What makes the ARE4 system so compelling is not necessarily ex post facto processing but near real-time processing of data. That makes for a variety of interesting possibilities, because the system can begin analyzing physicians’ notes the moment they are written. For example:
ARE4’s near real-time NLP capability can review a physician’s report, flag if a certain confidence level is not met, and can suggest routing the report to another specialist for further review.
Additional Imaging Assessment
After initial training, the ARE4 system can classify reports based on if they contain clinically significant findings. After classification, the system can recommend additional imaging.
Best Practice Measurements
It is difficult to generate and distribute best practice measurements without expensive, time consuming manual intervention. Manual processes naturally delay both reporting and decision making. Our ARE4 system can review reports, measure best practices and then provide follow-up metrics without most of the tedious manual curation. For example, if the best practice for a specific tumor size is to follow up every 24 months, our system can check for compliance to that goal, automatically and without any user intervention.
Our system can also execute pre-defined reports that can check for a variety of radiology report errors, like missing laterality, conflicting findings, and size mismatches. Miscommunication is a common cause of treatment errors and malpractice lawsuits. Our system minimizes the exposure to miscommunication.