Evidence map›Paper›PMID 41679779›Full record

ArticleBMJ global health2026

Level and determinants of district primary healthcare system technical efficiency in Ghana: two-stage stochastic frontier analysis.

Beatrice Amboko, Jacob Novignon, Rose Nabi Deborah Karimi Muthuri, Fiammetta Maria Bozzani, Anna Vassall, Edwine Barasa

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Article in BMJ global health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

  1. New article types atBMJ global health · 2026
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Beatrice AmbokoHealth Economics Research Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya indimulib06@gmail.com.ORCID 0000-0002-5754-3853
Jacob NovignonCentre for Social Policy Studies, University of Ghana, Accra, Ghana.
Rose Nabi Deborah Karimi MuthuriHealth Economics Research Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.ORCID 0000-0003-0353-8132
Fiammetta Maria BozzaniDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, England, UK.ORCID 0000-0002-9518-6885
Anna VassallGlobal Health and Development, London School of Hygiene & Tropical Medicine, London, England, UK.
Edwine BarasaHealth Economics Research Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.ORCID 0000-0001-5793-7177

Funding

the Bill and Melinda Gates Foundation INV-021815
6 · The paper itself

Abstract

backgroundPrimary healthcare (PHC) is critical towards achieving Universal Health Coverage (UHC). In Ghana, PHC is organised at the district level and plays a key role in the country's pursuit of UHC. However, many districts face challenges not only with limited resources but also with how effectively they are used. We examined how efficiently districts in Ghana use their health resources and what factors are associated with this efficiency.

methodsWe used a two-step stochastic frontier analysis model using data from 181 districts. The output variable was a composite coverage index derived from eight PHC service indicators for 2021, primarily reflecting maternal and child health and infectious disease services. Input variables included district health expenditure for 2020/2021 and the number of health facilities and clinical staff in 2021. We then assessed the associations between efficiency scores generated by the model and health systems, socioeconomic and demographic factors, such as health facility type, insurance coverage, literacy level, Gini coefficient, poverty incidence, urbanisation and population density.

resultsOn average, districts operated at 87% efficiency, with scores ranging from 65% to 99%. Two factors were associated with the efficiency. First, districts with a higher proportion of PHC facilities tended to use resources more efficiently (coeff=0.151; 95% CI=0.041 to 0.261). Second, districts with greater income inequality were less efficient, measured by the Gini coefficient (coeff=-0.858; 95% CI=-1.146 to -0.252).

conclusionDistricts in Ghana have the potential to improve PHC outputs by about 13% on average by better use of existing resources and addressing determinants of efficiency. Findings suggest that districts with a higher proportion of PHC facilities and lower income inequality tend to be more efficient. These patterns highlight the value of strengthening PHC infrastructure and pursuing equity-focused policies as part of strategies to enhance efficiency in district health systems.

Indexed as

Efficiency, OrganizationalPrimary Health CareGhanaHumansPublic Health InfrastructureSocioeconomic FactorsStochastic ProcessesUniversal Health InsuranceGlobal HealthHealth economicsHealth systemsPublic Health

Identifiers

PMID41679779
PMCPMC12911674

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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.