Background: Although youth constitute a large and growing part of the African population, their participation in health policy and governance remains limited. Despite their size and social relevance, young people are largely excluded from the formulation of health policies, implementation, and governance, reinforcing cycles of inequities and poor system responsiveness. Objectives: This narrative review consolidates evidence on barriers and enablers of youth participation in health policy and governance across Africa. Methods: We performed a structured literature search across PubMed, AJOL, Google Scholar, and key organisational repositories (WHO, UNICEF, AU, and youth network databases) for studies and reports published between 2010 and 2025. Peer-reviewed and grey literature focusing on youth participation in health policy and governance, policy processes, and program evaluations within the African context were included. Non-health-related reports or studies focusing only on service usage and not conducted in Africa were excluded. A thematic narrative synthesis was used to identify common recurring barriers, enabling factors, and potential pathways linking youth voice to governance outcomes. Results: Major barriers include ineffective and/or tokenistic institutional mechanisms, deeply rooted age and gender hierarchies, insufficient funding and infrastructure, low levels of policy literacy and mentorship, and digital and geographic divides. Enablers included rights-based legal frameworks and national youth policies, sustained mentorship and capacity building, blended digital and face-to-face mobilisation, and formal participatory bodies with clear mandates. Four mechanisms for strengthening governance through youth participation were identified: formal representation, enhancing accountability and transparency, revitalising intergenerational trust, and increased system responsiveness that promotes equity. Conclusion: Effective youth participation requires sustainable institutionalisation, adequate resources, capacity building and support, active inclusion of underrepresented youth, and monitoring indicators that track quality of participation and its impact. Future research should prioritise longitudinal impacts of youth involvement, capacity-building models, and the development of a common set of indicators to assess participation.

Since the adoption of the WHO Global Code of Practice on the International Recruitment of Health Personnel in 2010, the context of health workforce recruitment, migration, and integration has changed significantly, including the impact of the COVID-19 pandemic. This rapid review of 137 published articles and 89 grey literature sources captures key modes of recruitment, evolving pathways, and emerging issues. Seven overlapping modes of international recruitment were identified, each with different actors, advantages, and disadvantages for different interest holders: 1) Active employer-initiated recruitment; 2) Active agency-initiated recruitment; 3) Passive employer-initiated recruitment; 4) Migrant-initiated employment pathway; 5) Migrant-initiated training pathway; 6) Streamlined immigration pathways; and 7) Streamlined regulatory pathways. Key policy recommendations from this rapid review include: the need for internationally agreed-upon and utilized standard definitions of international health worker recruitment, migration and integration and more standardized conceptualizations of health worker recruitment modes and pathways; an internationally agreed-upon common minimum data standard for reporting the number and sources of the flows of different types of workers, students and faculty by recruitment, migration and integration pathway; stronger reporting instruments implemented more iteratively across the various policy actors involved in the recruitment, migration and integration of international health workers, students and faculty; and stronger forms of governance and regulation of the recruitment, migration and integration of internal health workers including model bilateral agreements that can be adopted by source and destination countries to foster longer-term arrangements explicitly for workers, students, and faculty.

Participatory approaches to decision making which involve the potential beneficiaries ensure that the decisions are acceptable and interventions effective. However, in cultures where adolescents and young women (AGYW) are marginalized, they lack access to decision-making processes- even when the decisions affect them. This is more so for undocumented AGYW who work in the informal artisanal mining sector. This paper reports on an approach that meaningfully engaged AGYW, from Uganda and Uganda, in a participatory decision making with regards to their health, and economic well being. The nominal group discussion technique supported AGYWs to identify the relevant priorities at the community, district and national levels. The AGYW identified the top priority interventions, which were validated by district and national level stakeholders. The provision of information and training if participants supported the AGYW to identify priorities which resonated with the decision makers. The process empowered the AGYW to advocate for the priority interventions. The participatory approach empowered the AGYW, and enabled them to meaningfully engage in priority setting and to advocate for themselves. The approaches used in this study are useful to researchers and decision makers who are interested in including vulnerable populations in decision making and programming.

