Dexur's AI Risk Factor Identification: Automatically See What Impacts Your Outcomes


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Healthcare organizations constantly endeavor to improve patient outcomes such as readmissions, mortalities, patient experience, and safety. Identifying risk factors that could impact quality outcomes is essential for enhancing hospital performance. Dexur's AI approach, which automatically identifies risk factors influencing your quality outcomes, represents a significant leap in its potential impact on quality measures.

The AI Advantage

At the heart of Dexur's solution lies a powerful AI engine that automatically sifts through vast data, examining all possible permutations and combinations of risk factors. For instance,traditional methods might only consider common factors when looking at heart failure readmissions. Dexur's AI, however, goes much deeper by exploring every conceivable risk element, from comorbidities like Diabetes and CKD to age and discharge status.

A practical example showcases its capabilities. Let's take Acme Hospital. Traditionally, it might report a heart failure readmission rate of 12%. But with Dexur's AI solution, it's shown that the number jumps to 20% if those heart failure patients also suffer from CKD. Such granular insights have enormous potential to direct patient care strategies and interventions.

Moreover, the report doesn’t just stop at identification. It provides an insightful comparison of these risk factors alongside incidence rates against state and national benchmarks. This paints a clear picture for hospitals on where they stand and the areas they need to focus on.

Three Reasons Dexur is Able to Deliver a Differentiated AI-Driven Risk Factor Identification

Dexur’s AI Risk Factor Identification solution represents a significant leap in pursuing hospital quality excellence. With its differentiated data and AI-driven approach, Hospitals can get automatic insights into what drives outcomes and the precise levers to fix problems.