Final Report: Results-Based Financing to Scale Community Health Programs in Uganda

The project was launched in 2019 and implemented over 2.5 years, despite the challenges posed by the COVID-19 pandemic and an Ebola outbreak. The project utilized a model of contracting for high-impact, cost-effective community health services that can be used by donors and governments. Payments to the implementing partner, Living Goods (LG), were based on the performance of community health workers (CHWs) aimed at achieving high impact and continuous innovation as community health services were scaled. The RBF model is attractive because it allows donors and governments to contract with third-party implementers to provide community health services with payments based on the results achieved, offering the highest value for money proposition and delivery of cost-effective results at scale. LG's proven model to improve community health outcomes is rooted in the four DESC (Digitally Enabled, Equipped, Supervised, and Compensated) principles that enable CHWs to optimally care for their communities. LG trains and provides CHWs with digital tools which serve as a job aid to improve the provision of quality care while also collecting valuable data on service provision. CHWs use LG's platform to deliver a range of services, including integrated community case management (iCCM) for malaria, pneumonia, and diarrhea for children under-five (U5); maternal health services; family planning for women of reproductive age; and immunization services. The project supported 1,165 CHWs reaching 116,500 households with more than 582,000 individuals, based on verified results with design conditions applied. Over the 2.5 years of implementation, CHWs treated or referred nearly 500,000 cases of sick children, supported 11,800 births to take place in health facilities, and conducted 230,000 household visits to provide family planning information and methods to couples in their communities. This project proved successful in presenting a cost-effective mechanism for donors, ensuring they only paid for verified, quality community health services. However, learnings throughout implementation revealed an array of modifications that could be made to optimize the design and implementation of the RBF model, as well as opportunities to better adjust the approach to the community health context and to be more cost-effective for implementing partners. Ultimately, LG believes delivering high-quality community health sustainably and at scale can be best achieved by supporting governments to finance and manage their own digital community health programs. In line with this vision, the RBF model holds the potential to enable resource-strapped governments to compensate CHWs in a cost-effective way. As with the RBF project, LG leverages learnings from its direct implementation sites to develop proof of best practices and subsequently advocate for government adoption. The project's success has piqued the interest of national governments, and LG is now working closely with both the governments of Kenya and Uganda to promote a simplified, contextualized RBF model direct to CHWs. This model focuses on providing performance-based compensation directly to CHWs, with the single performance metric focused on whether a CHW is actively providing care in their community. This model was a success and has been adopted by local governments in Kenya and Uganda. The need for community health services is critical, with approximately 6 million children dying each year for want of simple, inexpensive healthcare. Community health services have tremendous potential to reduce infant, child, and maternal mortality, but most CHW systems are not achieving the scale and quality needed to improve health outcomes due to lack of sufficient, accessible, and sustainable financing. The RBF model holds the potential to address these challenges by providing a cost-effective mechanism for donors and governments to finance and manage community health programs.