We examine whether the COVID-19 pandemic enabled low- and middle-income countries (LMICs) to expand fiscal space for health through domestic revenue mobilization, or whether binding fiscal constraints limited health financing responses despite unprecedented system-wide pressures. Using panel data for 85 countries over 2015–2022 and system-GMM estimation, we find that taxation capacity positively affects government health expenditure, confirming fiscal space as the binding constraint on health financing. Critically, the pandemic did not systematically alter this relationship. However, we document substantial heterogeneity masked by this null average effect. Low- and lower-middle-income countries that implemented tax reforms during 2020–2021 sustained health expenditure increases through 2022, whereas countries relying on deficit financing experienced spending reversals. Upper-middle-income countries show no pandemic strengthening of the fiscal space-health relationship. These findings challenge the conventional view that health crises automatically generate political will sufficient to overcome fiscal constraints, demonstrating instead that administrative capacity to expand revenue determines whether reform windows translate into sustainable financing. For universal health coverage strategies, the results imply that building tax administration capacity during normal periods constitutes essential crisis preparation, as robust collection infrastructure cannot be rapidly developed amid sudden economic shocks.

Background: The COVID-19 pandemic exposed persistent structural inequities within and between universal health systems. We compared how social determinants of health (SDH) shaped COVID-19 mortality across Ceará (Brazil) and Portugal. Methods: We conducted a comparative ecological analysis of 21 administrative regions (Ceará=14; Portugal=7) for 2020–2022, harmonizing publicly available, aggregated data on COVID-19 deaths, population, and SDH (Human Development Index [HDI], poverty risk, literacy, income, urbanization, population density, primary-care supply, and social-protection coverage). Univariable Gamma generalized linear models (log link) screened associations; a multivariable Gamma model with heteroskedasticity-consistent (HC3) and cluster-robust standard errors assessed independent effects. Principal component analysis with k-means (k=2) explored latent territorial structure. Results: We recorded 68,394 deaths (Ceará=28,067; Portugal=40,327), corresponding to 319.1 and 389.9 per 100,000 inhabitants. PCA+k-means identified two stable vulnerability clusters (silhouette=0.761; adjusted Rand index=1.000). In multivariable models, higher HDI (β=17.749; interpreted per 0.1 increase: exp(β·0.1)≈5.9; p<0.001) and poverty risk (β=0.103; exp(β)=1.109; p=0.002) increased mortality, while literacy was protective (β=−0.024; exp(β)=0.976; p=0.036). After adjustment, the “country” indicator was not significant (p=0.597). Conclusions: COVID-19 mortality followed clear social gradients across both contexts. Poverty and low literacy amplified vulnerability, whereas development (HDI) interacted with aging and mobility to yield paradoxical risks in early waves. Differences in mortality were better explained by SDH than by national context, underscoring the need for territorially tailored, intersectoral strategies to ensure equity in future crises.

The global refugee population has nearly doubled in the last decade, and many of these populations face chronic displacement, often in neighbouring countries with limited resources. Emergency, short-term responses are being transitioned to longer term approaches, including a focus on inclusion through coverage in national health systems. However, analysis of empirical and comparative evidence on how to enact these approaches has been limited. In this article, we analyse the inclusion of refugees in six low and middle-income country (LMIC) health systems (Kenya, Kurdistan Region of Iraq (KRI), Mauritania, Pakistan, Peru and Zambia). Using a shared framework and tools, we collected data over 2023 to 2025, using document reviews, key informant interviews, focus group discussions and participatory workshops. Analysis was carried out separately for each setting, validated locally, and later compared and contrasted for synthesis. We focus on key health system domains – governance, health financing, service delivery (including health workforce) and health information systems - outlining the attributes of refugee inclusion and system integration in each, identifying patterns across the case studies and barriers and enablers. We identify leverage points for improving integration but highlight that inclusion of refugees into national health systems is complex and does not guarantee improved outcomes, especially when refugees previously benefited from a higher level of resources and are being included in strained host health systems. However, committed government leadership, coordinated international support, and multi-year investments in strengthening key components of the local health system, including enabling refugee health staff to engage effectively in it, can make the transition one which benefits both refugee and host communities.

Abstract Despite its widespread application in public financial management reforms across low- and middle-income countries, programme-based budgeting (PBB) implementation often remains relative superficial. The technical weaknesses of the reform have been widely documented; however, the political economy dynamics around the introduction and implementation of PBB in the health sector have not been studied. This comparative case study analysis of seven low and middle-income countries (Burkina Faso, Cameroon, Ghana, Kenya, Peru, Philippines, and South Africa) aims to unpack the political economy drivers of PBB reform in the health sector. The study draws from a global literature review, as well as documentary reviews and expert interviews in each of the seven study settings. Findings describe the policy processes relating to PBB introduction and implementation in the health sector, and provide a detailed, comparative stakeholder mapping and political economy analysis. This describes the position of the key actors in relation to PBB reform in health, which is explained by their interests and how PBB reform would impact them, and how they used their power to affect the PBB reform processes in health. Our analysis identifies political dynamics, processes and narratives that can be strategically leveraged to better inform PBB implementation in the health sector. It also underscores how the insights from PEA can help to advance budgeting reforms in the health sector as part of overall health financing reforms in support of UHC agenda in low and middle-income settings, which experience has shown do not lend themselves to technical solutions alone.

