Up to half of medical organizations either already using or preparing to implement AI
Nearly 20% of healthcare organizations have already implemented some sort of artificial intelligence application into their workflows, and over half are preparing to do so in the near future, according to new insights from KLAS—a leader in healthcare IT insights.
It was evident during this year’s annual meeting of the Radiological Society of North America that AI is no longer spoken about exclusively in future tense. With the number of FDA approved AI-enabled applications nearing 1,000, it’s clear the healthcare industry is ready to embrace the evolving technology, and that its presence will continue to expand within the medical field.
“The latest wave of high tech will allow us to delegate the least attractive parts of our jobs to the AI models while retaining the rewarding tasks, focusing on patient care and personal connections,” Curtis P. Langlotz, MD, PhD, a noted physician and president of RSNA, said during the President’s Address on Sunday. “These advances can upskill us all, reduce burnout and bring better healthcare to underserved areas, and it can do so while we develop richer human connections like the ones we form in the reading room, in the exam room, and at meetings like this one.”
The new KLAS report contains data from over 200 healthcare organizations across the United States. Collected between May 2023 and April 2024, the data offers valuable insights into trends related to AI adoption across a broad spectrum of organizations during a time when federal AI approvals are growing by the hundreds.
Here are some of the report’s key findings:
Larger organizations are leading the way in terms of AI adoption, with 42% using it already and considering upping that utilization in the near future.
Smaller and midsize organizations (those that complete between 100K-499K studies annually) are most likely to integrate AI soon, with 30% planning to implement it for the first time over the next year.
Applications focused on neurology use cases, such as stroke detection and prioritization of critical results, were most popular among organizations using or considering AI, followed by computer-aided detection (CAD) software for breast cancer screening exams.
Other popular use cases were lung nodule detection algorithms and automatic report generation tools that allow radiologists to review, edit and finalize results.
As of August 2024, the FDA had cleared 950 clinical artificial intelligence-enabled applications. With 723 FDA-cleared algorithms, AI applications tailored to radiology make up over 70% of all approved products.