Newborn Survival Case Study in Rwanda - Bottleneck Analysis and Projections in Key Maternal and Child Mortality Rates Using Lives Saved Tool (LiST)

Background and Objective: The Newborn Survival Case study in Rwanda provides an analysis of the newborn health and survival situation in the country. It reviews evidence-based interventions and coverage levels already implemented in the country; identifies key issues and bottlenecks in service delivery and uptake of services by community/beneficiaries, and provides key recommendations aimed at faster reduction in newborn mortality rate. Methods: This study utilized mixed method research including qualitative and quantitative analyses of various maternal and newborn health programs implemented in the country. This included interviewing key stakeholders at each level, field visits and also interviewing beneficiaries for assessment of uptake of services. Monitoring systems such as Health Management Information Systems (HMIS), maternal and newborn death audits were reviewed and data analyzed to aid these analyses. Results: Policies, protocols, various guidelines and tools for monitoring are already in place however, implementation of these remains a challenge e.g. infection control practices to reduce deaths due to sepsis. Although existing staff are quite knowledgeable and are highly motivated, however, shortage of health personnel especially doctors in an issue. New facilities are being operationalized e.g. at Gisenyi, however, the existing facilities needs expansion. Conclusion and Global Health Implications: It is essential to implement high impact evidence based interventions but coverage levels need to be significantly high in order to achieve higher reduction in newborn mortality rate. Equity approach should be considered in planning so that the services are better implemented and the poor and needy can get the benefits of public health programs. Key words: Bottleneck Analysis • Lives Saved Tool • Rwanda • Maternal and Newborn Health • Neonatal Mortality Copyright © 2017 Khurmi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.