New Smartphone Tech May Prevent the Deaths of Millions of Women and Children
Health workers in rural districts in India and Uganda may soon have the use of a smartphone technology that allows them to pinpoint victims based on openly sourced data. The proposed tech will use data analytics, social media trends, and risk maps to narrow down the area where potential patients may need care. By utilizing social media along with risk maps and even climate change data, the application hopes to offer insights that are useful for local health professionals to get to patients as they fall sick.
A Change For the Better
Less than a decade ago, these health workers were entirely without the aid of technology. Now, thanks to significant advances in infrastructure, many health workers, even in the most remote areas of these countries, have smartphones or tablets with access to network connections. By taking this as its starting point, the project intends to use those existing devices to transmit and correlate information from health professionals within areas, using that data to update the risk maps.
The announcement comes as good news for these developing nations. The United Nations has been on the road to lowering infant mortality rates in these countries, and recent statistics published by the organization show that the deaths of newborns have decreased throughout the world. However, the organization also mentions that a baby or mother dies every eleven seconds somewhere in the world. The UN considers this figure unacceptable and thinks that this technology will enable health workers to address the situation better and save more lives.
The project is a $100 million initiative co-chaired by the World Health Organization, UNICEF, the World Bank, and a few other organizations. The long-term plans of the project see it being offered to over ten countries by 2030 with the potential to save the lives of over six million women and children. Universal health coverage in these areas has suffered from a lack of disaggregated data that practitioners could use to streamline their service delivery better. It is hoped that this application provides that data and a means to decipher it for front-line medical professionals.
