Big Data Can Improve Health of Mothers and Children

Across every industry, data is revolutionizing numerous aspects of people's lives. It is changing the present and prospects for the greater good. But people are missing huge opportunities to employ new data-driven innovations to improve the health of the poorest and most vulnerable – in particular mothers and young children.

One of the greatest needs for big data in current times is assisting community health workers to prevent maternal and newborn deaths. However, the rate of women dying from pregnancy and childbirth has declined significantly over the past decade but over 800 women still lose their lives while giving life. Additionally, around 2.5 million children died before they were one-month-old, last year.

There exist a number of simple and not-so-expensive tools that can save the majority of maternal and newborn deaths, but they fail to reach the right person at the right time quite often. This is where big data comes into picture which can bring significant change. It proves to be transformative in reaching out to poorer and remote areas, by providing critical intelligence to help community health workers prioritize and triage care and resources to those most at risk.

Women's and children's health is a global priority and elevated risks and harm in such areas are an important concern to look after for. Death of young women in sub-Saharan Africa is exceptionally high and the consequences of the orphanhood are already at its peak because of HIV. With the help of technology, it is needed to identify effective approaches to prevent and mitigate such effects.

Moreover, in the region of sub-Saharan Africa, there are more people with access to mobile phones than those with electricity. This offers an opportunity to enhance health workers' ability to reach the most vulnerable population.

The potential of big data to improve the health of mothers and children makes healthcare providers responsible for keeping track of the health of scores of families and making rapid decisions about who to visit and when. They need to focus on putting a stop to problems before they occur.

If 10 pregnant females are on the list to visit on a particular day but the service provider can reach 5 only, then the big data facilities on their phone can help them prioritize with women that have the highest-risk pregnancies and require urgent attention. The technology can also predict which newborns are most likely to struggle to survive at the time of birth so that they can take precise action on time.

Moreover, overlaying health data with data depending on the factors – weather, disaster and calamities, the entire team of health workers can be quickly moved to a community where a terrible storm is predicted to flood the roads, blocking the area's lone ambulance from reaching a health center in the nearest city.