Survey finds over 75% of radiology organizations using AI lack clear, quantified ROI data.
Key Details
- 1Black Book Research surveyed over 200 hospital and clinic leaders ahead of RSNA.
- 2More than 75% of organizations using radiology AI do not have quantifiable ROI information.
- 3About 24% had measurable ROI data; of these, 36% received AI payments per study.
- 4Other payment structures included bundled payments (25%), enterprise licenses (20%), and per-user pricing (10%).
- 5Despite lack of ROI clarity, most leaders reported positive or neutral feelings about AI's impact.
Why It Matters
As AI becomes more integrated into radiology workflows, the lack of clear ROI data could slow adoption or influence future investment decisions. Understanding payment models and satisfaction levels helps stakeholders adapt strategies for successful AI implementation.
Source
Radiology Business
Related News
•AuntMinnie
AI’s Path in Radiology Hinges on Tech, Policy, and Human Insight
SIIM-CAIMI keynote highlights that AI's future in radiology depends on synchronized advances in technology, regulation, finance, and culture.
•Radiology Business
Meta Funds Ohio State’s Radiology AI Innovation Projects
Meta will fund Ohio State researchers to explore AI-driven advancements in radiology, including chest X-ray reporting and disease prediction.
•AuntMinnie
SIIM-CAIMI Leaders Discuss Key Trends in Imaging AI Deployment
SIIM-CAIMI program chairs highlight AI's transition from algorithm evaluation to real-world implementation in medical imaging.