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Process evaluation of a social franchising model to improve maternal health: evidence from a multi-methods study in Uttar Pradesh, India

Overview of attention for article published in Implementation Science, September 2018
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Title
Process evaluation of a social franchising model to improve maternal health: evidence from a multi-methods study in Uttar Pradesh, India
Published in
Implementation Science, September 2018
DOI 10.1186/s13012-018-0813-y
Pubmed ID
Authors

Loveday Penn-Kekana, Timothy Powell-Jackson, Manon Haemmerli, Varun Dutt, Isabelle L. Lange, Aniva Mahapatra, Gaurav Sharma, Kultar Singh, Sunita Singh, Vasudha Shukla, Catherine Goodman

Abstract

A prominent strategy to engage private sector health providers in low- and middle-income countries is clinical social franchising, an organisational model that applies the principles of commercial franchising for socially beneficial goals. The Matrika programme, a multi-faceted social franchise model to improve maternal health, was implemented in three districts of Uttar Pradesh, India, between 2013 and 2016. Previous research indicates that the intervention was not effective in improving the quality and coverage of maternal health services at the population level. This paper reports findings from an independent external process evaluation, conducted alongside the impact evaluation, with the aim of explaining the impact findings. It focuses on the main component of the programme, the "Sky" social franchise. We first developed a theory of change, mapping the key mechanisms through which the programme was hypothesised to have impact. We then undertook a multi-methods study, drawing on both quantitative and qualitative primary data from a wide range of sources to assess the extent of implementation and to understand mechanisms of impact and the role of contextual factors. We analysed the quantitative data descriptively to generate indicators of implementation. We undertook a thematic analysis of the qualitative data before holding reflective meetings to triangulate across data sources, synthesise evidence, and identify the main findings. Finally, we used the framework provided by the theory of change to organise and interpret our findings. We report six key findings. First, despite the franchisor achieving its recruitment targets, the competitive nature of the market for antenatal care meant social franchise providers achieved very low market share. Second, all Sky health providers were branded but community awareness of the franchise remained low. Third, using lower-level providers and community health volunteers to encourage women to attend franchised antenatal care services was ineffective. Fourth, referral linkages were not sufficiently strong between antenatal care providers in the franchise network and delivery care providers. Fifth, Sky health providers had better knowledge and self-reported practice than comparable health providers, but overall, the evidence pointed to poor quality of care across the board. Finally, telemedicine was perceived by clients as an attractive feature, but problems in the implementation of the technology meant its effect on quality of antenatal care was likely limited. These findings point towards the importance of designing programmes based on a strong theory of change, understanding market conditions and what patients value, and rigorously testing new technologies. The design of future social franchising programmes should take account of the challenges documented in this and other evaluations.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 136 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 15%
Student > Bachelor 19 14%
Student > Ph. D. Student 14 10%
Researcher 12 9%
Student > Doctoral Student 10 7%
Other 24 18%
Unknown 36 26%
Readers by discipline Count As %
Medicine and Dentistry 21 15%
Nursing and Health Professions 20 15%
Social Sciences 19 14%
Business, Management and Accounting 4 3%
Engineering 4 3%
Other 22 16%
Unknown 46 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 28 September 2018.
All research outputs
#5,809,704
of 23,103,903 outputs
Outputs from Implementation Science
#1,007
of 1,726 outputs
Outputs of similar age
#102,317
of 340,828 outputs
Outputs of similar age from Implementation Science
#24
of 27 outputs
Altmetric has tracked 23,103,903 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,726 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.8. 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 340,828 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.