Adapting Economic Evaluation Methods to Shifting Global Health Priorities: Assessing the Value of Health System Inputs.

OBJECTIVES: We highlight the importance of undertaking value assessments for health system inputs if allocative efficiency is to be achieve with health sector resources, with a focus on low- and middle-income countries. However, methodological challenges complicated the application of current economic evaluation techniques to health system input investments. METHODS: We undertake a review of the literature to examine how assessments of investments in health system inputs have been considered to date, highlighting several studies that have suggested ways to address the methodological issues. Additionally, we surveyed how empirical economic evaluations of health system inputs have approached these issues. Finally, we highlight the steps required to move toward a comprehensive standardized framework for undertaking economic evaluations to make value assessments for investments in health systems. RESULTS: Although the methodological challenges have been illustrated, a comprehensive framework for value assessments of health system inputs, guiding the evidence required, does not exist. The applied literature of economic evaluations of health system inputs has largely ignored the issues, likely resulting in inaccurate assessments of cost-effectiveness. CONCLUSIONS: A majority of health sector budgets are spent on health system inputs, facilitating the provision of healthcare interventions. Although economic evaluation methods are a key component in priority setting for healthcare interventions, such methods are less commonly applied to decision making for investments in health system inputs. Given the growing agenda for investments in health systems, a framework will be increasingly required to guide governments and development partners in prioritizing investments in scarce health sector budgets.

The effect of distance on maternal institutional delivery choice: Evidence from Malawi.

In many low- and middle-income countries, geographical accessibility continues to be a barrier to health care utilization. In this paper, we aim to better understand the full relationship between distance to providers and utilization of maternal delivery services. We address three methodological challenges: non-linear effects between distance and utilization; unobserved heterogeneity through non-random distance "assignment"; and heterogeneous effects of distance. Linking Malawi Demographic Health Survey household data to Service Provision Assessment facility data, we consider distance as a continuous treatment variable, estimating a Dose-Response Function based on generalized propensity scores, allowing exploration of non-linearities in the effect of an increment in distance at different distance exposures. Using an instrumental variables approach, we examine the potential for unobserved differences between women residing at different distances to health facilities. Our results suggest distance significantly reduces the probability of having a facility delivery, with evidence of non-linearities in the effect. The negative relationship is shown to be particularly strong for women with poor health knowledge and lower socio-economic status, with important implications for equity. We also find evidence of potential unobserved confounding, suggesting that methods that ignore such confounding may underestimate the effect of distance on the utilization of health services.

Allocating resources to support universal health coverage: development of a geographical funding formula in Malawi.

BACKGROUND: Universal health coverage (UHC) requires that local health sector institutions-such as local authorities-are properly funded to fulfil their service delivery commitments. In this study, we examine how formula funding can align sub-national resource allocations with national priorities. This is illustrated by outlining alternative options for using mathematical formula to guide the allocation of national drug and service delivery budgets to district councils in Malawi in 2018/2019. METHODS: We use demographic, epidemiological and health sector budget data with information on implementation constraints to construct three variant allocation formulae. The first gives an equal per capita allocation to each district, and is included as a baseline to compare alternatives. The second allocates funds to districts using estimates of the resources required to provide Malawi's essential health package of priority cost-effective interventions to the full population in need of each intervention. The third adjusts these estimates to reflect a practicable level of attainable coverage for each intervention, based on the current configurations of health services and demand for interventions. FINDINGS: Compared with current district allocations, not underpinned by an explicit formula, the formulae presented in this study suggest sizeable shifts in the allocations received by many districts. In some cases, the magnitude of these shifts exceed 50% reductions or doubling of district budgets. The large shifts illustrate inequities in the current system of budget allocation and the potential improvements possible. CONCLUSION: The use of mathematical formulae can guide the efficient and equitable allocation of healthcare funds to local health authorities. The formulae developed were facilitated by the existence of an explicit package of priority interventions. The approach can be replicated in wide range of countries seeking to achieve UHC.

