Change Healthcare Launches New AI Model to Extract Diagnostic Data from EHRs for Case Management

Change Healthcare Launches New AI Model to Extract Diagnostic Data from EHRs for Case Management
Change Healthcare Launches New AI Model to Extract Diagnostic Data from EHRs for Case Management

What You Should Know:

– Change Healthcare launches a new artificial intelligence model that automatically extracts diagnostic data from clinical notes to increase the efficiency of automated medical necessity reviews by over 20%.

– The new Change Healthcare AI models are trained using
clinical data and are honed by expert physicians.


Change Healthcare unveils new innovative new Artificial Intelligence models, trained by expert physicians, which extract meaningful diagnostic information from the text in EHRs. The first application of this technology will be within the InterQual AutoReview™ solution, which automates medical necessity reviews using real-time data from EHRs.

Get Integrated, Automated and Accurate Medical Reviews
Right from your EHR

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.


Driven by InterQual Criteria

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 Change
Healthcare-developed AI models with ultra-high prediction accuracy that can be
used to improve processes across the Change Healthcare portfolio and healthcare
industry.


Why It Matters

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 Nilo Mehrabian, VP of Client Strategy, Decision Support, at Change Healthcare. “InterQual AutoReview already reduces the amount of time case managers spend completing medical necessity reviews, and now it can automatically eliminate one of the most time-consuming and subjective aspects of a review—deciphering a radiologist’s report.”


<!–

–>