ArticlePLOS global public health2024
Drivers of success in global health outcomes: A content analysis of Exemplar studies.
Article in PLOS global public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Trends in the burden of fire, heat, and hot substances in North Africa and the Middle East, 1990-2023: an analysis of the 2023 Global Burden of Disease Study.Tropical medicine and health · 2026Article
- Community-led vaccine strategies to boost COVID-19 vaccine uptake among racialized immigrant groups in Parc Extension, Quebec: a strengths-based exemplar study.Canadian journal of public health = Revue canadienne de sante publique · 2026Article
- Article
- Family planning exemplar country selection methodology: time lag and trends analysis.BMJ global health · 2026Article
- Assessing quality of childbirth care provided by skilled health personnel in Exemplar countries.Nature medicine · 2026Article
- Sources of evidence, pathways, and processes to support disability-inclusive decision-making in low- and middle-income countries: A scoping review.PLOS global public health · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Applying a positive outlier lens is one effective approach for generating evidence to inform global health policy, program, and funding decisions. Exemplars in Global Health (EGH) is a program that studies positive outlier countries that have made extraordinary progress in health outcomes (despite limited resources) and disseminates their successes through multiple types of outputs. To date, EGH has studied, or is studying, 14 global health topics in 28 countries. This paper aims to identify findings, summarized as themes and sub-themes, that appear among all completed EGH studies. We developed a conceptual framework and used a content analysis approach to identify the top thematic areas that appear as drivers for programmatic success across EGH studies that were completed between June 2020-May 2023. The EGH studies (N = 31) spanned six topics including under-five child mortality (n = 6), childhood stunting (n = 5), community health workers (CHW) (n = 4), vaccine delivery (n = 3), COVID-19 response (n = 6), and newborn and maternal mortality reduction (n = 7) across 19 countries in sub-Saharan Africa, Latin America, South and Central Asia, and the Caribbean regions. Top drivers of success were defined as those critical or catalytic in achieving the intended outcome. Eight key drivers were identified: (1) efficient data collection and use for decision-making, (2) strong political commitment and health leadership, (3) effective stakeholder coordination, (4) a local, connected, and capacitated workforce, (5) intentional women's empowerment and engagement, (6) effective adoption and implementation of national policies, (7) effective and sustainable financing, and (8) equitable, efficient outreach and targeting. These cross-cutting drivers span a broad range of development outcomes, sectors, and populations, and indicate a need to effectively integrate people, systems, and sectors to improve global health outcomes. Findings from this study aim to support peer learning among countries and support evidence-based decision-making for funders, policymakers, and other key stakeholders.
Identifiers
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Registered trials
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.