Evidence map›Paper›PMID 25243463›Full record

ReviewPLoS medicine2014

Equity-oriented monitoring in the context of universal health coverage.

Ahmad Reza Hosseinpoor, Nicole Bergen, Theadora Koller, Amit Prasad, Anne Schlotheuber, Nicole Valentine, John Lynch, Jeanette Vega

Abstract readReview
In one paragraph

Review in PLoS medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 3 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

72 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  20. Findings from a scoping review.Journal of clinical epidemiology · 2022
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12 more citing papers are in PubMed but not listed here.

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

8 authors.

Ahmad Reza HosseinpoorDepartment of Health Statistics and Information Systems, World Health Organization, Geneva, Switzerland.
Nicole BergenDepartment of Health Statistics and Information Systems, World Health Organization, Geneva, Switzerland.
Theadora KollerGender, Equity and Human Rights, World Health Organization, Geneva, Switzerland.
Amit PrasadCentre for Health Development, World Health Organization, Kobe, Japan.
Anne SchlotheuberDepartment of Health Statistics and Information Systems, World Health Organization, Geneva, Switzerland.
Nicole ValentineDepartment of Public Health, Environmental and Social Determinants of Health, World Health Organization, Geneva, Switzerland.
John LynchSchool of Population Health, University of Adelaide, Adelaide, Australia.
Jeanette VegaRockefeller Foundation, New York, New York, United States of America.

Funding

World Health Organization 001
6 · The paper itself

Abstract

Monitoring inequalities in health is fundamental to the equitable and progressive realization of universal health coverage (UHC). A successful approach to global inequality monitoring must be intuitive enough for widespread adoption, yet maintain technical credibility. This article discusses methodological considerations for equity-oriented monitoring of UHC, and proposes recommendations for monitoring and target setting. Inequality is multidimensional, such that the extent of inequality may vary considerably across different dimensions such as economic status, education, sex, and urban/rural residence. Hence, global monitoring should include complementary dimensions of inequality (such as economic status and urban/rural residence) as well as sex. For a given dimension of inequality, subgroups for monitoring must be formulated taking into consideration applicability of the criteria across countries and subgroup heterogeneity. For economic-related inequality, we recommend forming subgroups as quintiles, and for urban/rural inequality we recommend a binary categorization. Inequality spans populations, thus appropriate approaches to monitoring should be based on comparisons between two subgroups (gap approach) or across multiple subgroups (whole spectrum approach). When measuring inequality absolute and relative measures should be reported together, along with disaggregated data; inequality should be reported alongside the national average. We recommend targets based on proportional reductions in absolute inequality across populations. Building capacity for health inequality monitoring is timely, relevant, and important. The development of high-quality health information systems, including data collection, analysis, interpretation, and reporting practices that are linked to review and evaluation cycles across health systems, will enable effective global and national health inequality monitoring. These actions will support equity-oriented progressive realization of UHC.

Indexed as

Global HealthHealth ResourcesHealth Status DisparitiesHumansSocioeconomic FactorsUniversal Health Insurance

Identifiers

PMID25243463
PMCPMC4171107

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.