The ACR Data Science Institute® (ACR DSI) released three new Non-Interpretive Patient Facing use cases in April, adding to the guidelines DSI provides to the artificial intelligence (AI) community. Developers can freely access 12 patient-facing use cases on the DSI website.
The new Non-Interpretive Patient Facing cases include:
- Triaged Patient Friendly Radiology Report Follow-up Recommendations: In the current landscape, many patients can view their radiology reports prior to meeting with their referring clinician, but the reports are only generated for physician or provider readers. Adding patient-friendly automated follow-up recommendations would enable patients to become more involved in their care, enhance their understanding of necessary follow-up, and potentially improve the frequency of follow-up recommendations being completed.
- Ensure Patient Follow-up of Radiology Report Recommendations: With an automated patient follow-up for annual screenings, we can expect mortality and late diagnosis to significantly decrease.
- Ensure Referring Clinician Reads the Radiology Report: Confirming that radiology reports have reached their destination and were read by the ordering clinicians will help reduce risk to the patient, radiologist, referring clinician, and institutions that employ them, and lessen the need for alternative communication methods by radiologists resulting in improved efficiency.
Register here for a free upcoming Non-Interpretive AI webinar, “Beyond Interpretation: Unleashing the Potential of Non-Interpretive AI in Radiology,” on Wednesday, May 31, from 7–8 pm ET. The key learnings from the webinar and Q&A panel will include understanding the breadth of non-interpretive AI tools available for clinical practice, how non-interpretive AI tools may impact the radiologic practice from an operational and clinical standpoint, and the outlook for emerging non-interpretive AI tools in the marketplace.
About ACR DSI use cases: ACR DSI use cases are scenarios where the use of AI may help improve clinical settings and medical imaging care. They provide structured data elements for training, testing and monitoring algorithms to help those developing AI to create new AI models, or improve existing AI products. ACR DSI has released more than 200 use cases developed by subspecialty data science panels of experts.