Evidence map›Paper›PMID 42833705›Full record

ArticleBMJ global health2026

Assessment of the performance of primary healthcare in eight African countries: based on the Composite Fuzzy Index.

Xiaolong Hu, Maryam Zaid, Jinkou Zhao, Mufuta Tshimanga, Gasto Frumence, Dominic Nkhoma, Jiayan Huang

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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. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Xiaolong HuSchool of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China.ORCID http://orcid.org/0009-0002-6933-4917
Maryam ZaidSchool of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China.
Jinkou ZhaoThe Global Fund to Fight AIDS Tuberculosis and Malaria, Grand-Saconnex, Switzerland.
Mufuta TshimangaUniversity of Zimbabwe, Harare, Zimbabwe.
Gasto FrumenceSchool of Public Health and Social Sciences, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania.
Dominic NkhomaKamuzu University of Health Sciences, Blantyre, Malawi.
Jiayan HuangSchool of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China jiayanhuang@fudan.edu.cn.ORCID http://orcid.org/0000-0003-4166-6119

Funding

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6 · The paper itself

Abstract

backgroundAfrican countries face a dual burden of infectious and non-communicable diseases, placing substantial pressure on primary healthcare (PHC) systems. Existing indicator-weighting approaches are limited in addressing redundancy and non-linear relationships. In addition, conventional composite indices often rely on linear aggregation assumptions that may not adequately reflect complex relationships among PHC performance indicators. This study proposes a novel weighting method and composite index to improve facility-level assessment of PHC performance.

methodsWe analysed nationally representative healthcare facility data from Service Provision Assessments conducted in eight African countries (Ethiopia, the Democratic Republic of the Congo, Tanzania, Malawi, Kenya, Namibia, Rwanda and Uganda). Based on the Primary Health Care Performance Initiative framework, we constructed an indicator system comprising 34 indicators across five subdomains within the Service Delivery domain. Two composite indices were calculated: the Arithmetic Mean Index (AMI) and the Composite Fuzzy Index (CFI). AMI was derived using a simple arithmetic mean, while CFI employed a distance-based aggregation approach with indicator weights estimated using Multivariate Adaptive Regression Splines. The associations between the composite indices and patient-reported satisfaction were examined, with patient satisfaction calculated as a weighted average across surveyed patients.

findingsA total of 6921 facilities were included. Overall performance across indicators was low, with particularly poor scores observed in community engagement within the population health management subdomain (mean=0.08). AMI ranged from 0.238 to 0.806, and CFI ranged from 0.237 to 0.705. Facility-level CFI scores showed a positive association with patient satisfaction (Spearman's ρ=0.039, p<0.01; Kendall's τ=0.027, p<0.01), whereas AMI showed no significant association.

conclusionPHC performance in African countries remains suboptimal across multiple dimensions. The proposed weighting and aggregation approach better captures inter-relationships among indicators and provides a more plausible assessment of PHC performance than traditional composite indices.

Indexed as

Primary Health CareQuality Indicators, Health CareAfricaHumansAfrica South of the SaharaDelivery of Health CareHealth policyHealth systems evaluation

Identifiers

PMID42833705
PMCPMC13646962

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