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.
AI could appreciably improve the delivery of healthcare services to patients—if only people trusted it. For many, the difference-maker would be nicely crafted federal regulations.
From boutique clinics in Mexico to medical spas in Europe to top-tier academic medical centers in the U.S., healthcare organizations courting medical tourists are enjoying boom times.
As debate simmers over how best to regulate AI, experts continue to offer guidance on where to start, how to proceed and what to emphasize. A new resource models its recommendations on what its authors call the “SETO Loop.”
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.
