When we hear about computer vision, it’s typically in the context of self driving cars or automated manufacturing processes. “Computer vision is the automated extraction of information from images. Information can mean anything from 3D models, camera position, to object detection” (1). Imagine a world where your car can automatically detect obstacles and turns, all while you are reading a book in the driver seat. We are not far away from this reality.
In healthcare, Computer Vision is primarily used in diagnostic applications, medical imaging, and surgery. Computer Vision algorithms have the ability to detect anomalies in images helping doctors to detect disease or execute challenging operations. Computer Vision is undoubtedly helping doctors to detect problems and ultimately save lives.
But there is an application for this groundbreaking technology that is on the horizon with even greater impact to humankind: Direct Patient Care and Resident Safety. Every year there are over 36 million patients admitted into hospitals. (2) There are over 2 million seniors living in nursing homes or assisted living facilities (3) and over 4.7 million leveraging home care services. (4) It is impossible for caretakers to always have visibility into their patients and residents at all times. When there is no visibility, bad things can happen. A recent study showed that the overall medical costs of falls in the United States is over $50 billion annually and as many as 440,000 people die every year to preventable errors that occur in the healthcare industry. With smart automated monitoring systems in place, there is an opportunity to save lives and significantly reduce the strain on our healthcare system.
“When patients and residents are behind closed doors, we as clinicians are in the dark. When we don’t have visibility into our patients or residents, we can’t prevent adverse events from happening” – Mike Wang RN – CEO of Inspiren
Computer Vision through Edge Computing provides safe, private, and de-identified visibility into the care environment while leveraging algorithms to proactively notify clinicians of potentially dangerous events. Just like the algorithms that stop a self-driving car in traffic, algorithms can detect when patients or residents are in danger and notify staff to take action. It also opens the door to better understand how care is delivered. Knowing the frequency and duration of staff visitation can allow organizations to implement clinical initiatives that can be measured and evaluated.
Self driving cars are heralded as the future of transportation safety. It will reduce manual labor, human error, and potentially eliminate dangerous and deadly accidents. If computer vision can improve safety and productivity while we drive, why would we not let it improve our lives when we are sick?
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