While many healthcare stakeholders are still coming up to speed on what AI can do for them, federal policymakers are wasting no time looking to what might come next.
With the question, “How can AI help transform healthcare delivery and improve patient health outcomes?”, the Innovation Center of the federal Centers for Medicare and Medicaid Services recently announced the AI Health Outcomes Challenge for early 2019 with the goal of using new AI and analytics methods to better predict health outcomes and improve healthcare delivery.
The challenge, says CMS, is to look beyond existing uses of the technology.
“It’s not enough to build on the technology that currently exists. We need to ask bold questions, like how artificial intelligence (AI) can transform and disrupt how we think about healthcare delivery,” CMS said in announcing the challenge.
For the challenge, policymakers want input from outside familiar terrain, inviting all sectors — not just those involved in healthcare — to take part, including tech companies, academic institutions, and scientists from across the AI landscape.
The details of the challenge are still being developed, but CMS said it is looking to apply the technology to all health care services, incorporating AI into new payment and service delivery models as well as medical care. “The goal is to help the healthcare system deliver the right care, at the right time, in the right place, and by the right people,” the agency said in its announcement.
As tech writer Kevin McCaney sees it, the wide-ranging scope of CMS’ challenge “reflects the impact that AI is already having in the field, with its ability to crunch massive amounts of data, recognize patterns, predict likely outcomes and draw conclusions.”
He notes the “impressive results” AI systems have had when it comes to “detecting signs of cancer, diagnosing heart disease, and sequencing genetic data, to name a few medical applications.”
Moreover, he points out that the Food and Drug Administration has begun approving AI-powered medical tools, and announced plans to accelerate development and clinical trials of AI devices.
AI is also being used in a variety of patient monitoring applications, says McCaney, as well as in increasing hospital efficiency. “Hospitals have tested it to take over data collection duties from ICU nurses in order to free up their time for patient care, monitor high-risk patients for early signs of sepsis, and track patients’ movements to send alerts if they’re at risk of falling. It’s even been used to monitor the effects of light and noise levels on infants, with an eye toward improving their care by improving their environment.”