Using routinely collected health data to estimate child health service coverage in Ghanaian health facilities

Background Suboptimal resource allocation limits uptake of essential health services in sub-Saharan Africa. Reliable population denominators and intervention coverage estimates may inform allocation such that health facility resources better match demand. An approach utilising routinely collected health data has previously been used for region-/district-level estimation. 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 assumed shared utilisation patterns for benchmark/target interventions (providing denominators and numerators, respectively), and was calibrated and evaluated using household survey data. Results Region-level coverage estimates of 90.3% and 92.4% were obtained for second (Penta2) and third doses of the pentavalent vaccine, and 83.8% for the first dose of the measles-rubella vaccine. The variability and proportion of implausible (> 100%) coverage estimates increased through lower levels; the Penta2 district-level median was 93.6% (IQR:87.3%-96.2%) and facility-level median was 96.5% (IQR:92.0%-104.5%). At all levels, diarrhoea service utilisation estimates were lower than the survey-derived estimate; the district-level median was 7.7% (IQR:5.9%-9.6%) and facility-level median was 2.3% (IQR:0.0%-5.5%). Conclusions Whilst this approach is useful for uncovering local variation in service uptake, integrating routinely collected health data with alternative approaches that explicitly recognise inter-facility competition and spatial/aspatial determinants of health-seeking may produce more accurate estimates, better informing facility-level resource allocation.