AI automatically extracts diagnostic data from clinical notes to increase efficiency of automated medical necessity reviews by over 20%
Conducting a medical necessity review is a time-consuming process consisting of retrieving and reviewing clinical data from a patient’s record and manually completing the review. This task can take anywhere from 10-30 minutes for a typical review and places a significant administrative burden on highly skilled clinical staff.
The InterQual AutoReview™ solution already reduces this burden by extracting structured data, such as labs, medications, and vital signs, directly from the EHR—representing up to a 75% reduction in the administrative burden of conducting reviews. Now Change Healthcare AI Natural Language Processing models, created and trained by Change Healthcare’s AI data scientists and expert clinicians and radiologists, can identify diagnostic information, such as the presence of pneumonia, bowel obstruction, pancreatitis, and other conditions, from unstructured radiology reports.
With hundreds of medical reviews conducted in many hospitals each day, the impact of this enhanced technology is significant. Case managers are freed from the administrative burden of not only retrieving and reviewing information, but also interpreting narratives, enabling them to focus on more complex cases.
“This is an extremely helpful application of AI for case managers,” said
The new Change Healthcare AI models are trained using clinical data and are honed by expert physicians. As a result, the InterQual AutoReview™ solution can identify diagnostic information, such as the presence of pneumonia from unstructured clinical narratives, enabling an additional 20% of pneumonia reviews to be automatically completed on top of reviews already completed through structured EHR data. This is just one of several
Providers interested in learning more about this new AI technology within the InterQual AutoReview™ solution can visit the InterQual AutoReview AI resource page.
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