While there is a lot of hype around AI and its profound influence on the future of the medical imaging, today’s main concern of hospitals and imaging centers remains the same – How can AI generate ROI?


There are three key areas where a practice can deliver ROI using AI:

  • Increasing radiology efficiency, by allowing radiologists and departments to work faster
  • Adding value for referrers, by providing better quality of care and evidencing that for patients
  • Replacing or augmenting existing procedures to increase volume that wouldn’t have otherwise come to radiology.

For all of the above, it is vital to find an alignment between the user (beneficiary) and the budget holder. And so, each of these also depends on the respective environment for which the AI is intended, whether that is radiology groups, an imaging centers, radiology departments or health systems. For example, in a hospital environment, the buyer is a hospital, while the user is a radiologist. But in a radiology group, the buyer is radiology led, so it may be easier to demonstrate value.

To help illustrate this point, we now look at some examples of the way that AI generates value and ROI for different audiences.


Increase efficiency

For the radiologist, this is a fairly simple argument – AI tools like image registration and segmentation can save time by allowing you to read faster and help avoid missed findings. As a result of this the ROI is basically about reducing cost by saving time. For the radiology department, the argument is more focused on driving a higher patient throughput, which means increased volume for the same capital investment. It’s also about being able to defend referral decisions.


Add value for referrers

This links to making a radiology group a differentiator for referrers and driving volume growth as a result. The keyways that AI can drive ROI for referring physicians is through quantitative reporting and radiology triage.

Quantitative reporting is about understanding the benefit of what a radiologist could accomplish if they had more time to report a study. Whether that’s quantification of lesion sizes or comparison to population norms.

Radiology triage on the other hand is best understood by considering what the impact would be if every study was read on acquisition. This would deliver a faster reaction to life-threatening conditions.

In both of these cases, the ROI for the radiology group is about competitive differentiation and increased volume, while for the hospital, the value is about improved patient outcomes and communication of that care to the patients.


Replace or augment existing procedures

By replacing a high risk or high cost procedure from elsewhere in the hospital with an imaging study, you are increasing radiology volume with work that wouldn’t have otherwise come to radiology. This also benefits the hospital by an overall reduction in cost for same result, combined with a reduction in patent risk and an improved patient experience.

Similarly, by providing better information to team involved in a high risk surgical procedure you are still adding volume to the radiology department, but the benefit to the hospital is now more focused on a reduction in OR time.


To find out more on how to unlock the value of AI in radiology, read our White Paper:

Download the White Paper