthcare. However, given the challenge of replication, it is difficult to identify innovations that could be successfully adapted to high-income settings. We present a set of criteria for evaluating the potential impact of LMIC innovations in HIC settings. An initial framework was drafted based on a literature review, and revised iteratively by applying it to LMIC examples from the Center for Health Market Innovations (CHMI) program database. The resulting criteria were then reviewed using a modified Delphi process by the Reverse Innovation Working Group, consisting of 31 experts in medicine, engineering, management and political science, as well as representatives from industry and government, all with an expressed interest in reverse innovation. The resulting 8 criteria are divided into two steps with a simple scoring system. First, innovations are assessed according to their success within the LMIC context according to metrics of improving accessibility, cost-effectiveness, scalability, and overall effectiveness. Next, they are scored for their potential for spread to HICs, according to their ability to address an HIC healthcare challenge, compatibility with infrastructure and regulatory requirements, degree of novelty, and degree of current collaboration with HICs. We use examples to illustrate where programs which appear initially promising may be unlikely to succeed in a HIC setting due to feasibility concerns. This study presents a framework for identifying reverse innovations that may be useful to policymakers and funding agencies interested in identifying novel approaches to addressing cost and access to care in HICs. We solicited expert feedback and consensus on an empirically-derived set of criteria to create a practical tool for funders that can be used directly and tested prospectively using current databases of LMIC programs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
United States 1 <1%
Unknown 128 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 13%
Researcher 14 11%
Student > Doctoral Student 13 10%
Student > Bachelor 11 8%
Other 11 8%
Other 21 16%
Unknown 43 33%
Readers by discipline Count As %
Medicine and Dentistry 23 18%
Social Sciences 15 12%
Business, Management and Accounting 11 8%
Nursing and Health Professions 9 7%
Engineering 5 4%
Other 21 16%
Unknown 46 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 27 April 2022.
All research outputs
#4,740,359
of 23,666,535 outputs
Outputs from Globalization and Health
#660
of 1,133 outputs
Outputs of similar age
#95,537
of 421,917 outputs
Outputs of similar age from Globalization and Health
#9
of 16 outputs
Altmetric has tracked 23,666,535 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,133 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.0. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
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 421,917 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.