Cost-effectiveness of a direct to beneficiary mobile communication programme in improving reproductive and child health outcomes in India.

INTRODUCTION: Kilkari is the largest maternal messaging programme of its kind globally. Between its initiation in 2012 in Bihar and its transition to the government in 2019, Kilkari was scaled to 13 states across India and reached over 10 million new and expectant mothers and their families. This study aims to determine the cost-effectiveness of exposure to Kilkari as compared with no exposure across 13 states in India. METHODS: The study was conducted from a programme perspective using an analytic time horizon aligned with national scale-up efforts from December 2014 to April 2019. Economic costs were derived from the financial records of implementing partners. Data on incremental changes in the practice of reproductive maternal newborn and child health (RMNCH) outcomes were drawn from an individually randomised controlled trial in Madhya Pradesh and inputted into the Lives Saved Tool to yield estimates of maternal and child lives saved. One-way and probabilistic sensitivity analyses were carried out to assess uncertainty. RESULTS: Inflation adjusted programme costs were US$8.4 million for the period of December 2014-April 2019, corresponding to an average cost of US$264 298 per year of implementation in each state. An estimated 13 842 lives were saved across 13 states, 96% among children and 4% among mothers. The cost per life saved ranged by year of implementation and with the addition of new states from US$392 ($385-$393) to US$953 ($889-$1092). Key drivers included call costs and incremental changes in coverage for key RMNCH practices. CONCLUSION: Kilkari is highly cost-effective using a threshold of India's national gross domestic product of US$1998. Study findings provide important evidence on the cost-effectiveness of a national maternal messaging programme in India. TRIAL REGISTRATION: NCT03576157.

Can health information through mobile phones close the divide in health behaviours among the marginalised? An equity analysis of Kilkari in Madhya Pradesh, India.

Kilkari is one of the largest maternal mobile messaging programmes in the world. It makes weekly prerecorded calls to new and expectant mothers and their families from the fourth month of pregnancy until 1-year post partum. The programme delivers reproductive, maternal, neonatal and child health information directly to subscribers' phones. However, little is known about the reach of Kilkari among different subgroups in the population, or the differentiated benefits of the programme among these subgroups. In this analysis, we assess differentials in eligibility, enrolment, reach, exposure and impact across well-known proxies of socioeconomic position-that is, education, caste and wealth. Data are drawn from a randomised controlled trial (RCT) in Madhya Pradesh, India, including call data records from Kilkari subscribers in the RCT intervention arm, and the National Family Health Survey-4, 2015. The analysis identifies that disparities in household phone ownership and women's access to phones create inequities in the population eligible to receive Kilkari, and that among enrolled Kilkari subscribers, marginalised caste groups and those without education are under-represented. An analysis of who is left behind by such interventions and how to reach those groups through alternative communication channels and platforms should be undertaken at the intervention design phase to set reasonable expectations of impact. Results suggest that exposure to Kilkari has improved levels of some health behaviours across marginalised groups but has not completely closed pre-existing gaps in indicators such as wealth and education.

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

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.