Health policy and planning最新文献

Intervention evaluation is critical for determining the value of health interventions; however, real-world implementation frequently falls short of achieving anticipated large-scale impacts. This evidence-to-practice gap often arises from challenges in capturing the complexity inherent in intervention implementation. This complexity may stem from the intervention itself, the dynamic and interrelated processes of dissemination, implementation, and sustainment, or the constraints of real-world settings characterized by interconnected systems. Integrating implementation science, which employs theories, models, and frameworks to understand the adoption and integration of evidence-based interventions, with systems science, which provides tools to model and analyze complex systems, offers a promising pathway for addressing these challenges. However, practical guidance on combining these approaches to evaluate dynamic interactions between interventions and implementation contexts, while simultaneously capturing system-level learnings, remains limited. In this methodological musing, we reflect on our experience integrating systems and implementation science to develop a conceptual and quantitative model for scenario evaluation of a maternal health service delivery redesign initiative in Kakamega, Kenya. We use four research objectives as a touchstone for organizing our reflections, explicated by three steps of an evaluation process: (i) developing a qualitative systems model using implementation frameworks and causal loop diagrams; (ii) constructing and parameterizing a quantitative computational model; and (iii) conducting scenario analyses to explore "what-if" strategies and inform adaptive planning. These reflections highlight the potential strengths of an integrated approach and offer practical considerations for researchers and practitioners evaluating complex health interventions through quantitative modeling and scenario development.

Digital health information systems have the potential to improve data-driven decision-making and strengthen primary health care delivery in low- and middle-income countries (LMICs). This study examines Rajasthan, India's public health information systems with an aim to describe data processes and identify key barriers and opportunities for improvement. Using a qualitative approach, we conducted in-depth interviews with 39 stakeholders, including frontline health workers and state health officials. Our findings highlight inefficiencies in parallel paper and digital reporting systems, leading to high health worker burden, redundant data entry, delays in patient care, and poor data accountability. While digital platforms have improved data accessibility and care coordination, challenges such as poor interoperability, IT infrastructure limitations, and gaps in digital literacy remain. Lessons from successful digital health implementations in other LMICs suggest that integrated, human-centered, and interoperable systems are critical for sustainable digital transformation. We propose a "5I Framework" for policymakers to streamline Rajasthan's digital health ecosystem: (1) Integrated platforms, (2) Implementable systems co-designed with health workers, (3) Ink-free transitions away from paper-based systems, (4) Insights from geospatial and real-time data, and (5) Incentives aligned with workforce needs. Strengthening Rajasthan's digital health systems through these strategies can enhance service delivery, improve public health outcomes, and serve as a model for other LMICs.

Research on health system capacity to manage non-communicable diseases (NCDs) has largely focused on 'system hardware' such as infrastructure, workforce, and commodities. However, this overlooks the critical role of 'system software' elements such as relationships, norms, and power, and the complex adaptive nature of health systems. This study aimed to explore how health system hardware and software elements interact to shape the capacity of the health system to deliver hypertension care in Kilifi County in the coastal region of Kenya. We conducted a cross-sectional qualitative study and collected data using document reviews (n=14) and in-depth interviews with purposively selected front-line health workers (FLHWs) at five health facilities and health managers at county and national levels (n=37). We applied a framework approach to data analysis, utilizing complex adaptive systems (CAS) theory as our analytic framework. Complex interactions of system hardware and software elements constrained the provision of hypertension care. Frequent medicines stockouts (hardware) stemmed from budgetary gaps, procurement delays, regulatory restrictions, and weak quantification practices (software). To mitigate medicines shortages, facilities employed adaptive responses such as inter-facility borrowing and sourcing from alternative suppliers (software). Access and continuity of care were enabled by organizational norms like dedicated hypertension clinic days (software) but undermined by inadequate consultation rooms, staff shortages (hardware) and limited training and support supervision (software). FLHWs' ideas to improve medication adherence were undermined by staff shortages (hardware) and inadequate support from facility managers (software), weakening service delivery. The application of CAS theory unpacked the hitherto underexplored aspects of health system capacity. System 'software' plays a central role in shaping health system capacity for hypertension care. Therefore, strengthening health system capacity for NCDs requires coordinated investment in both system hardware and software elements. Importantly, system strengthening interventions should consider the CAS nature of health systems to foster conditions for productive emergence.

