Evidence map›Paper›PMID 30410743›Full record

ArticleJournal of global health2018

Linking household survey and health facility data for effective coverage measures: a comparison of ecological and individual linking methods using the Multiple Indicator Cluster Survey in Côte d'Ivoire.

Melinda K Munos, Abdoulaye Maiga, Mai Do, Glebelho Lazare Sika, Emily D Carter, Rosine Mosso, Abdul Dosso, Alejandra Leyton, Shane M Khan

Open access · goldAbstract readComparative Study
In one paragraph

Article in Journal of global health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 3 pooled it
4.4field-weighted citation impact, top 6% 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

28 citing papers in PubMed, 3 syntheses or guidelines pooled it, 44 citations in OpenAlex.

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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

9 authors at 4 institutions in 2 countries.

Melinda K MunosInstitute for International Programs, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Abdoulaye MaigaInstitute for International Programs, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Mai DoDepartment of Global Community Health and Behavioral Sciences, Tulane University School of Public Health and Tropical Medicine, Tulane, New Orleans, Louisiana, USA.
Glebelho Lazare SikaEcole Nationale Supérieure de Statistique et d'Economie Appliquée, Abidjan, Côte d'Ivoire.
Emily D CarterInstitute for International Programs, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Rosine MossoEcole Nationale Supérieure de Statistique et d'Economie Appliquée, Abidjan, Côte d'Ivoire.
Abdul DossoJohns Hopkins Center for Communication Programs, Abidjan, Côte d'Ivoire.
Alejandra LeytonDepartment of Global Community Health and Behavioral Sciences, Tulane University School of Public Health and Tropical Medicine, Tulane, New Orleans, Louisiana, USA.
Shane M KhanDivision of Data, Research and Policy, UNICEF, New York, New York, USA.
Johns Hopkins University · USÉcole Nationale Supérieure de Statistique et d'Économie Appliquée · CITulane University · USUnited Nations Children's Fund · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPopulation-based measures of intervention coverage are used in low- and middle-income countries for program planning, prioritization, and evaluation. There is increased interest in effective coverage, which integrates information about service quality or health outcomes. Approaches proposed for quality-adjusted effective coverage include linking data on need and service contact from population-based surveys with data on service quality from health facility surveys. However, there is limited evidence about the validity of different linking methods for effective coverage estimation.

methodsWe collaborated with the 2016 Côte d'Ivoire Multiple Indicator Cluster Survey (MICS) to link data from a health provider assessment to care-seeking data collected by the MICS in the Savanes region of Côte d'Ivoire. The provider assessment was conducted in a census of public and non-public health facilities and pharmacies in Savanes in May-June 2016. We also included community health workers managing sick children who served the clusters sampled for the MICS. The provider assessment collected information on structural and process quality for antenatal care, delivery and immediate newborn care, postnatal care, and sick child care. We linked the MICS and provider data using exact-match and ecological linking methods, including aggregate linking and geolinking methods. We compared the results obtained from exact-match and ecological methods.

resultsWe linked 731 of 786 care-seeking episodes (93%) from the MICS to a structural quality score for the provider named by the respondent. Effective coverage estimates computed using exact-match methods were 13%-63% lower than the care-seeking estimates from the MICS. Absolute differences between exact match and ecological linking methods were ±7 percentage points for all ecological methods. Incorporating adjustments for provider category and weighting by service-specific utilization into the ecological methods generally resulted in better agreement between ecological and exact match estimates.

conclusionsEcological linking may be a feasible and valid approach for estimating quality-adjusted effective coverage when a census of providers is used. Adjusting for provider type and caseload may improve agreement with exact match results. There remain methodological questions to be addressed to develop guidance on using linking methods for estimating quality-adjusted effective coverage, including the effect of facility sampling and time displacement.

Indexed as

Health Care SurveysMedical Record LinkageAdolescentAdultChild, PreschoolCote d'IvoireEcologyFeasibility StudiesFemaleHealth Services Needs and DemandHumansInfantInfant, NewbornInformation Storage and RetrievalMiddle AgedPatient Acceptance of Health Care

Identifiers

PMID30410743
PMCPMC6211616
OpenAlexW2893466430

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.