ArticleBMC health services research2018
A critique of the Uganda district league table using a normative health system performance assessment framework.
Article in BMC health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 17 citations in OpenAlex.
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- Using normalisation process theory (NPT) to explore implementation of the maternal perinatal death surveillance and response (MPDSR) policy in Uganda: a reflection.Health research policy and systems · 2024Article
- Exploring variations in the implementation of a health system level policy intervention to improve maternal and child health outcomes in resource limited settings: A qualitative multiple case study from Uganda.PLOS global public health · 2024Article
- Delineating natural catchment health districts with routinely collected health data from women's travel to give birth in Ghana.BMC health services research · 2022Article
- Healthworker preparedness for COVID-19 management and implementation experiences: a mixed methods study in Uganda's refugee-hosting districts.Conflict and health · 2021Article
- Can routine health facility data be used to monitor subnational coverage of maternal, newborn and child health services in Uganda?BMC health services research · 2021Article
- District Health Teams' Readiness to Institutionalize Integrated Community Case Management in the Uganda Local Health Systems: A Repeated Qualitative Study.Global health, science and practice · 2020Article
- Generating statistics from health facility data: the state of routine health information systems in Eastern and Southern Africa.BMJ global health · 2019Review
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Authors and funding
8 authors at 5 institutions in 4 countries.
Funding
Abstract
backgroundIn 2003 the Uganda Ministry of Health (MoH) introduced the District League Table (DLT) to track district performance. This review of the DLT is intended to add to the evidence base on Health Systems Performance Assessment (HSPA) globally, with emphasis on Low and Middle Income Countries (LMICs), and provide recommendations for adjustments to the current Ugandan reality.
methodsA normative HSPA framework was used to inform the development of a Key Informant Interview (KII) tool. Thirty Key Informants were interviewed, purposively selected from the Ugandan health system on the basis of having developed or used the DLT. KII data and information from published and grey literature on the Uganda health system was analyzed using deductive analysis.
resultsStakeholder involvement in the development of the DLT was limited, including MoH officials and development partners, and a few district technical managers. Uganda policy documents articulate a conceptually broad health system whereas the DLT focuses on a healthcare system. The complexity and dynamism of the Uganda health system was insufficiently acknowledged by the HSPA framework. Though DLT objectives and indicators were articulated, there was no conceptual reference model and lack of clarity on the constitutive dimensions. The DLT mechanisms for change were not explicit. The DLT compared markedly different districts and did not identify factors behind observed performance. Uganda lacks a designated institutional unit for the analysis and presentation of HSPA data, and there are challenges in data quality and range.
conclusionsThe critique of the DLT using a normative model supported the development of recommendation for Uganda district HSPA and provides lessons for other LMICs. A similar approach can be used by researchers and policy makers elsewhere for the review and development of other frameworks. Adjustments in Uganda district HSPA should consider: wider stakeholder involvement with more district managers including political, administrative and technical; better anchoring within the national health system framework; integration of the notion of complexity in the design of the framework; and emphasis on facilitating district decision-making and learning. There is need to improve data quality and range and additional approaches for data analysis and presentation.
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