RadWise CDS has its foundation in evidence-based medicine from published studies, often mediated by systematic reviews, then processed into medical algorithms for use in clinical practice. The flow of information is one way; from research to practice. However once these diagnostic procedures are performed, then their outcomes can be collected systematically becoming "practice-based evidence" and such aggregated data can complement that from medical research. Understanding this, Sage HMS has developed a new product Sage Ox to collect and aggregate CDS findings data from narrative reports, especially when using RadWise CDS.
Since Sage Ox is constructed on Natural Language Processing (NLP) and machine learning algorithms for filtering, it can be applied to narrative reports from various disciplines besides radiology, such as laboratory, cardiology, among others. Each discipline has its own algorithms to accurately predict the findings categories into Positive, Negative, or Equivocal. These data show patterns in clinical practice that can lead organizations to better strategies and better management of patient care and population health, resulting in more efficient processes and lower costs. In addition, these data can be used to support value-based reimbursement analyses and contracting.
Sage Ox utilizes algorithms developed through rigorous machine learning techniques to simplify unstructured patient narrative reports into accurate analyzable data. The accuracy of Sage Ox algorithms fall between 92%-95%. This level of accuracy is significantly better than the standard accuracy of 80%-85% from other similar NLP competitive products.
With the Sage Ox finding categories established for the unstructured reports, these new structured data can be used for predictive analytics, as well as to enhance patient care and to improve communication between providers. For example, when the specific finding categories are displayed with the narratives, the Ordering Provider can more easily manage the prioritization of narrative review and identify the findings that need special follow up for individual patients. In addition, such simplified information improves communication of the narratives between the performing provider and the ordering provider. This will reduce the risk of malpractice as each narrative has valuable, easily understood categories for both parties. Such easily useable data then has both implications for efficiencies and analytics.
Focused on predictive analytics, Sage Ox - especially when used with the prescriptive analytics of RadWise Clinical Decision Support (CDS):
Sage Ox can provide your organization analytics for quality measures in the new value-based reimbursement market and maximize your benefit and investment in RadWise CDS.
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