Sub-Saharan Africa (SSA) is experiencing an epidemiological transition where non-communicable diseases are becoming the leading cause of disability and mortality alongside infectious diseases such as HIV/AIDs. Multimorbidity, the coexistence of two or more long-term conditions, is increasing in SSA. However, the cost of managing multimorbidity is largely unknown. This study aimed to estimate the economic cost of public outpatient primary care for adults with multimorbidity (HIV, hypertension, and/or diabetes, and their associated conditions, cardiovascular disease and TB) in rural South Africa. This study used a cross-sectional, retrospective cost-of-illness approach to estimate the direct and indirect costs of multimorbidity management in Bushbuckridge, Mpumalanga, in 2022. Data was synthesized from patient-level data from eight public primary healthcare facilities within the Agincourt study site - a rapidly transitioning rural South African setting. Additionally, government reports and an existing study on transport costs and productivity losses conducted within the Agincourt study site were used to estimate the costs of managing patients in the primary care facilities. Results showed that patients with multimorbidity had higher average economic costs per patient compared to those with single conditions. Overall, patients with multimorbidity increase costs above the baseline of a patient with a single condition (R4 900/annum) by between 42% - 83%. Patients with multimorbidity also incur slightly higher costs associated with accessing primary care services compared to those with a single condition. However, our model shows that the additive cost of managing multiple conditions in separate consultations is higher than managing all conditions in a one visit. This shows that managing patients within an integrated care model seems to have a cost-limiting effect. However, treatment guidelines for managing multimorbidity in South Africa should be developed to ensure standardised care.

As countries progress through the 'nutrition transition' and experience rising rates of obesity and non-communicable disease, concern has broadened from a primary focus on economic consequences of child stunting, to incorporate multiple forms of malnutrition, including overweight and obesity, or a more ambitious set of individual dietary risk factors from the Global Burden of Disease work. This paper conceptualizes a methodology which uses unhealthy diets to better understand the economic impact as the nutrition transition progresses. The Lives Saved Tool (LiST) is used to estimate how much healthier diets alone (without other health interventions) can reduce future child stunting. The Global Burden of Disease Results Tool is used to estimate how much healthier diets can reduce future non-communicable disease among adults, via effects on three metabolic markers (high body mass index -BMI, high systolic blood pressure, and high fasting blood glucose). We then link the metabolic markers to diet quality (measured by the Global Diet Quality Score). Calculations are made for the Philippines for 2014 and 2021 and Ethiopia for 2011 and 2019. Recent studies have estimated the present value of future child stunting costs as 2.0% of GDP for the Philippines and 5.25% for Ethiopia, in both cases in 2023, of which we estimate up to 45% and 50% respectively are avertible over the long run by healthier diets, while public nutrition and public health programs account for the rest. The present value of costs associated with the three metabolic markers among adults are estimated as 7.99% of GDP (Philippines 2021) and 2.15% (Ethiopia 2019), of which we estimate 20% is avertible by healthier diets. The total losses avertible by healthier diets are therefore estimated as 2.5% of GDP (Philippines 2021) and 3.1% (Ethiopia 2019), with metabolic factors predominating in the Philippines and stunting in Ethiopia.

This study develops an inverse rank-weighted index (IRWI) to adjust catastrophic thresholds for out-of-pocket expenditure (OOPE) components. The proposed method eliminates the arbitrariness of the existing proportionate approach by ensuring fairness in determining component-specific catastrophic thresholds. It measures the effective expenditure share of each OOPE component while considering the concentration of component-specific spending across household income levels. Using nationally representative household survey data on healthcare consumption from 2017-18, the study estimates catastrophic health expenditure (CHE) at both aggregate and component levels in India under uniform, proportionate, and IRWI thresholds. The findings reveal that the uniform threshold significantly underestimates CHE incidence, whereas component-specific thresholds identify twice as many households that experience CHE. Shifting from the proportionate method thresholds to IRWI thresholds significantly alters CHE estimates. The IRWI approach offers a more reliable framework for integrating component-specific and aggregate CHE assessments. It underscores the need for income-sensitive, component-specific thresholds to accurately quantify financial hardship and prevent underestimating healthcare-related economic burden.

