Abstract

In 2010, the Bill and Melinda Gates Foundation (BMGF) partnered with the Government of Bihar (GoB), India to launch the Ananya program to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) outcomes. The program sought to address supply- and demand-side barriers to the adoption, coverage, quality, equity and health impact of select RMNCHN interventions. Approaches included strengthening frontline worker service delivery; social and behavior change communications; layering of health, nutrition and sanitation into women's self-help groups (SHGs); and quality improvement in maternal and newborn care at primary health care facilities. Ananya program interventions were piloted in approximately 28 million population in eight innovation districts from 2011-2013, and then beginning in 2014, were scaled up by the GoB across the rest of the state's population of 104 million. A Bihar Technical Support Program provided techno-managerial support to governmental Health as well as Integrated Child Development Services, and the JEEViKA Technical Support Program supported health layering and scale-up of the GoB's SHG program. The level of support at the block level during statewide scale-up in 2014 onwards was approximately one-fourth that provided in the pilot phase of Ananya in 2011-2013. This paper - the first manuscript in an 11-manuscript and 2-viewpoint collection on Learning from Ananya: Lessons for primary health care performance improvement - seeks to provide a broad description of Ananya and subsequent statewide adaptation and scale-up, and capture the background and context, key objectives, interventions, delivery approaches and evaluation methods of this expansive program. Subsequent papers in this collection focus on specific intervention delivery platforms. For the analyses in this series, Stanford University held key informant interviews and worked with the technical support and evaluation grantees of the Ananya program, as well as leadership from the India Country Office of the BMGF, to analyse and synthesise data from multiple sources. Capturing lessons from the Ananya pilot program and statewide scale-up will assist program managers and policymakers to more effectively design and implement RMNCHN programs at scale through technical assistance to governments.

Highlights

  • Title Improving primary health care delivery in Bihar, India: Learning from piloting and statewide scale-up of Ananya

  • Several studies – while citing methodological limitations around large-scale studies of PHC initiatives – have captured consistent evidence in multiple low- and middle-income countries (LMICs) that investments in PHC systems can lead to improved health outcomes including increased access to essential health services, reduced child mortality, and reduced wealth-based disparities in mortality [1,3]

  • There is a robust body of evidence correlating interventions delivered through specific service delivery channels or platforms with improved reproductive, maternal, newborn and child health and nutrition (RMNCHN) outcomes, including 1) strengthening the capabilities of frontline workers (FLWs) [4,5,6,7]; 2) skill development and staff training at public health facilities [8]; and, 3) exposure to multifaceted social and behaviour change communication (SBCC) programs, community participation efforts, and women’s self-help groups (SHGs), among other channels for individual and collective behaviour change [9,10,11,12,13,14,15,16,17]

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Summary

Introduction

Title Improving primary health care delivery in Bihar, India: Learning from piloting and statewide scale-up of Ananya. In the first two years of implementation (2011-2013), the Ananya program would focus on testing a range of innovations designed by Ananya partners for implementation across multiple public delivery platforms by GoB functionaries to increase the coverage of critical RMNCHN interventions in eight out of Bihar’s 38 districts (Figure 1), and support the government with technical assistance as they scaled up successful solutions across the state.

Results
Conclusion

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