Description

SNOMED CT is being used to define evaluation criteria for concept-based rule logic and understand potential use cases for the derivation of actionable clinical insights through alerts/reminders, cohort identification, and clinical documentation improvement.

The ability to understand clinical context for patients and populations rests on our understanding of clinical terminology in a variety of health information systems. SNOMED CT is foundational to our terminology infrastructure that enables both real-time concept detection from free text as well as real-time computation against clinical data sources in a way that adds value to an existing body of knowledge.

The following are use cases for this approach:
  • Detection of clinical concepts in unstructured text and conversion to SNOMED CT
  • Alerting of evidence-based interventions in EHR workflows that reduce mortality, readmissions, and cost
  • Identification of patient cohorts to clinical trial enrolment
  • Detection of undocumented diagnoses to improve clinical documentation and to complement population health efforts
Location: Okehampton, United Kingdom 

Scope

  • Cohort
  • Clinical Trial Recruitment Detection
  • Undocumented DM1, DM2, Gestational DM Genomics
  • Clopidogrel Metabolism and CYP2C19 Gene Quality
  • Heart Failure
  • Aldosterone Antagonists Calculation
  • CAP
  • Pneumonia Severity Index Monitoring
  • Diabetes Mellitus
  • HbA1c Safety
  • Beers Criteria
  • Unnecessary Care
  • Avoiding CK-MB (heart muscle damage test)
  • Testing for Acute Coronary Syndrome
  • And Countless Others…

How SNOMED CT will be used

SNOMED CT is being used to support the following:
  • Enabling guideline and decision support systems to provide real-time advice
  • Enhancing audits of care delivery
  • Allowing accurate and comprehensive searches that identify patients
  • Enhancing audits of care delivery
  • Reducing costs of inappropriate and duplicative testing and treatment
  • Raising the cost-effectiveness and quality of care

Why SNOMED CT was selected

SNOMED CT was chosen due to its ontological basis allowing leveraging of computer-based assertions to support inferencing within decision-support systems.

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