Realyze Intelligence combines the latest in artificial intelligence (AI) technology with clinical expertise, interpreting a patient’s health record to provide deeper insights into both the individual patient and populations, ultimately driving better outcomes for health care. Realyze uses AI and natural language processing to identify precise patient populations with chronic diseases and cancer so that they can get the most beneficial treatments.
The Realyze clinical intelligence platform “reads” both the detailed clinical notes and structured data from patients’ electronic medical records (EMR), allowing the software to more thoroughly understand the person and their comorbidities. This deeper knowledge of the patient is scaled across the entire population to identify precise cohorts with high clinical risk. Those individuals can then be prioritized to receive appropriate care in a timely fashion. Realyze is able to understand the patient and populations in greater detail.
Providers use Realyze’s web-based tools to quickly assess the data that are already present in patients’ notes. The dynamic platform can be deployed within a provider’s workflow, making the solution effective for a variety of patient conditions, including various cancers, chronic kidney disease (CKD), diabetes, and inflammatory bowel disease (IBD).
“For providers to give the most effective care, they need a complete understanding of their patients and all of their comorbidities. Realyze helps them find specific patients and intervene at the correct time with the correct treatment,” said Aaron Brauser, Realyze president and chief executive officer. “This can improve a patient’s overall health while hospitals benefit from avoidance of unplanned events and reduction of abstraction costs.”
Founded in 2020, Realyze is being used at UPMC for improving patient care, extending analytics capabilities, and supporting clinical research. In an analysis of more than 100,000 CKD patients at UPMC, Realyze enhanced the work done by UPMC’s clinical analytics team by deriving new insights from clinical notes that were not available in the structured data. With this information, UPMC will improve its ability to implement more precise patient segmentation, which, in turn, will allow clinicians to better deploy resources for more appropriate care.
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