Most organizations using AI for radiology are unsure of its ROI
Now that artificial intelligence-powered tools are well established in many radiology workflows, it seems fitting that there would be data available on organizations’ return on investment (ROI). However, this is not the case at all, according to new survey information.
Collected by Black Book Research the week leading up to the annual meeting of the Radiological Society of North America, the survey responses suggest that over 75% of organizations that have implemented radiology AI into practice do not yet have clear, quantified financial ROI data. Despite this, leaders within these organizations did not show concern regarding their AI investments, as most believed the move resulted in positive or neutral impact, while others noted their facilities had not yet attempted to measure the financial effects.
"On the RSNA show floor, AI is everywhere," Doug Brown, founder of Black Book Research, said in a release. "But when you talk to CFOs and imaging leaders, you hear a different story: they're paying for AI, but often can't point to a clean line on the P&L that proves it's paying them back."
The survey included data from more than 200 hospital and clinic representatives throughout the United States. Respondents included chief financial officers, imaging service line leaders, radiology practice executives and IT/PACS leaders.
Around 24% of respondents had measurable data to report. Of those 36% indicated their organization was receiving AI payments on a per-study basis; another 25% reported their AI-related payments were bundled with modality or PACS/enterprise imaging contracts, while another 20% signaled payments were received through enterprise-wide licenses. Just over 10% reported per-user pricing.
The data suggest that AI reimbursement is still lagging, with just 14% collecting payments clearly tied to AI. However, nearly 40% suggested that AI implementation was having a secondary impact on finances and increasing reimbursement elsewhere, such as through increased throughput, new service lines or fewer denials. Conversely, around one-third of respondents could not identify revenue attributable directly to AI since its integration.
In terms of how the use of AI has affected respondents’ staffing, there were no notable findings from the survey. Most indicated they have used AI to reduce radiologist burden in some form, but AI has not had measurable impacts on staffing, other than 24% reporting their companies avoided hiring or redeploying staff to growth areas; this has not resulted in net cost reductions yet though.
"Most organizations are using AI to keep up with rising volumes rather than to shrink their workforce," Brown noted. "The return is often deferred hiring or capacity expansion, which is harder to quantify and even harder to communicate to boards and payors."
It was evident that many organizations’ structured reviews of AI ROI are lagging behind implementation. Over one-third reported intentions to conduct a formal review over the next 12 months.
In addition to her background in journalism, Hannah also has patient-facing experience in clinical settings, having spent more than 12 years working as a registered rad tech. She began covering the medical imaging industry for Innovate Healthcare in 2021.