Level and determinants of district primary healthcare system technical efficiency in Ghana

Two-stage stochastic frontier analysis

Bibliographic Data

ID21880672
AuthorsBeatrice Amboko (0000-0002-5754-3853, Kenya Medical Research Institute), Jacob Novignon (0000-0002-4718-9328, University of Ghana), Rose Nabi Deborah Karimi Muthuri (0000-0003-0353-8132, Kenya Medical Research Institute), Fiammetta Bozzani (0000-0002-9518-6885, London School of Hygiene & Tropical Medicine), Anna Vassall (0000-0002-2911-1375, London School of Hygiene & Tropical Medicine), Edwine Barasa (0000-0001-5793-7177, Kenya Medical Research Institute)
Year2026
Volume11
Issue2
Pagese018847
Publication date2026-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBMJ Global Health (JOURNAL)
Journal identifiersISSN: 2059-7908 • E-ISSN: 2059-7908
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/bmjgh-2024-018847
PMID41679779
OpenAlexW7128679902
LanguageEN
References cited38

BACKGROUND: Primary 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. METHODS: We 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. RESULTS: On 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). CONCLUSION: Districts 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

Frontier · Healthcare system · Inequality · Primary health care · Public health · Stochastic frontier analysis · Global Health Care Issues · Global Maternal and Child Health · Healthcare Systems and Reforms