From 2011 through 2015, HealthBridge ran a project in Pakur, India with local partners, with the goal of improving maternal and child survival. Through improving maternal health services demand and delivery a number of important changes were made, summarized in this graph from the final report.

There are many important changes there, including increase in % of live births in a health institution attended by a skilled birth attendant (from 30 to 71%) and % of pregnant women who consumed iron supplements 100 times (from 3% to 31%). Unfortunately there were also some negative results – due to stock outs there was a decrease in children receiving vitamin A capsules (from 59 to 14%) and DPT vaccines (from 41 to 34%).

These were important changes, but they are actually only intermediate outcomes and they don’t tell us if we achieved what we were really trying to do – increase mother and child survival.

However there is a tool that allows us to estimate the survival rate: LiST – The Lives Saved Tool, sofware developed by Johns Hopkins University staff. From their website:

The Lives Saved Tool (LiST) is a Microsoft Windows-based software tool used to model the impact of scaling-up health interventions aimed to reduce mortality and morbidity in mothers, newborns, and children under five years of age.

LiST allows users to set up and run multiple scenarios, called projections, in order to estimate the impact of different health intervention packages based upon coverage at the national or subnational (e.g. region, state, or district) level. These projections provide a structured format for program managers or ministry of health personnel to:

• utilize the latest scientific information about the effectiveness of interventions for maternal, neonatal, and child health,
• combine information about causes of death and current coverage of interventions to inform planning and decision-making,
• help prioritize investments and evaluate existing programs.

LiST can be used prospectively, to help plan interventions to maximize health impacts, or retrospectively, to estimate the impact of completed interventions.

Using LiST and the data from the above figure, we were able to estimate the number of deaths prevented in Pakur in neonates, children under five, and mothers. By the time the program was fully implemented, we estimate that each year 159 neonatal deaths and 7 maternal deaths were averted. For the post-neonatal period, the impact of decreased vitamin A and DPT coverage counter-balanced other program impacts so there was no net change in children from 1 month to 5 years of age.

Pakur is just a small part of India with less than 1/10th of one percent of the nation’s people - the population of Pakur is about 900,000, out of 1.2 Billion in all of India. If the program in Pakur was scaled up to reach all of India, each year there would be 770,000 neonatal deaths and 32,000 maternal deaths averted. So, what are we waiting for?