Evidence map›Paper›PMID 28812807›Full record

ArticleInternational journal of health policy and management2017

Health Technology Assessment: Global Advocacy and Local Realities Comment on "Priority Setting for Universal Health Coverage: We Need Evidence-Informed Deliberative Processes, Not Just More Evidence on Cost-Effectiveness".

Kalipso Chalkidou, Ryan Li, Anthony J Culyer, Amanda Glassman, Karen J Hofman, Yot Teerawattananon

Abstract readComment
In one paragraph

Article in International journal of health policy and management, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  10. Accelerating access to medicines in a changing world.Bulletin of the World Health Organization · 2020
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Kalipso ChalkidouInstitute of Global Health Innovation, Imperial College London, London, UK.
Ryan LiInstitute of Global Health Innovation, Imperial College London, London, UK.
Anthony J CulyerDepartment of Economics & Related Studies and Centre for Health Economics, University of York, York, UK.
Amanda GlassmanCenter for Global Development, Washington, DC, USA.
Karen J HofmanSchool of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Yot TeerawattananonHealth Intervention and Technology Assessment Program (HITAP), Nonthaburi, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cost-effectiveness analysis (CEA) can help countries attain and sustain universal health coverage (UHC), as long as it is context-specific and considered within deliberative processes at the country level. Institutionalising robust deliberative processes requires significant time and resources, however, and countries often begin by demanding evidence (including local CEA evidence as well as evidence about local values), whilst striving to strengthen the governance structures and technical capacities with which to generate, consider and act on such evidence. In low- and middle-income countries (LMICs), such capacities could be developed initially around a small technical unit in the health ministry or health insurer. The role of networks, development partners, and global norm setting organisations is crucial in supporting the necessary capacities.

Indexed as

Delivery of Health CareUniversal Health InsuranceBiomedical TechnologyCost-Benefit AnalysisHealth ResourcesHumansCost-Effectiveness Analysis (CEA)DeliberationEfficiencyGovernanceUniversal Coverage

Identifiers

PMID28812807
PMCPMC5384986

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.