Impact of the Salud Mesoamerica Initiative on delivery care choices in Guatemala, Honduras, and Nicaragua.

BACKGROUND: The Salud Mesoamérica Initiative (SMI) is a public-private collaboration aimed to improve maternal and child health conditions in the poorest populations of Mesoamerica through a results-based aid mechanism. We assess the impact of SMI on the staffing and availability of equipment and supplies for delivery care, the proportion of institutional deliveries, and the proportion of women who choose a facility other than the one closest to their locality of residence for delivery. METHODS: We used a quasi-experimental design, including baseline and follow-up measurements between 2013 and 2018 in intervention and comparison areas of Guatemala, Nicaragua, and Honduras. We collected information on 8754 births linked to the health facility closest to the mother's locality of residence and the facility where the delivery took place (if attended in a health facility). We fit difference-in-difference models, adjusting for women's characteristics (age, parity, education), household characteristics, exposure to health promotion interventions, health facility level, and country. RESULTS: Equipment, inputs, and staffing of facilities improved after the Initiative in both intervention and comparison areas. After adjustment for covariates, institutional delivery increased between baseline and follow-up by 3.1 percentage points (ß = 0.031, 95% CI -0.03, 0.09) more in intervention areas than in comparison areas. The proportion of women in intervention areas who chose a facility other than their closest one to attend the delivery decreased between baseline and follow-up by 13 percentage points (ß = - 0.130, 95% CI -0.23, - 0.03) more than in the comparison group. CONCLUSIONS: Results indicate that women in intervention areas of SMI are more likely to go to their closest facility to attend delivery after the Initiative has improved facilities' capacity, suggesting that results-based aid initiatives targeting poor populations, like SMI, can increase the use of facilities closest to the place of residence for delivery care services. This should be considered in the design of interventions after the COVID-19 pandemic may have changed health and social conditions.

Bringing a health systems modelling approach to complex evaluations: multicountry applications in HIV, TB and malaria.

INTRODUCTION: Understanding how to deliver interventions more effectively is a growing emphasis in Global Health. Simultaneously, health system strengthening is a key component to improving delivery. As a result, it is challenging to evaluate programme implementation while reflecting real-world complexity. We present our experience in using a health systems modelling approach as part of a mixed-methods evaluation and describe applications of these models. METHODS: We developed a framework for how health systems translate financial inputs into health outcomes, with in-country and international experts. We collated available data to measure framework indicators and developed models for malaria in Democratic Republic of the Congo (DRC), and tuberculosis in Guatemala and Senegal using Bayesian structural equation modelling. We conducted several postmodelling analyses: measuring efficiency, assessing bottlenecks, understanding mediation, analysing the cascade of care and measuring subnational effectiveness. RESULTS: The DRC model indicated a strong relationship between shipment of commodities and utilisation thereof. In Guatemala, the strongest model coefficients were more evenly distributed. Results in Senegal varied most, but pathways related to community care had the strongest relationships. In DRC, we used model results to estimate the end-to-end cost of delivering commodities. In Guatemala, we used model results to identify potential bottlenecks and understand mediation. In Senegal, we used model results to identify potential weak links in the cascade of care, and explore subnationally. CONCLUSION: This study demonstrates a complementary modelling approach to traditional evaluation methods. Although these models have limitations, they can be applied in a variety of ways to gain greater insight into implementation and functioning of health service delivery.