AI Case Study
NCI designated cancer centers reduces time to treatment for diagnosed patients by 5 days using machine learning and natural language processing
NCI-Designated Cancer Centers have implemented Digital Reasoning’s deep analytics care management software to automate processing pathology and radiology reports. The software helps speed up patient's journey from diagnosis to treatment by discovering, classifying and prioritizing cancer cases for optimal follow-up. It augments health care providers by supporting the workflows, triage and extracting key points from documents.
Healthcare Providers And Services
"Digital Reasoning’s deep analytics care management software uses patented Natural Language Understanding and machine learning technology to intelligently read pathology and radiology reports at the front-end of the cancer diagnosis and treatment process. The software augments the cancer care workflow in real-time by discovering, classifying, and prioritizing cancer cases for optimal follow-up; augmenting physicians, nurse navigators, care coordination and oncology pathway efficacy with intelligent workflow support, including dynamic work queues, care pathway matching, and care complexity triage; and extracting key data elements to automate and ease documentation burdens."
The results claimed:
* Improves the patient experience, including cutting the time from diagnosis to first contact with a physician to less than 72 hours
* Increases healthcare system margins and efficiency and enhances clinical quality, improving speed to treatment by over 1 week and increasing survivability
"High-quality cancer care is a labor-intensive process with oncologists, radiologists, pathologists, nurse navigators, patient care coordinators, and registrars. Across the clinical workflow, artificial intelligence (AI) can augment the effectiveness of the clinical care team by invisibly assisting with the repetitive, routine tasks behind-the-scenes. Today, 162 hospitals across the country use Digital Reasoning’s AI-enabled cancer software to raise the standard of care — improving clinical quality, patient experience, efficiency, and productivity while growing oncology patient volume."