Connecting the Dots: AI’s Impact on Radiology Economics, Quality and Safety

LaurenGoldingMDThis post was contributed by Lauren P. Golding, MD, a radiologist at Triad Radiology Associates in North Carolina and faculty for the 2018 ACR Annual Conference on Quality and Safety

Artificial Intelligence (AI). There’s no question it will have a big impact on radiology. But don’t buy into all the hype that it’s a threat to our profession. More truthfully, it holds tremendous potential to help radiologists deliver more value through better quality, which will both drive down unnecessary costs and enhance our critical contribution to patient care particularly in the big picture of population health.

This fall, I’ll be among the faculty presenting at the 2018 ACR Annual Conference on Quality and Safety in Boston during the session “The Chicken and the Egg: Economics and Improvement.” We’ll dive into the business case for improvement, regulatory imperatives and opportunities with AI, practical strategies for measuring and communicating the value-add of radiology, and the costs of delivering good and poor quality. Earlier in the day, Dr. Andrew Rosenkrantz will walk us through his work on radiologist accountability for costs associated with incidental findings. Registration is now open, and I hope that many of you will join us.

This isn’t the first time we’ve talked about AI’s impact on radiology economics, and it won’t be the last. As my fellow faculty, Dr. Gregory Nicola, pointed out in a post for this blog last month, AI application will further advance our ability to reduce unnecessary care and variance. AI could also improve efficiency in data management and integration, building upon and amplifying the benefits gained from participation in the Radiology Support, Communication and Alignment Network (R-SCAN™) and registries. With shifts in US payment policy from traditional fee-for-service to value-based reimbursement models in the Medicare Quality Payment Program, AI presents opportunities – and challenges – for reimbursement.

The ACR Data Science Institute™ (DSI) is working to assist radiologists, AI algorithm developers and federal agencies by defining use cases, providing validation services and enhancing performance-monitoring capabilities. The DSI co-hosted the Spring 2018 Data Science Summit: Economics of Artificial Intelligence in Healthcare at the Society for Imaging Informatics in Medicine (SIIM) 2018 Annual Meeting in May. And in August, DSI will co-sponsor the National Institute of Biomedical Imaging and Bioengineering (NIBIB)’s free two-day workshop on AI in Medical Imaging; a workshop that was so popular it reached capacity on the same day that NIBIB opened registration.

We don’t practice in silos. Cost, quality and safety are closely tied together. By examining the whole system and strategically engaging in regulatory and payment policy issues in AI, we can leverage AI to deliver better value for patients, radiologists and the healthcare economy. See you in Boston!

  • What are some ways you are adding value to your practice by improving quality and safety? Has it resulted in an increased ability to control costs as well?

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