RadAI Case Study

RadAI, founded in 2018 by former Greensboro Radiology radiologist Jeff Chang, pioneered the first generative AI product in healthcare. The company’s innovative solutions address the massive data challenges in medical imaging, particularly in managing incidental findings.

Cone Health faced inefficiencies in radiology workflow, report generation, and low follow-up rates for incidental findings. RadAI’s AI-driven solutions presented an opportunity to streamline processes and improve patient care.

After initial IT pushback, Prinnovo facilitated meetings between RadAI and internal stakeholders to understand key requirements. RadAI’s team, led by radiologists, demonstrated expertise and responsiveness. Their solutions, including Impressions, Continuity, and Reporting, were identified as potential game-changers for Cone Health’s radiology department.

Prinnovo leveraged its understanding of health system engagement value to negotiate agreements. Joint development and data use agreements were established, aligning incentives between RadAI and Cone Health. This partnership showcased Prinnovo’s ability to create mutually beneficial collaborations.

RadAI and Cone Health co-developed solutions, focusing on automating workflow rather than image analysis. The pilot process proved the effectiveness of RadAI’s tools in improving report accuracy, saving radiologists’ time and enhancing follow-up rates for incidental findings.

Implementation of RadAI’s solutions at Cone Health led to significant improvements. The stage one lung cancer diagnosis rate increased from 26% to 36% over five years, potentially saving approximately 50 more lives in Greensboro alone. Follow-up rates for incidental findings improved from 30-40% to 80%.

Since partnering with Cone Health, RadAI has experienced remarkable growth. Recognized as the 19th fastest-growing company in North America by Deloitte, RadAI completed a $50 million Series B funding round. The company now serves almost half of all US health systems and 9 of the 10 largest radiology groups.

Prinnovo identified RadAI’s potential to solve critical imaging challenges, resulting in improved patient outcomes and operational efficiency. With RadAI’s solutions now widely adopted, your health system could also lead in healthcare innovation. Request a consultation to explore opportunities.