Health workers aim to save lives of mothers and babies with smartphone data

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[September 25, 2019]  By Kate Kelland

LONDON (Reuters) - Community health workers in India and Uganda are to be armed with smartphones and tablets that use data analytics, risk maps and social media trends help to save the lives of mothers and their babies.

The $100 million project, backed by the World Health Organization, UNICEF, the World Bank and others, will be extended to 10 countries in all and aims to prevent the premature deaths of 6 million women and children by 2030.

The plan is to give frontline health workers inexpensive data analytic tools to help them gather the intelligence they need to focus on communities and families most at risk, said Raj Shah, president of the philanthropic Rockefeller Foundation that is co-leading the project.
 


This will include creating real-time risk maps to help health workers be more effective at reaching mothers and children in need, and analyzing non-health data such as climate patterns or social media trends to predict and prepare in advance for local disease outbreaks or health emergencies.

"A few years ago, these community health workers had no real technology - they were usually flying blind," Shah told Reuters.

"Today the vast majority of them have smartphones with data and software technologies literally in their hands - and with those, we can help them do their work better."

U.N. figures published last week showed that while more women and newborns survive now than ever before, a baby or a pregnant woman still dies every 11 seconds somewhere in the world.

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Levels of maternal deaths are nearly 50 times higher for women in sub-Saharan Africa than in wealthy countries, and their babies are 10 times more likely to die in their first month of life, the report found.

UNICEF's executive director Henrietta Fore said that by adopting a precision approach - using granular knowledge of which people and families are most at risk due to poverty, medical history, or gaps in vaccinations for example - should help health teams "make life-saving decisions and prevent epidemics before they happen".

“Timely, reliable and disaggregated data, underpinned by a commitment to universal health coverage, can ensure that vulnerable women, children and young people get the care they need at the right place and the right time," she said.

(Reporting by Kate Kelland; Editing by Alison Williams)

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