Evidence map›Paper›PMID 25889124›Full record

ArticleBMC medicine2015

Benchmarking health system performance across districts in Zambia: a systematic analysis of levels and trends in key maternal and child health interventions from 1990 to 2010.

Katherine Ellicott Colson, Laura Dwyer-Lindgren, Tom Achoki, Nancy Fullman, Matthew Schneider, Peter Mulenga, Peter Hangoma, Marie Ng, Felix Masiye, Emmanuela Gakidou

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
12.1field-weighted citation impact, top 2% of its field
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

17 citing papers in PubMed, 32 citations in OpenAlex.

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  5. A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa.International journal of environmental research and public health · 2020
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  14. In Response.The American journal of tropical medicine and hygiene · 2016
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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

10 authors at 2 institutions in 2 countries.

Katherine Ellicott ColsonUniversity of California, Berkeley (UC Berkeley), Berkeley, CA, USA. kecolson@gmail.com.
Laura Dwyer-LindgrenInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. ladwyer@uw.edu.
Tom AchokiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. n_achoki@yahoo.com.
Nancy FullmanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. nf4@uw.edu.
Matthew SchneiderUSAID, Washington, DC, USA. matthew.schneider1324@gmail.com.
Peter MulengaClinton Health Access Initiative, Lusaka, Zambia. pmulengamusonda@yahoo.com.
Peter HangomaDepartment of Economics, University of Bergen, Bergen, Norway. peterhangoma555@yahoo.com.
Marie NgInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. marieng@uw.edu.
Felix MasiyeInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. fmasiye@yahoo.com.
Emmanuela GakidouInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. gakidou@uw.edu.
Institute for Health Metrics and Evaluation · USUniversity of Zambia · ZM

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAchieving universal health coverage and reducing health inequalities are primary goals for an increasing number of health systems worldwide. Timely and accurate measurements of levels and trends in key health indicators at local levels are crucial to assess progress and identify drivers of success and areas that may be lagging behind.

methodsWe generated estimates of 17 key maternal and child health indicators for Zambia's 72 districts from 1990 to 2010 using surveys, censuses, and administrative data. We used a three-step statistical model involving spatial-temporal smoothing and Gaussian process regression. We generated estimates at the national level for each indicator by calculating the population-weighted mean of the district values and calculated composite coverage as the average of 10 priority interventions.

resultsNational estimates masked substantial variation across districts in the levels and trends of all indicators. Overall, composite coverage increased from 46% in 1990 to 73% in 2010, and most of this gain was attributable to the scale-up of malaria control interventions, pentavalent immunization, and exclusive breastfeeding. The scale-up of these interventions was relatively equitable across districts. In contrast, progress in routine services, including polio immunization, antenatal care, and skilled birth attendance, stagnated or declined and exhibited large disparities across districts. The absolute difference in composite coverage between the highest-performing and lowest-performing districts declined from 37 to 26 percentage points between 1990 and 2010, although considerable variation in composite coverage across districts persisted.

conclusionsZambia has made marked progress in delivering maternal and child health interventions between 1990 and 2010; nevertheless, substantial variations across districts and interventions remained. Subnational benchmarking is important to identify these disparities, allowing policymakers to prioritize areas of greatest need. Analyses such as this one should be conducted regularly and feed directly into policy decisions in order to increase accountability at the local, regional, and national levels.

Indexed as

BenchmarkingChildChild WelfareData CollectionFamilyFemaleHumansInfantMaternal Health ServicesMaternal WelfareNational Health ProgramsPregnancySocioeconomic FactorsZambia

Identifiers

PMID25889124
PMCPMC4382853
OpenAlexW2142533311

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.