4 things imaging providers should consider when choosing an AI vendor

Forty-seven percent of healthcare organizations are either already using artificial intelligence (AI) to help with medical imaging or actively planning to use AI, according to a new report published by KLAS. And adoption is expected to escalate sooner than later.

In the report, called Artificial Intelligence in Imaging 2018, author Monique Rasband and coauthor/analyst Emily Paxman studied the behavior of more than 80 healthcare organizations. The authors also listed four key things organizations should look for in an AI vendor.

“Where there is success, there are typically several key vendor attributes present,” Rasband and Paxman wrote. “By looking to partner with vendors who exemplify these traits, providers can begin their imaging AI journey on the right foot.”

1. Crystal clear expectations

Healthcare providers are often disappointed with new technology, the authors explained, because their expectations were too high. “A clear discussion about what outcomes will be achieved, when those outcomes will be realized, and the steps that both the customer and vendor need to take to realize the outcomes is key,” Rasband and Paxman wrote.

2. Proactive, strategic relationships

As is the case for so many things in both business and life, communication is crucial when it comes to developing new technologies. Organizations should look for a vendor that can build strong relationships and treats their account with the respect and attention it deserves.

3. A central focus on training

“Quality of training is one of the best predictors of customer satisfaction, affecting usability, adoption, and perception of a system’s functionality,” the authors wrote. “Unfortunately, training (particularly ongoing training) is often taken off the table by vendors during contract negotiations to lower the purchase price.”

Providers should seek a vendor who will work to remove financial barriers to training instead of cutting training out of the equation all together, they added.

4. Strong data governance

“Strong data governance can make or break an imaging strategy,” Rasband and Paxman wrote.

Time and time again, providers who have gone live with an AI strategy have said governance played a significant role in their success. Vendors should encouraging their partners to focus on governance, providing assistance when necessary to make implementing AI as painless as possible. This, the authors added, can be “the difference between realizing a tangible ROI and sinking resources into a failed project.”

More information on KLAS and its various industry reports can be found on the company’s website.