Recent reductions in U.S. global health funding have disrupted essential programs in sub-Saharan Africa (SSA), highlighting the region's vulnerability to external financing shocks. The suspension of USAID initiatives has affected disease control, maternal care, and health system operations across 47 countries, raising urgent questions about how to sustain progress without reliable donor support. This commentary examines the potential of Public-Private Partnerships (PPPs)-structured collaborations in which governments and private actors share financing, risk, and managerial responsibility-to strengthen domestic capacity. Drawing on examples from Senegal, Nigeria, and Kenya, we explore how service, concession, financing, and technology-focused PPPs can mobilize additional resources, expand access, and improve service delivery. We also address key challenges, including governance risks, fiscal constraints, and shifting global power dynamics. While not a substitute for aid, well-designed PPPs aligned with national priorities can support more resilient, equitable, and self-reliant health systems in SSA.

There has been increasing interest in co-designing interventions with end users to prevent violence against women (VAW). Co-design is theorised as an ethical approach to research able to engage some of the most marginalised groups in VAW prevention. However, there is little evidence of whether co-designing interventions can reduce violence against women, or theoretical consideration of how it might do so. This paper contributes to current discussions about co-design by examining the results of the E le Saua le Alofa ("Love Shouldn't Hurt")-a pilot intervention that engaged Samoan communities in co-designing violence prevention activities. A mixed methods evaluation of the pilot has shown promising results, and in this paper we consider how the co-design process may have contributed to these results. The evaluation of the co-design process assessed four theorised mechanisms: (1) increased ownership of the problem of violence; (2) improved health behaviours and social norms; (3) relevance of actions taken to address VAW; (4) addressing power structures arising from coloniality. Our results show that change in violence outcomes occurred through the pilot's ability to revisit previous conversations about violence in Samoa, prompting new activities by local leaders, and tightening village rules on violence. Yet, the activities implemented by local leaders were largely unpredictability and sometimes conflicted with global evidence. We argue that such actions should not be construed by policymakers as the 'unpredictable outcomes' of an intervention, but rather understood within a broader framework of diversified knowledge systems. The need for balance in co-designing VAW interventions with communities affected by violence highlights a key challenge of decolonising VAW practice within a co-production framework.

Unmet healthcare needs are a significant concern in China, possibly due to the underutilization of primary healthcare services. Patients disproportionately seek tertiary hospital services, reflecting the historical underinvestment in community healthcare and a weak referral system. This misallocation of medical resources burdens the capacity of tertiary hospitals and limits access to necessary healthcare. To address this, the Family Doctor Contracting System (FDCS) was introduced to enhance community health services and reduce unmet healthcare needs. This study empirically analyzes the impact of the FDCS on unmet healthcare needs using data from the 2018 National Health Service Survey in Shandong Province, which included 27 447 individuals aged ≥18 years. An entropy balancing method was employed to address self-selection bias. Logistic regression results show that individuals contracted with family doctors (FDs) are associated with a 1.6% lower probability of experiencing unmet outpatient healthcare needs compared to those who did not participate, although the FDCS had no significant impact on unmet inpatient needs. A potential mechanism is that the FDCS has improved the accessibility of outpatient services. We found that signing up with FDs reduced the likelihood of citing inaccessibility as the main reason for unmet outpatient care needs by 43.7 percentage points, while the impact on unacceptability and unavailability was relatively more minor at 0.5 percentage points. The findings highlight the effectiveness of the FDCS in enhancing the role of primary care and improving access to healthcare. Future policy initiatives should focus on promoting the benefits of the FDCS and encouraging utilization of the FD service while strengthening community-based primary care by providing adequate infrastructure, resources, and training.

Limited research has been conducted on strategies to improve the efficiency of HIV services for key populations (KPs). This study investigates ways to enhance healthcare delivery efficiency, focusing on HIV services for KPs. We explore two strategies: expanding service volume and offering multiple HIV services within a single health facility. Using data from the Linkages Across the Continuum of HIV Services for Key Populations Affected by HIV (LINKAGES) program in Kenya and Malawi, we exploit the variation in services provided to assess correlations between different service delivery configurations and their costs. We apply log-log fixed-effects regression models to analyze relationships between the total costs of four HIV services and the volume and range of services delivered. We find that service volume increases correlate with higher total costs, albeit less than proportionally, consistent with possible economies of scale. Negative correlations between service integration and total costs suggest that integrating HIV services for KPs could lead to reduced total costs for some service combinations. These results indicate potential strategies to increase the efficiency of HIV services for KPs, which can inform strategic planning and program execution in Kenya, Malawi, and similar countries.