The National Health Service (NHS) receives thousands of complaints weekly, yet existing systems remain largely manual, inconsistent, and unable to generate strategic insights. This paper examines the potential of Artificial Intelligence (AI) and digital technologies to transform complaint and feedback management within the NHS. Using a pilot initiative at Oxford University Hospitals (OUH) as a case study, the article explores the design, implementation, and impact of an AI-enabled Complaint Management System (AI-CMS). The system leverages Natural Language Processing (NLP) to streamline complaint triage, detect emergent themes, and offer real-time analytics. We discuss the operational, financial, and ethical implications of AI-CMS deployment and highlight the need to expand its remit to cover broader patient feedback mechanisms. The findings underscore AI’s potential not only to enhance efficiency but to catalyse a shift towards learning, responsiveness, and patient-centred service redesign.

The healthcare system in the Gaza Strip has been severely compromised by prolonged conflict, infrastructure degradation, and resource limitations. Interdependent systems—water, sanitation, energy, and transport—are critical for effective healthcare delivery, yet their collapse has amplified public health crises. This study evaluates optimal strategies for rebuilding Gaza’s healthcare system and related infrastructure to improve population health outcomes. A retrospective quantitative approach was employed using data from the World Health Organization (WHO), verified local sources, and media reports. Hospital functionality, health workforce availability, medical supply continuity, and infrastructure status were assessed. Infectious disease incidence was analyzed relative to system disruptions using Spearman’s rank correlation. Healthcare system recovery was modeled with Success Tree Analysis (STA), and potential interventions were evaluated via Multi-Criteria Decision Analysis (MCDA). Of 38 hospitals assessed, only 23.7% were fully functional, with North Gaza experiencing 50% non-functional facilities. Physicians per 10,000 population declined by 45%, and only 48% of facilities had essential medicines. Electricity and water system functionality were 27% and 35%, respectively, contributing to high diarrheal disease (72.4/10,000) and respiratory infection (96.5/10,000) rates. Strong correlations were observed between infrastructure and health outcomes, including electricity vs. hospital functionality (ρ = 0.82) and water supply vs. diarrheal disease (ρ = –0.76). STA modeling indicated that integrated recovery of energy, water, and workforce could restore up to 89% of hospital functionality within five months. MCDA ranked rapid infrastructure repair, renewable energy integration, and water network rehabilitation as top strategies. The findings highlight that Gaza’s healthcare system requires coordinated, multi-sectoral interventions and spatially targeted strategies to ensure equitable access, strengthen resilience, and improve population health in conflict-affected settings.

Background: Statistical analysis is central to medical research. Generative artificial intelligence have recently emerged as potential tools to support data analysis in medical research. Objective: to evaluate the accuracy and reliability of artificial intelligence in performing statistical analyses by comparing its output with previously published statistical results revised by professional biostatisticians. Methods: An observational, comparative secondary analysis of 14 previously analyzed datasets. The GPT-4o analyses were conducted between May and September 2025 using a standardized prompt chain. A 13-item rubric was used to score each task (2 = identical, 1 = almost identical, and 0 = Dissimilar). The dataset-level categories were pre-specified as perfect (100%), good (90%–<100%), and poor (<90%). Results: The GPT-4o model correctly identified the file structure in 13/14 (92.9%) datasets and accurately assessed normality in 12/14 (85.7%). Its errors were mainly schema-related, treating coded categorical fields as numeric and missing some composite recoding; therefore, numeric values sometimes differed even when significance decisions matched human analyses. Of the 14 datasets, the GPT-4o output was classified as perfect for two (14.3%), good for 10 (71.4%), and poor for two (14.3%). Conclusion: The GPT-4o model performed well on structured tasks with clear prompts and correct variable typing, often converging with human analyses on significance decisions. However, it struggled with coded categorical data, complex recoding, and publication-ready tables, with numerical discrepancies in several datasets. While the tested GenAI model could assist early analytical work under expert supervision, further research is warranted, particularly with evolving GenAI models.

