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RSNA 2022: Our Top 3 Takeaways

aiOS, Read Time, Turnaround Time, Workflow

RSNA 2022 has wrapped up, leaving us with another unforgettable conference in the books. This year we felt an unprecedented enthusiasm for AI and its potential for widespread adoption. As always, our time in Chicago brought light to many new and exciting developments in radiology. Of course, the most exciting conversations for us involved in-depth discussions about AI and its ever growing role not only in the day to day life of radiologists, but hospital-wide workflows. Among the countless exciting, interesting and compelling things we learned at the conference, here are three of our biggest takeaways.

1. AI Is Catching On

Based on the conversations we had at RSNA, we noticed a major shift in the general perception of healthcare AI, virtually redefining the technology from a “nice to have” into the standard of care. It has become more obvious than ever that organizations that have yet to invest in AI are beginning to have in-depth conversations about it, many even beginning to build out their AI strategies. In fact, the numbers back this up. According to a March 2021 report from Optum, 90% of healthcare executives reported having an AI strategy in place. This meant a shift in the content of the conversations, whether that be from U.S.-based radiologists or radiologists from abroad. Questions were less centered around the necessity of radiology AI and were more oriented toward practicalities such as implementation and ROI. 

2. Beyond the Algorithm: AI Now Viewed as an Enterprise Solution

In addition to AI  gaining ground with radiologists, leaders are now beginning to look at their AI strategies from a hospital-wide perspective. Instead of fielding questions around AI skepticism, we had conversations about nuanced AI strategies that go well beyond the traditional single-point solution model. We found there is a market need for a one-stop shop, or an AI marketplace, that allows hospitals to ditch the pick-and-choose buffet style of AI algorithms  the market has grown accustomed to. Amongst leading hospitals, there is a desire to fill the gaps intrinsic to running disparate AI solutions from multiple vendors. We used this as an opportunity to educate about our award-winning aiOS™ and how an operating system  gives healthcare providers the ability to orchestrate multiple AI solutions hospital-wide, showing an impact and ROI well beyond the radiologist workstation.

3. Radiologists Are Still Leading AI Adoption

The idea that radiologists are in the driver’s seat for hospital-wide AI adoption is something we’ve talked about multiple times, but our conversations at RSNA 2022 served as true – and continued – validation of that idea. The content of conversations about the value of AI went well beyond metrics, like algorithm sensitivity and specificity (which are important discussions worth having, especially in defining value in radiology), and focused more around patient outcomes, ROI, and other impactful metrics such as the impact of AI on length of stay. It not only shows that radiologists believe in the value of AI for their profession, but that it’s also a jump-off point for closer involvement in patient care and downstream facility impact. This is obviously a thrilling development for us to see in the general perception of radiology AI, and we believe this really gives radiologists a unique opportunity to initiate the AI revolution in healthcare.

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