BMJ Global Health最新文献

Community engagement and local governance are important components of health interventions aiming to empower local populations. Yet, there is limited evidence on how to effectively engage with communities and codevelop interventions, especially in Southeast Asian contexts. Despite rapid progress, the Lao People's Democratic Republic (Lao PDR) still has high maternal and child mortality, with essential service coverage showing significant disparities across socioeconomic strata. Long-standing challenges in community health were exacerbated by the COVID-19 pandemic and reinforced by poor trust between users and health providers. However, the pandemic also provided an opportunity to develop approaches for enhanced community engagement and local governance capacity to tackle health inequities. The Community Network Engagement for Essential Healthcare and COVID-19 Responses through Trust (CONNECT) Initiative, developed by the Lao PDR government, WHO and partners, has resulted in initial positive outcomes in community health such as increased vaccination uptake, facility births and trust in health providers. This case study describes the iterative, adaptive process by which the CONNECT Initiative was developed, and how the core components, key stakeholders, theory of change and evaluation framework evolved from grounded observations and hypotheses. Lessons learnt include (1) awareness of entry points and existing structures to strengthen local governance for health through mutually beneficial intersectoral collaboration; (2) building relationships and trust with an adaptive, grounds-up approach for sustainability and scalability. As a model which can be adapted to other settings, this case study provides evidence on how to engage with communities, strengthen local governance and codevelop interventions towards greater health equity.

Background: Human resources are a key determinant for the quality of healthcare and health outcomes. Several human resource management approaches or practices have been proposed and implemented to better understand and address health workers' challenges with mixed results particularly in low- and middle-income countries (LMICs). The aim of this framework synthesis was to review the human resources frameworks commonly available to address human resources for health issues in LMIC.

Methods: We searched studies in Medline, Embase, CAB Global Health, CINAHL (EBSCO) and WHO global Index Medicus up to 2021. We included studies that provided frameworks to tackle human resources for health issues, especially for LMICs. We synthesised the findings using a framework and thematic synthesis methods.

Results: The search identified 8574 studies, out of which 17 were included in our analysis. The common elements of different frameworks are (in descending order of frequency): (1) functional roles of health workers; (2) health workforce performance outcomes; (3) human resource management practises and levers; (4) health system outcomes; (5) contextual/cross-cutting issues; (6) population health outcomes and (7) the humanness of health workers. All frameworks directly or indirectly considered themes around the functional roles of health workers and on the outcomes of health workforce activities, while themes concerning the humanness of health workers were least represented. We propose a synthesised Human-Centred Health Workforce Framework.

Conclusions: Several frameworks exist providing different recurring thematic areas for addressing human resources for health issues in LMIC. Frameworks have predominantly functional or instrumental dimensions and much less consideration of the humanness of health workers. The paradigms used in policy making, development and funding may compromise the effectiveness of strategies to address human resources challenges in LMIC. We propose a comprehensive human resources for health framework to address these pitfalls.

Introduction: This study examines the impact of China's family doctor system (FDS) on healthcare utilisation and costs among diabetic patients with distinct long-term service utilisation patterns.

Methods: Conducted in City A, eastern China, this retrospective cohort study used data from the Health Information System and Health Insurance Claim Databases, covering diabetic patients from 1 January 2014 to 31 December 2019.Patients were categorised into service utilisation trajectories based on quarterly outpatient visits to community health centres (CHCs) and secondary/tertiary hospitals from 2014 to 2017 using group-based trajectory models. Propensity score matching within each trajectory group matched FDS-enrolled patients (intervention) with non-enrolled patients (control). Difference-in-differences analysis compared outcomes between groups, with a SUEST test for cross-model comparison. Outcomes included outpatient visits indicator, costs indicator and out-of-pocket (OOP) expenses.

Results: Among 17 232 diabetic patients (55.21% female, mean age 62.85 years), 13 094 were enrolled in the FDS (intervention group) and 4138 were not (control group). Patients were classified into four trajectory groups based on service utilisation from 2014 to 2017: (1) low overall outpatient utilisation, (2) high CHC visits, (3) high secondary/tertiary hospital visits and (4) high overall outpatient utilisation. After enrolled in FDS From 2018 to 2019, the group with high secondary/tertiary hospital visits saw a 6.265 increase in CHC visits (225.4% cost increase) and a 3.345 decrease in hospital visits (55.5% cost reduction). The high overall utilisation group experienced a 4.642 increase in CHC visits (109.5% cost increase) and a 1.493 decrease in hospital visits. OOP expenses were significantly reduced across all groups.

