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New York, NY, May 24, 2022 —  Today, the ̽����ѡ and the Human Centered Automation company, announced a new partnership that will, for the first time, apply machine-learning to the ̽����ѡ's data collection in health clinics treating malnourished children. Currently, data at health facilities is collected by hand and then transcribed into databases. This collaboration marks a potential breakthrough in how data is captured and used in some of the most challenging humanitarian settings.

“We’re thrilled to launch this initiative with Hyperscience,” said Jeannie Annan, Chief Research and Innovation Officer at the ̽����ѡ. “Their technology and application in humanitarian contexts—where there are limited data systems—could be a game changer for data analysis and measuring outcomes. Not only does this enable us to increase the speed and accuracy of our data collection, but it helps us create more capacity to improve programs and test new solutions.”

Globally, 50 million children are acutely malnourished at any given time, with only 20% receiving treatment, due in large part to a complex and costly system that severely limits scaled access to care. The ̽����ѡ has developed and tested a simpler, more cost-effective approach to treat malnutrition, designed to scale so that significantly more children can receive a treatment that has been proven to be extremely effective. The ̽����ѡ teams are currently running several pilots demonstrating how the approach works in practice, and in each pilot the accurate, near real-time data allows the ̽����ѡ to continually refine how it can treat patients and scale its methods.

Using Hyperscience’s human-centered automation technology, handwritten data captured by ̽����ѡ teams can be photographed and instantly digitized to automate information extraction. By accelerating the speed at which critical information on patient outcomes can be recorded and analyzed, the ̽����ѡ will have the ability to improve programming, including the collection of broader patient demographics and prescriptions from doctors, previously left unrecorded due to time constraints. This creates a more complete data set of patient outcomes to help better inform necessary solutions to combat malnutrition.

“We are honored that our technology will support the ̽����ѡ with faster access to higher quality data,” said Charlie Newark-French, Interim CEO at Hyperscience. Additionally, by augmenting such a vital and burdensome part of the process, we’re also helping valuable frontline resources focus on what matters most—helping others. This is a tremendous opportunity to put in action and further improve our technology for other important applications like this in the future.”

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