Stephen Herman, MD, an associate professor of radiology at University Health Network in Toronto, Ontario, Canada, and CEO of MedCurrent, discusses how radiology decision support systems can help reduce radiation exposure, and what it will take for the tools to catch on.
Stephen Herman, MD, is an associate professor of radiology at University Health Network in Toronto, Ontario, Canada, and CEO of MedCurrent, developer of decision support systems. Here he discusses how radiology decision support systems can help reduce radiation exposure, and what it will take for widespread adoption of the tools.
For more on radiation safety, check out Taking Steps to Improve Radiation Safety.
Radiology decision support systems have been discussed as a way to help reduce exposure. How much of an impact can these tools make?
The impact could potentially be significant.
Consider that some ordering physicians order a CT scan of the head for patients with simple headaches. Research shows that the chance of demonstrating significant disease in such patients is very low, and therefore CT should not be used. A radiology decision support (RDS) tool would have guided the ordering physician to this fact and saved the patient from being exposed to radiation unnecessarily.
Now consider a patient with AIDS who develops a simple headache. In this situation, a physician may order a CT scan of the head. According to evidence-based criteria, the ACR recommends that such patients undergo MRI, not CT. If an RDS solution were used, the ordering physician would have seen this recommendation and would likely change the order from CT head to MRI brain, thereby avoiding unnecessary radiation.
In some cases, low-dose CT scanning is the go-to standard for assessing specific problems in some patients. The newest RDS systems distinguish between variations in procedures to guide ordering doctors in selecting a low-dose CT rather than a standard CT. Again radiation exposure is reduced.
Finally, the most advanced RDS solutions can actually auto-protocol the study. When using such a system, the doctor places an order for a CT scan and the system automatically selects the best protocol for the given patient problem. Protocols are determined by experienced radiologists, thus reflecting the optimal method using the least amount of radiation required. Without needing specify the exact order, the referring physician is assured that the CT being provided uses the least amount of radiation possible.
How widespread is the use of these systems?
Use of RDS systems is not widespread at the present time, yet experts predict a significant increase in adoption rates in the coming years. Healthcare providers and payers face continued and increasing pressure to reduce costs. Several studies have shown financial value in replacing the radiology benefit management model with an RDS model.
Minnesota is moving to a model that uses RDS, and Washington State recently announced a similar initiative. At the federal level, while future stages of meaningful use are yet to be clarified, it is likely that RDS will be included in a forthcoming definition.
What needs to happen to help increase adoption?
Adoption rates for radiology decision support solutions will increase as:
- healthcare providers and payers become more aware of RDS solutions
- early adopters prove cost-reduction benefits
- users realize the value of eliminating the “hassle factor” and reducing expenses associated with RBMs as “middle man”
- increasing numbers of physicians use them
- accountable care organizations (ACOs) become more widespread
- government programs mandate their use; results of the just-launched Medicare Imaging Demonstration Project will be used to help guide these decisions
I anticipate that the evolution of RDS systems will follow a similar path to the evolution of PACs. What’s now the mainstream technology for radiologists was once resisted because it required a change to physician behavior. As RDS solutions become the norm, physicians will look back and wonder how they practiced without one.