This study examines the geospatial and intertemporal impact of Ghana’s National Health Insurance Scheme (NHIS) on household health expenditure using nationally representative data from the 2022 Annual Household Income and Expenditure Survey (AHIES). Employing propensity score matching (PSM) to control for selection bias, the analysis reveals that NHIS significantly reduces health spending across most of Ghana’s 16 regions, with Greater Accra, Ashanti, and Central showing the largest impacts. However, regional disparities persist, with Volta Region showing no statistically significant effect. Temporally, the scheme’s effectiveness also varies, with the largest cost reductions observed in the fourth quarter of 2022, suggesting seasonal sensitivity in healthcare access and NHIS performance. The findings underscore the need for region-specific interventions, improved service delivery, and stronger inter-ministerial coordination, particularly among the Ministry of Health, NHIA, and Ghana Health Service to ensure equitable and consistent financial protection for all households, especially the poor and vulnerable ones.

Despite growing interest in self-care to advance universal health coverage, national self-care policies are largely absent in low- and middle-income countries. We used the ExpandNet framework, which provides guidance for scaling up health interventions, to assess the environmental influences on scaling up sexual and reproductive health (SRH) self-care in Mozambique. We conducted a mixed-methods analysis that drew on data collected as part of a larger multi-phase study on self-care introduction and scale-up. Our analysis included qualitative stakeholder interviews (n=16) and a quantitative consumer survey (n=606). Summary tabulations of the quantitative survey data were coded alongside the qualitative data in an integrated analysis. Stakeholders described how self-care could complement limited primary care infrastructure and human resources but noted that inadequate public resources could hinder effective scale-up due to the need to provide follow-up services, including linkage to care and timely treatment after self-testing. Stakeholders noted the role of the private sector, particularly pharmacies, in the delivery of self-care products . Many were optimistic that community sensitization activities could address cultural barriers to SRH self-care scale-up, particularly in rural areas. Potential demand for self-care was demonstrated in the more than 85% of consumers who said they would be likely or very likely to use a home-based HPV self-sampling kit and the 72% of consumers who had never used self-injectable contraception who said they would be likely or very likely to use it in the future. This analysis of the environment for SRH self-care scale-up using the ExpandNet framework can serve as a guide to others developing self-care scale-up strategies in other settings. Key considerations for SRH self-care in Mozambique may include investments in follow-up care, integration of the private sector, implementation of a supportive social behavior change strategy, and tailored approaches to reach populations with the greatest health needs.

Background: Nigeria confronts an ongoing maternal mortality crisis that contributes disproportionately to global maternal deaths. While the clinical causes are well-documented, the underlying socioeconomic determinants and entrenched health inequities remain underexplored, creating a critical knowledge gap that hinders effective resource allocation by stakeholders. Objectives: To determine the relative predictive influence of individual, population, and health system factors on maternal mortality in Nigeria using machine learning approaches. Methods: This ecological time series study examines associations between individual, population, and health system factors and maternal mortality in Nigeria (1960-2024). Using data from reputable institutions, we employed XGBoost and Random Forest algorithms to analyse the complex relationships between these multidimensional factors and maternal mortality outcomes. Results: Analysis revealed that educational attainment and service sector employment consistently predict reduced maternal mortality in Nigeria. Early marriage, vulnerable employment, rural residence, and poverty were associated with increased mortality but showed less predictive reliability. Health financing demonstrated lower reliability overall, with government expenditure decreasing maternal mortality while external funding dependence tended to increase mortality. Conclusion: This study challenges traditional perspectives on maternal mortality predictors while identifying key policy intervention areas. Future research should examine the complex relationships between education, employment, and maternal mortality to inform strategic investments.

In scenarios where patient demand exceeds hospital capacity, such as natural disasters, terrorist attacks, or staffing shortages, the rapid discharge of patients who are identified through reverse triage methodologies can create surge capacity. Numerous resources and studies have evaluated this concept, but current tools tend to be extensive and siloed, which may make them difficult to use during emergencies. To prepare the largest municipal healthcare system in the United States for situations requiring rapid patient discharge, New York City Health + Hospital’s Central Office Emergency Management sought to develop a short, synthesized, and user-friendly plan. After consulting experts and reviewing existing peer-reviewed papers, gray literature, and internal facility documents, the team created a 7-page Response Action Checklist - Risk-based, Abbreviated, Patient Identification Discharge Tool (RAPID) to synthesize important content. This tool was successfully utilized during a resident labor action in May 2023, illustrating that its utility may extend beyond the system in which it was used. Future work should be done to validate and improve upon this tool.

