Insight and Meaning from Darkness
The Clinical Semantic Network (CSN) dramatically increases the volume of well-formed clinical data available to providers, value-based organizations, and payers leading to improved (and more collaborative) outcomes through clinical decision support, care coordination, dynamic member engagement and financial performance.
To derive understanding of population cohorts, healthcare delivery organizations primarily focus on the available “limited” structured data, i.e. claims, labs, medications, etc. but are not able to tap the “dark matter” trapped in the other 80%, classified as unstructured text. Many tools are available to derive some key words from text data but few, if any, are able to liberate clinical meaning from that data.
Our Solutions, driven by the CSN and the genomics capabilities of our sister company MolecularDx, provide for deeper health and medical understanding of individuals desperately needed by Provider and Payer organizations alike.
At Goldblatt Systems, we believe that moving to more comprehensive, data-driven population health requires an engine that creates structured clinical data and untangles unstructured data by mapping it using clinical semantics. Making this happen can add true, well-formed clinical information resulting in:
- Clinical documentation created and aggregated as structured medical information
- Volumetric increase in medical knowledge of members/patients
- Early identification of co-morbidities from ordinary engagement (i.e. case management)
- Increased accuracy in health risk stratification
- Preventive and more effective coordination of care
Medical semantic information that is structured (vs. unstructured text) and leads to better healthcare. However, when data is not structured and lives across multiple providers and institutions, it loses meaning, especially when it is exchanged. Health information exchanged as text data often lacks the semantics to allow for swift or machine-based interpretation. The CSN transforms all form of medical information into meaningful, computable health information.