Child health service coverage estimation using routine health data from Ghana’s Eastern Region
Abstract
Background: Suboptimal resource allocation limits uptake of essential health services in sub-Saharan Africa. Reliable population denominators and coverage estimates are needed to better match health facility resources to local demand. An estimation approach utilising routine health data has previously been used at region-/district-level. This ecological study aimed to explore its use at lower administrative levels, taking Ghana as an example.
Methods: Data collected by Ghanaian health facilities from 2017-2020 were obtained from the District Health Information Management System and used to estimate childhood vaccination coverage and diarrhoea service utilisation in 2020 for the Eastern region, districts therein, and selected sub-districts and facilities. The estimation approach derived the denominator from routine data quantifying uptake of the first dose of the pentavalent vaccine and was calibrated and evaluated using household survey data.
Results: Here we show region-level coverage of 90.3% and 92.4% for second (Penta2) and third pentavalent doses, respectively, and 83.8% for the first dose of the measles-rubella vaccine. The variability and proportion of implausible (>100%) coverage estimates increase through lower levels; the Penta2 district-level median was 93.6% (IQR:87.3%-96.2%) and facility-level median 96.5% (IQR:92.0%-104.5%). At all levels, diarrhoea service utilisation estimates are lower than the survey-derived estimate; the district-level median was 7.7% (IQR:5.9%-9.6%) and facility-level median 2.3% (IQR:0.0%-5.5%).
Conclusions: Whilst this approach is useful for uncovering local variation in service uptake, integrating routine health data within geostatistical estimation approaches able to model the spatial/aspatial determinants of health-seeking may produce more accurate estimates, better informing facility-level resource allocation.
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BibTeX
@article{johnson2026child,
title = {{Child health service coverage estimation using routine health data from Ghana’s Eastern Region}},
author = {Matthew Johnson and Winfred Dotse-Gborgbortsi and Anthony Ofosu and C. Edson Utazi and Nuala McGrath and James Wright},
journal = {Communications Medicine},
year = {2026},
month = oct,
doi = {10.1038/s43856-026-01946-3},
url = {https://www.nature.com/articles/s43856-026-01946-3},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Child health service coverage estimation using routine health data from Ghana’s Eastern Region
AU - Matthew Johnson
AU - Winfred Dotse-Gborgbortsi
AU - Anthony Ofosu
AU - C. Edson Utazi
AU - Nuala McGrath
AU - James Wright
PY - 2026
DA - 2026/10/09
JO - Communications Medicine
DO - 10.1038/s43856-026-01946-3
UR - https://www.nature.com/articles/s43856-026-01946-3
AB - Background: Suboptimal resource allocation limits uptake of essential health services in sub-Saharan Africa. Reliable population denominators and coverage estimates are needed to better match health facility resources to local demand. An estimation approach utilising routine health data has previously been used at region-/district-level. This ecological study aimed to explore its use at lower administrative levels, taking Ghana as an example. Methods: Data collected by Ghanaian health facilities from 2017-2020 were obtained from the District Health Information Management System and used to estimate childhood vaccination coverage and diarrhoea service utilisation in 2020 for the Eastern region, districts therein, and selected sub-districts and facilities. The estimation approach derived the denominator from routine data quantifying uptake of the first dose of the pentavalent vaccine and was calibrated and evaluated using household survey data. Results: Here we show region-level coverage of 90.3% and 92.4% for second (Penta2) and third pentavalent doses, respectively, and 83.8% for the first dose of the measles-rubella vaccine. The variability and proportion of implausible (>100%) coverage estimates increase through lower levels; the Penta2 district-level median was 93.6% (IQR:87.3%-96.2%) and facility-level median 96.5% (IQR:92.0%-104.5%). At all levels, diarrhoea service utilisation estimates are lower than the survey-derived estimate; the district-level median was 7.7% (IQR:5.9%-9.6%) and facility-level median 2.3% (IQR:0.0%-5.5%). Conclusions: Whilst this approach is useful for uncovering local variation in service uptake, integrating routine health data within geostatistical estimation approaches able to model the spatial/aspatial determinants of health-seeking may produce more accurate estimates, better informing facility-level resource allocation.
SN - 2730-664X
ER -