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Consistent and standardized common model to support large-scale vocabulary use and adoption Robust, scalable, and common API to reduce variation in clinical.

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Presentation on theme: "Consistent and standardized common model to support large-scale vocabulary use and adoption Robust, scalable, and common API to reduce variation in clinical."— Presentation transcript:

1 Consistent and standardized common model to support large-scale vocabulary use and adoption Robust, scalable, and common API to reduce variation in clinical description attributable to interface dependencies HL7 ANSI and ISO Standard Collection of programmable interfaces to access controlled terminologies and ontologies Supports deferred query resolution, payload optimization, defining and querying value sets Provides HL7 CTS 2 interface (future) PGRN Ontology Network Resource Jyotishman Pathak, PhD Robert R. Freimuth, PhD Christopher G. Chute, MD, DrPH Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN Background and Aims Data sharing requires transformation of clinical data into comparable consistent formats In practice, clinical data and provider information is unstructured and non-standard Overall Aim: Develop an open-source, dynamically configurable services framework for standards-conforming, comparable, and consistent phenotypic data representation Specific Aims: Adapt LexEVS as terminology/ontology infrastructure for PGRN Establish globally available resource for biomedical ontologies and value sets relevant to PGRN Develop infrastructure for phenotype representation referencing LexEVS Act as intermediary between PGRN investigators and standards bodies Ontologies provide a formal specification of how to represent objects, concepts, and relationships among them Ontologies can be used for: Naming “things” (annotation) Modeling a domain of interest Computational reasoning over data Driving Natural Language Processing Semantic information integration Ontologies in the biomedical domain: Genotype: Gene Ontology Diseases/Findings: SNOMED-CT, ICD Laboratory Measurements: LOINC Drugs: RxNorm, NDF-RT Domain-Specific: NCI Thesaurus, RadLex Multiple representations available: Open Biomedical Ontologies (OBO) Web Ontology Language (OWL) Rich Release Format (RRF) Clinical Data Normalization Personnel Value Sets Creation and Querying Enterprise Vocabulary Services (EVS) LexEVS Infrastructure Standardized Phenotype Representation Biomedical Ontologies Value Set Definition with in the LexGrid logical model defines the contents of Value Set Possible forms of Value Set Definitions Containing just the reference to Code System Containing just the reference to other Value Set Includes all the concept codes defined in the referencing Value Set Definition Reference to Code System plus concept codes, optionally with relationship plus additional rules Includes concept codes from the referencing code system that satisfies the rule set defined in the definition Combinations Value Set services provided by EVS Load, Create, Remove, Modify List all the Value Set Definitions loaded in the system Dynamically resolve Value Set Definition Check if one Value Set is sub set of other Value Set Check if a concept code is part of given Value Set Value Set Definition: Find the SNOMED-CT term GLIOMA and its immediate children, remove the root node Value Set Demo Example Study PhenX templates on consensus measures for phenotypes and environmental exposures Investigate HL7 and ISO templates and archetypes for disease or observation description Apply natural language processing techniques where applicable for phenotype extraction and representation Christopher G. Chute Robert R. Freimuth Jyotishman Pathak Lexical Grid Project (LexGrid)


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