Providers use predictive analytics for better home care
NEW YORK: Anyone who’s ever dealt with an aging parent (and seniors themselves) will probably not be surprised by the statistic that 87% of seniors would prefer to age in place, rather than relocate to an assisted living facility. However, seniors who choose to remain at home, especially after developing disabilities, are in danger of becoming housebound and unable to care for themselves or keep up their quality of life. Researchers estimate that over 2 million seniors – more than the population of those currently in nursing homes – rarely or never leave their homes, in danger of neglect, loneliness, and medical distress. But new developments in crowdsourcing technologies and predictive analytics can ensure that seniors are always monitored and connected to loved ones and medical help, says AI healthcare company Zanthion in a recent press release.
It’s difficult for anyone to leave the home he or she loves, but a number of problems and concerns can arise as seniors age in place unattended. Cooking, cleaning, and bathing become difficult. Almost 60% of seniors who are homebound and about a third of those who are semi-homebound suffer from depression, as it gets more difficult to go out and see friends. And fall detection and medical events become an enormous worry – with non-emergencies sometimes becoming a burden on medical personnel and calls about true emergencies being directed to far-away family and friends.
Seniors are often nervous about calling 911, afraid they’ll be charged an exorbitant bill for the ambulance. Either that, or they are reluctant to admit they are experiencing a true emergency. At that point, they call family or friends, who are unsure of what kind of response is really required. The worst-case scenario occurs when a fall or other medical emergency puts incapacitated (and unattended) seniors out of reach of a phone.
