While most healthcare analytics tools only look at broad categories of cost versus outcomes, we break clinical data down into unique cohorts that account for variables in patient type, surgical technique, and other mitigating factors to make a true "red apples to red apples" comparison for identifying unwarranted clinical variation. We have developed more than 360+ individual cohorts.
Rooted in existing cohorts, our AI-driven platform identifies variance by scanning and capturing thousands of data points from a variety of sources, including operative notes. Using Natural Language Processing (NLP) with 98% accuracy, our machine learning technology can quickly identify and pull pertinent data that would take significant time if done manually. This advanced technology allows us to identify meaningful variation in cost and clinical outcomes, determine reasons behind the variation and make recommendations to physicians and administrators based on the output.
The Empiric Analytics Suite takes the noise out of the data, returning scrubbed and accurate information that surgeons can trust. An internal feedback loop with clinically-experienced consultants further ensures that the information is both accurate and relevant.
The Empiric Analytics Suite makes complex reporting simple, using intuitive charts, graphs and pertinent details that nurses, surgeons and administrators can all easily and quickly digest — making conversations productive, and recommendations easily actionable.
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