Patient risk assessment for a leading RCA provider
Overview.
This solution focuses on developing a robust patient risk assessment solution for a leading Root Cause Analysis (RCA) provider. Currently, RCA investigations are often initiated after an adverse event has occurred. This reactive approach limits opportunities for prevention. Our solution leverages advanced analytics to assess patient risk proactively.
Healthcare institutions face significant financial penalties and resource drains due to adverse events.
Adverse events can severely damage a healthcare institution's reputation, leading to patient loss and decreased trust.
Traditional RCA, conducted after an event, may not fully identify underlying causes or prevent future occurrence
Solution.
This solution utilizes Graph AI to predict the likelihood of patients developing specific illnesses or experiencing side effects from medications. It goes beyond traditional methods that analyze individual patient attributes in isolation.
Builds a knowledge graph that connects patients to their attributes and other relevant entities, such as medications, diagnoses, and other patients with similar profiles.
This allows the model to analyze not only individual attributes but also how they interact and influence each other.
Considers factors like:
mDirect connections: How specific medications interact with a patient's existing conditions or genetic predispositions.
Proximity: How patients with similar profiles experienced specific illnesses or side effects, even if they don't share all the same attributes.
The Impact.
Improved accuracy Enhanced transparency Identification of hidden risks Personalized medicines
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