Evidence map›Paper›PMID 34511135›Full record

ArticleBMC health services research2021

Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study.

Abdoulaye Maïga, Agbessi Amouzou, Moussa Bagayoko, Cheikh M Faye, Safia S Jiwani, Dauda Kamara, Ibrahim B Koroma, Osman Sankoh

Abstract read
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Article in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Abdoulaye MaïgaBloomberg School of Public Health, Department of International Health, Johns Hopkins University, 615 N Wolfe St. 21205, Baltimore, USA. amaiga1@jhu.edu.ORCID http://orcid.org/0000-0002-0475-1106
Agbessi AmouzouBloomberg School of Public Health, Department of International Health, Johns Hopkins University, 615 N Wolfe St. 21205, Baltimore, USA.
Moussa BagayokoAfrican Population and Health Research Center, Nairobi, Kenya.
Cheikh M FayeAfrican Population and Health Research Center, Nairobi, Kenya.
Safia S JiwaniBloomberg School of Public Health, Department of International Health, Johns Hopkins University, 615 N Wolfe St. 21205, Baltimore, USA.
Dauda KamaraMinistry of Health and Sanitation, Freetown, Sierra Leone.
Ibrahim B KoromaMinistry of Health and Sanitation, Freetown, Sierra Leone.
Osman SankohStatistics Sierra Leone, Freetown, Sierra Leone.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere are limited existing approaches to generate estimates from Routine Health Information Systems (RHIS) data, despite the growing interest to these data. We calculated and assessed the consistency of maternal and child health service coverage estimates from RHIS data, using census-based and health service-based denominators in Sierra Leone.

methodsWe used Sierra Leone 2016 RHIS data to calculate coverage of first antenatal care contact (ANC1), institutional delivery and diphtheria-pertussis-tetanus 3 (DPT3) immunization service provision. For each indicator, national and district level coverages were calculated using denominators derived from two census-based and three health service-based methods. We compared the coverage estimates from RHIS data to estimates from MICS 2017. We considered the agreement adequate when estimates from RHIS fell within the 95% confidence interval of the survey estimate.

resultsWe found an overall poor consistency of the coverage estimates calculated from the census-based methods. ANC1 and institutional delivery coverage estimates from these methods were greater than 100% in about half of the fourteen districts, and only 3 of the 14 districts had estimates consistent with the survey data. Health service-based methods generated better estimates. For institutional delivery coverage, five districts met the agreement criteria using BCG service-based method. We found better agreement for DPT3 coverage estimates using DPT1 service-based method as national coverage was close to survey data, and estimates were consistent for 8 out of 14 districts. DPT3 estimates were consistent in almost half of the districts (6/14) using ANC1 service-based method.

conclusionThe study highlighted the challenge in determining an appropriate denominator for RHIS-based coverage estimates. Systematic and transparent data quality check and correction, as well as rigorous approaches to determining denominators are key considerations to generate accurate coverage statistics using RHIS data.

Indexed as

Child Health ServicesHealth Information SystemsMaternal Health ServicesChildFemaleHealth FacilitiesHumansPregnancySierra LeoneSurveys and QuestionnairesData qualityMaternal and child healthMeasuring coverageRHIS dataSierra Leone

Identifiers

PMID34511135
PMCPMC8435364

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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.