RSNA 2019: Tips for selling AI adoption to healthcare executives
AI technologies could change the practice of medical imaging forever, but many hospitals and radiology departments remain hesitant to move forward and adopt it at their own facilities.
Why is this still the case? That’s exactly what Ben Panter, CEO of Blackford Analysis, explored during a presentation Dec. 3 at RSNA 2019 in Chicago.
Panter, speaking from the podium at RSNA’s AI Theater, noted that more companies are working in AI than ever before, with funding and the number of FDA-approved applications both at an all-time high. Adoption is still moving at a relatively slow pace, however, due to questions about the return on investment (ROI) and concerns over the high cost of deployment.
“What we have to do is find different ways to express the ROI to a radiology practice so that we can facilitate the purchase of AI products,” Panter said. “Because if we’re talking about the real-life use of AI in a clinical environment, somebody needs to pay for it. And we have to be able to explain how that entity would benefit from making such a purchase.”
When trying to convince decision makers at hospitals and radiology practices to invest in AI, there are three distinct ways to tell them they will see a return on their investment: radiologists will become more efficient, significant value will be added for referrers and volumes will increase.
“Increasing radiologist efficiency is perhaps the simplest, most straightforward argument to make,” Panter said, noting that AI has been shown to speed up care considerably.
Hospitals may need to spend money to acquire these evolving technologies, but the potential improvements in efficiency can show even the most skeptical executive that it may be time to push forward with AI. More efficient radiologists, of course, mean that the radiology department is seeing more patients, and those patients are likely walking away more satisfied as a result of being treated so quickly.
Another key point to make when explaining the potential ROI of AI, Panter said, is that these advanced algorithms can help replace other procedures altogether. And that often leads to patients who entering the radiology department who would have typically gone elsewhere in a hospital.
“So you’re bringing in new patients,” Panter said. “And you’re also improving patient outcomes, decreasing risk and improving the patient experience.”
Michael has more than 18 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.