Providers utilize business intelligence to monitor referral patterns and collaborate with clinicians who order their services. Such analytics tools have also been deployed in the specialty to improve productivity, track patient satisfaction and bolster quality.
Of surveyed and interviewed U.S. physicians who showed significant six-month improvement in follow-up vs. baseline wellness checks, 47% attributed the gain to active personal changes. Not far behind were those who credited active work-related changes—40% of the field.
The new entity, Precure, will be owned by both groups. Its work in detecting early disease for timely intervention stems from a research project launched this summer. The Mayo Clinic said Precure will make the results of that initiative actionable.
Any negotiations are currently in the early stages, sources told Reuters. If a deal closes, Waystar could be taken off the stock market and restructure itself as a private business.
Add lanes to a highway and the traffic only gets more congested. Add doctors to a local health system and waiting times increase. What explains these parallel paradoxes?
With generative AI coming into its own, AI regulators must avoid relying too much on principles of risk management—and not enough on those of uncertainty management.
There’s no shortage of resources for healthcare workers who wish they knew AI well enough to talk shop with the technology pros who develop the models. The problem is weeding through the offerings to get to what will really work for you.
Discussions of AI governance may cause many an eye to glass over, but the discipline is as crucial to the ascent of AI in healthcare as big training datasets drawn from diverse patient populations.
For whatever reason, the grownups seem to get all the attention when talk turns to AI in healthcare. All the kiddos get to do is look on and listen in. Now comes a worthy little effort to balance the seesaw.