Evidence map›Paper›PMID 30665412›Full record

ArticleHealth research policy and systems2019

What, why and how do health systems learn from one another? Insights from eight low- and middle-income country case studies.

Sophie Witter, Ian Anderson, Peter Annear, Abiodun Awosusi, Nitin N Bhandari, Nouria Brikci, Blandine Binachon, Tata Chanturidze, Katherine Gilbert, Charity Jensen and 4 more

Abstract read
In one paragraph

Article in Health research policy and systems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Sophie WitterReBUILD and Institute for Global Health and Development, Queen Margaret University Edinburgh, Musselburgh, EH21 2UU, United Kingdom. switter@qmu.ac.uk.ORCID http://orcid.org/0000-0002-7656-6188
Ian AndersonCrawford School of Public Policy, Australian National University, Canberra, Australia.
Peter AnnearNossal Institute for Global Health, University of Melbourne, Melbourne, Australia.
Abiodun AwosusiOxford Policy Management (OPM), Oxford, United Kingdom.
Nitin N BhandariOxford Policy Management (OPM), Oxford, United Kingdom.
Nouria BrikciOxford Policy Management (OPM), Oxford, United Kingdom.
Blandine BinachonOxford Policy Management (OPM), Oxford, United Kingdom.
Tata ChanturidzeOxford Policy Management (OPM), Oxford, United Kingdom.
Katherine GilbertNossal Institute for Global Health, University of Melbourne, Melbourne, Australia.
Charity JensenOxford Policy Management (OPM), Oxford, United Kingdom.
Tomas LievensOxford Policy Management (OPM), Oxford, United Kingdom.
Barbara McPakeNossal Institute for Global Health, University of Melbourne, Melbourne, Australia.
Snehashish RaichowdhuryOxford Policy Management (OPM), Oxford, United Kingdom.
Alex JonesOxford Policy Management (OPM), Oxford, United Kingdom.

Funding

Bill and Melinda Gates Foundation Oxford Policy Management
6 · The paper itself

Abstract

backgroundAll health systems struggle to meet health needs within constrained resources. This is especially true for low-income countries. It is critical that they can learn from wider contexts in order to improve their performance. This article examines policy transfer and evidence use linked to it in low- and middle-income settings. The objective was to inform international investments in improved learning across health systems.

methodsThe article uses a comparative case study design, drawing on case studies conducted in Bangladesh, Burkina Faso, Cambodia, Ethiopia, Georgia, Nepal, Rwanda and Solomon Islands. One or two recent health system reforms were selected in each case and 148 key informants were interviewed in total, using a semi-structured tool focused on different stages of the policy cycle. Interviewees were selected for their engagement in the policy process and represented political, technical, development partner, non-governmental, academic and civil society constituencies. Data analysis used a framework approach, allowing for new themes to be developed inductively, focusing initially on each case and then on patterns across cases.

resultsThe selected policies demonstrated a range of influences of externally imposed, co-produced and home-grown solutions on the development of initial policy ideas. Eventual uptake of policy was strongly driven in most settings by local political economic considerations. Policy development post-adoption demonstrated some strong internal review, monitoring and sharing processes but there is a more contested view of the role of evaluation. In many cases, learning was facilitated by direct personal relationships with local development partner staff. While barriers and facilitators to evidence use included supply and demand factors, the most influential facilitators were incentives and capacity to use evidence.

conclusionsThese findings emphasise the agency of local actors and the importance of developing national and sub-national institutions for gathering, filtering and sharing evidence. Developing demand for and capacity to use evidence appears more important than augmenting supply of evidence, although specific gaps in supply were identified. The findings also highlight the importance of the local political economy in setting parameters within which evidence is considered and the need for a conceptual framework for health system learning.

Indexed as

Delivery of Health CareDeveloping CountriesHealth PolicyPolicy MakingAfricaAsiaCapacity BuildingEvidence-Based PracticeGovernment ProgramsHealth Care ReformHealth ResourcesHumansIncomeLearningMelanesiaPoliticsEvidence useHealth systemsLearningLow-income countriesPolicy transfer

Identifiers

PMID30665412
PMCPMC6341535

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.