Financing intersectoral action for health: a systematic review of co-financing models.

BACKGROUND: Addressing the social and other non-biological determinants of health largely depends on policies and programmes implemented outside the health sector. While there is growing evidence on the effectiveness of interventions that tackle these upstream determinants, the health sector does not typically prioritise them. From a health perspective, they may not be cost-effective because their non-health outcomes tend to be ignored. Non-health sectors may, in turn, undervalue interventions with important co-benefits for population health, given their focus on their own sectoral objectives. The societal value of win-win interventions with impacts on multiple development goals may, therefore, be under-valued and under-resourced, as a result of siloed resource allocation mechanisms. Pooling budgets across sectors could ensure the total multi-sectoral value of these interventions is captured, and sectors' shared goals are achieved more efficiently. Under such a co-financing approach, the cost of interventions with multi-sectoral outcomes would be shared by benefiting sectors, stimulating mutually beneficial cross-sectoral investments. Leveraging funding in other sectors could off-set flat-lining global development assistance for health and optimise public spending. Although there have been experiments with such cross-sectoral co-financing in several settings, there has been limited analysis to examine these models, their performance and their institutional feasibility. AIM: This study aimed to identify and characterise cross-sectoral co-financing models, their operational modalities, effectiveness, and institutional enablers and barriers. METHODS: We conducted a systematic review of peer-reviewed and grey literature, following PRISMA guidelines. Studies were included if data was provided on interventions funded across two or more sectors, or multiple budgets. Extracted data were categorised and qualitatively coded. RESULTS: Of 2751 publications screened, 81 cases of co-financing were identified. Most were from high-income countries (93%), but six innovative models were found in Uganda, Brazil, El Salvador, Mozambique, Zambia, and Kenya that also included non-public and international payers. The highest number of cases involved the health (93%), social care (64%) and education (22%) sectors. Co-financing models were most often implemented with the intention of integrating services across sectors for defined target populations, although models were also found aimed at health promotion activities outside the health sector and cross-sectoral financial rewards. Interventions were either implemented and governed by a single sector or delivered in an integrated manner with cross-sectoral accountability. Resource constraints and political relevance emerged as key enablers of co-financing, while lack of clarity around the roles of different sectoral players and the objectives of the pooling were found to be barriers to success. Although rigorous impact or economic evaluations were scarce, positive process measures were frequently reported with some evidence suggesting co-financing contributed to improved outcomes. CONCLUSION: Co-financing remains in an exploratory phase, with diverse models having been implemented across sectors and settings. By incentivising intersectoral action on structural inequities and barriers to health interventions, such a novel financing mechanism could contribute to more effective engagement of non-health sectors; to efficiency gains in the financing of universal health coverage; and to simultaneously achieving health and other well-being related sustainable development goals.

Supporting the development of a health benefits package in Malawi.

Malawi, like many low-income and middle-income countries, has used health benefits packages (HBPs) to allocate scarce resources to key healthcare interventions. With no widely accepted method for their development, HBPs often promise more than can be delivered, given available resources. An analytical framework is developed to guide the design of HBPs that can identify the potential value of including and implementing different interventions. It provides a basis for informing meaningful discussions between governments, donors and other stakeholders around the trade-offs implicit in package design. Metrics of value, founded on an understanding of the health opportunity costs of the choices faced, are used to quantify the scale of the potential net health impact (net disability adjusted life years averted) or the amount of additional healthcare resources that would be required to deliver similar net health impacts with existing interventions (the financial value to the healthcare system). The framework can be applied to answer key questions around, for example: the appropriate scale of the HBP; which interventions represent 'best buys' and should be prioritised; where investments in scaling up interventions and health system strengthening should be made; whether the package should be expanded; costs of the conditionalities of donor funding and how objectives beyond improving population health can be considered. This is illustrated using data from Malawi. The framework was successfully applied to inform the HBP in Malawi, as a core component of the country's Health Sector Strategic Plan II 2017-2022.