Net Health, a software and analytics tools developer for specialty healthcare providers, released two AI-powered capabilities within its EHR to reduce the risk of amputations and predict how quickly wounds will heal.
The company’s Risk of Amputation Indicator uses predictive analytics to tell clinicians how likely it is that a wound could lead to an amputation, and the Wound Healing Velocity Indicator informs doctors of the likelihood of a wound healing within four, eight, twelve or sixteen weeks.
“Wound care clinicians work tirelessly to help their patients,” Josh Budman, vice president of analytics at Net Health, said in a statement.
“But wound care is complex – there are multiple factors that can prolong or interrupt healing. What clinicians need is accurate information and guidance about the wounds they are treating. Predictive models and machine learning represent the next level in the evolution of wound care technology. Coupling that capability with the EHR most wound care clinicians trust and rely on provides a powerful tool to help patients get better faster.”
WHY IT MATTERS
More than two million people are living with limb loss in the U.S., and 185,000 have amputations each year, according to data compiled by the Amputee Coalition.
In 2014, hospital charges for patients who experienced an amputation totaled $10 billion, and lifetime healthcare costs for people with limb loss is more than $509,000, compared with about $361,000 for people without limb loss.
THE LARGER TREND
Artificial intelligence and machine learning are fast-growing tools for healthcare providers.
Just this month, an AI-powered mental health platform was launched in India. Ultromics, a maker of AI-supported cardiac imaging tools, announced it raised another $33 million in funding. ClosedLoop.ai, winner of the Centers for Medicare and Medicaid Services’ Artificial Intelligence Health Outcomes Challenge, scooped up $34 million. Abbott also landed FDA clearance for software that uses AI to give clinicians a better idea of blood flow and blockages in heart vessels.
But experts have pointed out potential problems in artificial intelligence and machine learning, like human biases creeping into algorithms or simple mistrust on the part of patients and providers who can’t always see or understand how they work.
“Technology has already dehumanized healthcare,” said Pat Baird, senior regulatory specialist at Philips, at a CES 2021 virtual panel in January. “I’m hoping this will help re-humanize healthcare by freeing up the caregivers, letting them give care. And some of the things that we can let the computers do, we can let the computers do now.”