Conclusion: The FDS in China significantly increases primary care utilisation and cost, while reducing hospital visits and costs among diabetic patients, particularly among patients with historically high hospital usage. Policymakers should focus on enhancing the FDS to further encourage primary care usage and improve chronic disease management.

Health-related stigma plays a significant role in the burden of various health conditions such as neglected tropical diseases and mental illnesses, and undermines successful health outcomes. Stigmatised individuals can face lifelong socioeconomic consequences because of their condition. It is broadly recognised that culturally salient factors interact with the way stigma is expressed in different local contexts. This study aimed to capture cultural capabilities that shape health-related stigma in Indonesia, using the 'what matters most' (WMM) stigma framework. In this qualitative research, 15 in-depth interviews with experts in the field of Indonesian culture and health studies were conducted, followed by a group discussion. Data were collected between April and September 2021, and analysed using thematic content analysis. The analysis shows that cultural values such as communal participation in local networks and the 'shame culture' shapes experiences of stigma in Indonesia. Moreover, the participants explained that achieving full standing in the Indonesian context meant contributing to the collective interest and maintaining the family reputation. Personhood is also related to socially defined gender roles. For example, community participation was often influenced by patriarchal values, which lead to differences in access to life opportunities, while recognition in the family was often connected to complying with gender roles. This study contributes to research on the cultural shaping of health-related stigma involving the WMM framework in the Indonesian context. Future research should focus on the perspectives of those who are affected by stigmatised conditions and on integrating these insights in the assessment and reduction of health-related stigma.

Background: Substandard and falsified medicines (SFMs) are a public health concern of global importance. Postmarket surveillance in the form of medicine sampling and quality testing can prevent and detect SFM, however, there is remarkably scarce evidence about the cost and value for money of these activities: how much do they cost and how effective are they in detecting SFM?

Methods: Between February and October 2022, Systematic Tracking of At Risk Medicines (STARmeds) collected and analysed for quality 1274 samples of 5 medicines from physical and online retail outlets in 7 Indonesian districts. We collated data on the resources consumed by STARmeds, related to all stages of medicines sampling and quality testing including design, fieldwork and laboratory analysis. We used activity-based costing principles to calculate the financial and economic cost of medicine quality surveillance from the perspective of a hypothetical medicines' regulator. We calculated the cost per day and per week of fieldwork, per sample collected and per substandard sample. We used bootstrapping to capture uncertainty in the number of samples collected, by seller location type (urban, rural and online).

Results: The total cost of sampling and testing medicines from the market was US$712 964 (current 2022 values). Laboratory costs represented the largest share (70%), followed by other direct costs (12%) and indirect costs (7%). On average, it costs STARmeds US$479 (95% CI US$462 to US$516) to collect one medicine sample and US$5990 (95% CI US$5601 to US$6258) to identify one substandard sample.

Conclusion: Our findings bring urgently needed and novel information on the cost and value for money of medicine quality surveillance. These may support planning and budgeting of the Indonesian pharmaceutical regulator, but also of regulators and researchers elsewhere, particularly in low-income and middle-income settings, as well as international organisations with health regulation and quality of care remits.

Background: Indigenous knowledge and responses were implemented during the COVID-19 pandemic to protect health, showcasing how Indigenous communities participation in health systems could be a pathway to increase resilience to emergent hazards like climate change. This study aimed to inform efforts to enhance climate change resilience in a health context by: (1) examining if and how adaptation to climate change is taking place within health systems in the Peruvian Amazon, (2) understanding how Indigenous communities and leaders' responses to climatic hazards are being articulated within the official health system and (3) to provide recommendations to increase the climate change resilience of Amazon health systems.

Methods: This study was conducted among two Peruvian Amazon healthcare networks in Junin and Loreto regions. A mixed methodology design was performed using a cross-sectional survey (13 healthcare facilities), semistructured interviews (27 official health system participants and 17 Indigenous participants) and two in-person workshops to validate and select key priorities (32 participants). We used a climate-resilient health system framework linked to the WHO health systems building blocks.

