No radiologist wants to see their patients fall through the cracks because of a missed finding or delayed treatment. In the fourth installment of our series on the power and potential of AI in radiology, we look at how intelligent solutions support more comprehensive care by helping radiologists detect the things they can’t miss.
Earlier in the series, we focused on how AI helps alleviate some of the biggest causes of radiologist burnout by automating mundane tasks and surfacing hidden or hard-to-find information. In this article, we turn our attention to how AI-powered solutions can help ensure we capture and deliver the critical information needed to support personalized care decisions, increase efficiencies, and lower healthcare costs.
AI adds value—by spotting the things we can’t miss
Modern AI tools can help minimize the increasing pressure on radiologists to keep pace with rising imaging volumes while maintaining quality and precision. AI can serve as a reliable safety net by catching errors like laterality and sex mismatches and identifying ancillary or less obvious findings like a breast lesion on a chest CT. Knowing that AI is running in the background to surface relevant findings enables radiologists to have a more comprehensive view of the case and stay focused on their interpretation. This all extends the value of radiology, giving downstream care teams more complete, actionable insights.
AI adds value—by increasing quality and safety
Perhaps one of the biggest challenges in healthcare is managing follow-ups. AI can help here, too, providing in-workflow capabilities that support consistent recommendations and help guide appropriate follow-up care.
And it doesn’t stop there. AI can also help close the loop on patient follow-up. It supports a proactive and comprehensive approach to tracking patient activity and streamlining communication to help prevent patients from falling through the cracks—improving patient care and reducing the risk of medical malpractice litigation.
AI adds value – by supporting a comprehensive approach
At Trinity Health Michigan (formerly Saint Joseph Mercy Health System), Alonzo Lewis, CEO, has seen the impact of implementing an end-to-end model. He states, “This has allowed us to be more proactive—doubling our follow-up recommendation identification and tracking so we can follow each patient through the process to closure.”
Nuance’s intelligent radiology solutions help imaging teams deliver more value to the care providers and patients they serve. Our customers are at the forefront of a monumental shift in healthcare. They are successfully integrating AI into their workflow to break down information silos and build connections across a diverse ecosystem of imaging stakeholders. And they’re achieving some spectacular results, including a 74% reduction in time-to-intervention, 29-35%fewer missed nodules, and up to 52% improvement in follow-up compliance.
Next time: Seizing the opportunity – How AI drives intelligent collaboration
Imaging AI is about more than just driving efficiency and value for radiologists, its impact continues downstream by making report and imaging data more actionable and consumable by referring physicians. In the final article in this series, we’ll explore radiology’s pivotal role in driving an enterprise AI strategy.
