Living independently as an older person carries risks. One in four Americans aged 65 and older falls each year, according to the National Council on Aging, and every 19 minutes an older adult dies from a fall. Health ailments like urinary tract infections (UTI) become increasingly common in old age, too, accounting for about 8.1 million physician visits each year. And it’s not just physical problems caregivers and older patients have to worry about — mental illnesses like depression affect an estimated 7 million older adults annually.
That’s why 30-year tech veteran and former IBM consultant Satish Movva founded CarePredict, a Fort Lauderdale, Florida-based health tech startup that aims to improve seniors’ quality of life with machine learning-driven wearables. CarePredict claims its platform can surface actionable insights that predict a UTI up to 3.7 days ahead of clinical diagnosis and depression two weeks ahead of diagnosis. The startup also claims it has managed to reduce falls by 25 percent in senior communities.
Those stats have investors impressed, it seems. CarePredict today announced that it has secured $9.5 million in Series A financing led by Secocha Ventures, Las Olas Ventures, and Startup Health Ventures. This brings its total raised to $19.7 million, following a $4 million seed fund round in December 2017 and a grant from the National Science Foundation.