Results: Indigenous and official health systems in the Peruvian Amazon are adapting to climate change. Indigenous responses included the use of Indigenous knowledge on weather variability, vegetal medicine to manage health risks and networks to share food and resources. Official health responses included strategies for climate change and response platforms that acted mainly after the occurrence of climate hazards. Key pathways to articulate Indigenous and official health systems encompass incorporating Indigenous representations in climate and health governance, training the health work force, improving service delivery and access, strengthening the evidence to support Indigenous responses and increasing the budget for climate emergency responses.

Conclusions: Key resilience pathways call for a broader paradigm shift in health systems that recognises Indigenous resilience as valuable for health adaptation, moves towards a more participatory health system and broadens the vision of health as a dimension inherently tied to the environment.

Introduction: The COVID-19 pandemic triggered one of the largest global health and economic crises in recent history. COVID-19 vaccination (CV) has been the central tool for global health and macroeconomic recovery, yet estimates of CV's global health and macroeconomic value remain scarce.

Methods: We used regression analyses to measure the impact of CV on gross domestic product (GDP), infections and deaths. We combined regression estimates of vaccine-averted infections and deaths with estimates of quality-adjusted life years (QALY) losses, and direct and indirect costs, to estimate three broad value components: (i) QALY gains, (ii) direct and indirect costs averted and (iii) GDP impacts. The global value is the sum of components over 148 countries between January 2020 and December 2021 for CV generally and for Pfizer-BioNTech specifically.

Results: CV's global value was US$5.2 (95% CI US$4.1 to US$6.2) trillion, with Pfizer-BioNTech's vaccines contributing over US$1.9 (95% CI US$1.5 to US$2.3) trillion. Varying key parameters results in values 10%-20% higher or lower than the base-case value. The largest value component was GDP impacts, followed by QALY gains, then direct and indirect costs averted. CV provided US$740 of value per dose, while Pfizer-BioNTech specifically provided >US$1600 per dose. We estimated conservative benefit-cost ratios of 13.9 and 30.8 for CV and Pfizer-BioNTech, respectively.

Conclusions: We provide the first estimates of the broad value of CV incorporating GDP, QALY and direct and indirect cost impacts. Through December 2021, CV produced significant health and economic value, represented strong value for money and produced significant macroeconomic benefits that should be considered in vaccine evaluation.

Background: Malaria mortality is influenced by several factors including climatic and environmental factors, interventions, socioeconomic status (SES) and access to health systems. Here, we investigated the joint effects of climatic and non-climatic factors on under-five malaria mortality at different spatial scales using data from a Health and Demographic Surveillance System (HDSS) in western Kenya.

Methods: We fitted Bayesian spatiotemporal (zero-inflated) negative binomial models to monthly mortality data aggregated at the village scale and over the catchment areas of the health facilities within the HDSS, between 2008 and 2019. First order autoregressive temporal and conditional autoregressive spatial processes were included as random effects to account for temporal and spatial variation. Remotely sensed climatic and environmental variables, bed net use, SES, travel time to health facilities, proximity from water bodies/streams and altitude were included in the models to assess their association with malaria mortality.

Results: Increase in rainfall (mortality rate ratio (MRR)=1.12, 95% Bayesian credible interval (BCI): 1.04-1.20), Normalized Difference Vegetation Index (MRR=1.16, 95% BCI: 1.06-1.28), crop cover (MRR=1.17, 95% BCI: 1.11-1.24) and travel time to the hospital (MRR=1.09, 95% BCI: 1.04-1.13) were associated with increased mortality, whereas increase in bed net use (MRR=0.84, 95% BCI: 0.70-1.00), distance to the nearest streams (MRR=0.89, 95% BCI: 0.83-0.96), SES (MRR=0.95, 95% BCI: 0.91-1.00) and altitude (MRR=0.86, 95% BCI: 0.81-0.90) were associated with lower mortality. The effects of travel time and SES were no longer significant when data was aggregated at the health facility catchment level.

Conclusion: Despite the relatively small size of the HDSS, there was spatial variation in malaria mortality that peaked every May-June. The rapid decline in malaria mortality was associated with bed nets, and finer spatial scale analysis identified additional important variables. Time and spatially targeted control interventions may be helpful, and fine spatial scales should be considered when data are available.