SNOMED CT Analytics using Microsoft Fabric
The increasing volume of data and variations in terminology, language and abbreviations within clinical documents pose significant challenges for medical professionals when it comes to extracting relevant information. Also, the use of various clinical terminologies led to data inconsistency and made it challenging to provide consistent decision support. These challenges not only lead to discrepancies in data interpretation but also result in substantial costs, time constraints, and a drain on your highly skilled personnel. This, in turn, hampers their capacity to concentrate on other vital aspects of clinical care.
Clinical Natural Language Processing (NLP) and Deep Learning techniques to analyze unstructured clinical data, extracting insights from free-text information. These methods leverage SNOMED CT as a resource to process and interpret medical information for more accurate analysis and understanding.
Solution leveraging Microsoft Fabric for extracting valuable insights from unstructured free-text information and encoding with SNOMED CT for standardized clinical terminologies.
SNOMED CT Analytics using Microsoft Fabric
Taliun has developed a solution that empowers the analysis of healthcare data extracted directly from clinical narratives or free text. This technology is adaptable for integration into current healthcare solutions and can process pertinent free text, converting crucial clinical components such as medications, diagnoses, procedures, symptoms, and findings into SNOMED CT-encoded data. Users can then employ customizable SNOMED CT queries to retrieve structured data, making it readily accessible facilitate analytics and querying of patient data encoded in SNOMED CT through Microsoft Fabric. The analytics can be carried out for clinical assessment and treatment; population monitoring; and Research.
Healthcare and Clinical Analytics using Microsoft Fabric
(Descriptive Analytics, Predictive Analytics, Prescriptive Analytics)
Taliun has built the solution for implementation of advanced healthcare analytics with Microsoft Fabric which aims to elevate patient outcomes and safety, streamline operational efficiency, enhance resource allocation and management, identify high-risk patients for proactive preventive care, and ensure compliance with regulations while maintaining stringent quality standards.
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