Communication plays an essential role in the transmission of information and feelings between individuals, significantly influencing emotional support, particularly in healthcare settings. Empathy emerges as a critical element for the effectiveness of this process, as it enables healthcare professionals to understand and adequately address the needs of patients and their relatives. It is imperative that communication remains continuous and infused with respect, considering the preferences and goals established throughout the treatment. Despite the intrinsic relevance of the communicative role of physicians, a considerable number of patients express difficulties in accessing information that is both clear and appropriate, especially in circumstances of severe illness and in the context of palliative care. Recurring complaints include the use of overly technical terminology, a lack of empathy, and ineffective methods in transmitting unfavorable news. On the other hand, relatives who report satisfaction emphasize the importance of careful and honest dialogues that preserve a sense of hope. Patients and their relatives express the desire for open communication that aligns with their emotional needs, valuing aspects such as empathy, clarity, and the recognition of the role played by caregivers. This study aims to investigate the dynamics of breaking bad news in the Intensive Care Unit (ICU), emphasizing the perceptions recorded by patients and their relatives.

This study examines Nigeria’s slow progress toward universal healthcare coverage (UHC), analyzing the policy development process and the roles of various actors involved. Using social network analysis (SNA) and qualitative methods, we conducted structured interviews and documentary analysis to identify key policy actors and their relationships within the UHC network. The SNA revealed a complex structural network categorizing actors into four groups: power actors, peripheral actors, gatekeepers (brokers), and isolated actors. These classifications determined their access to information, professional support, and resources. A stable subset of seven organizations demonstrated significant centrality and influence across multiple relationships, while other organizations were central only in specific contexts. Senior government officials emerged as the primary influencers in UHC policy development and decision-making, controlling information flow within the policy network. These actors played crucial roles in advancing and impeding UHC progress in Nigeria. The study identifies political, policy-oriented, financial, and organizational constraints as significant barriers to UHC implementation. Addressing these challenges is essential for improving financial protection and ensuring Nigerians have equitable access to essential healthcare services. Our findings contribute to understanding the complex interplay of actors in healthcare policy development in low- and middle-income countries, offering insights that could help accelerate progress toward achieving UHC in Nigeria and similar settings.

Abstract Background Although a complexity theory lens can help to understand national policy implementation at a local government level, application of this lens often remains metaphorical. We illustrate how complexity concepts (adaptation, feedback, emergence and co-evolution) can be used practically in research on policy implementation using a UK case study (Future in Mind; FiM), aimed at improving children’s access to mental health services in a municipality in northern England. Methods We re-analysed interview data with staff from local government, the National Health Service, schools, and the voluntary and community sector (n=31) involved in implementing FiM and coded this data in NVivo12 using complexity concepts as sensitising constructs. Findings We identified 5 feedback loops: two positives (1. flexing the training offer; 2. new skills, knowledge and behaviour by non-specialist staff) and three negatives (3. short termism, 4. free rider behaviour, 5. professional boundaries). These loops energised local adaptations of FiM by school and NHS staff, leading to system-level change (emergence), with the school system becoming more responsive to the mental wellbeing needs of children and young people, and shifts across systems (co-evolution), by developing joint values and language between schools and NHS. Conclusions We demonstrate the importance of positive and negative feedback loops for evidencing system-level change and shifts across systems. Our findings provide new insights into unintended consequences of policy implementation and starting positions for implementers to utilise feedback for generating impact. We argue for blurring of boundaries between implementation and evaluation in policy research to optimise the use of feedback.

Evidence shows limited use of routine data to support health actions in lower and middle-income countries. To address that, there are several ongoing efforts to strengthen routine health information systems which are largely crippled by the fragmented nature of the health system. This review determines factors influencing routine data use at different health system levels. We scoped up four literature sources, i.e., PubMed, IEEE Xplore, the Public Library of Science (PLOS), and Google Scholar for the article published between January 2019 and December 2023. Three reviewers independently screened article titles, abstracts, and full text against inclusion and exclusion criteria, following the Arksey and O’Malley and PRISMA framework to guide the review process. We classified our findings into three health system levels: i.e. facility, district, and national/sector-wide. Out of 387 articles retrieved from databases, 41 articles were selected for inclusion, where the majority of the articles (48.8%), were on the health facility level. The study found that factors influencing the use of routine data vary across health system levels, with human resource capacity and friendly data collection tools being more important at the facility level. In contrast, the availability, and capacity to use analytical tools and governance structures were more reported at the district and national levels. Further, capacity building in health information systems, IT infrastructure, and regular supervision, were identified as crucial across all health system levels. We argue for focused interventions to be designed to institutionalize routine data use practices for better healthcare outcomes across health system levels.