A Semantic-Web Representation of Clinical Element Models
Cui Tao, PhD Mayo Clinic
Acknowledgement Christopher G. Chute, MD, DrPH Robert R. Freimuth, PhD Stanley M. Huff, MD Guoqian Jiang, PhD Thomas A. Oniki, PhD Jyotishman Pathak, PhD Craig Parker, MD Deepak Sharma Feichen Shen Sridhar D. Yadav Qian Zhu, PhD
SHARPn
Normalized EHR
EHR
Database CEM
OWL
Triple Store
XML
drools
SWRLdrools
XML Schema
Database
Schema
IntroductionClinical Element Model (CEM):
Logical models ensure semantic interoperability for: Data representation Data interpretation Data exchange within and across heterogeneous
sources and applications Represented in CEML/CDL (Constraint Definition
Language) Define syntax and grammar Not semantics
IntroductionSemantic Web
Explicit and formal semantic knowledge representation
Web Ontology Language (OWL) /Resource Description Framework (RDF): Define relationships Define classes Define constraints
Consistency checking Link to other domain terminologies Harmonize with other clinical data modeling
languages Semantic reasoning
Layer1:meta-ontology
Layer2: detailed clinical element models
Layer3:patient instances
Joe Doe’s recordJean Doe’s recordJoe Doe’s record
RDF Triple Store
Meta-CEM.OWL
Detailed Clinical Element Model Ontology
Semantic Reasoning Consistency checking
Cardinality constraints Data types Property allowed domains and ranges Permissible values in value sets
Classification and reasoning
Consistency Checking
Consistency Checking
Consistency Checking
Automatic ClassificationSemantic Definition of Normal DBP Data
Two DBP Measurements
Automatic ClassificationSemantic Definition of Normal BP
Infer that both exam1 and exam2 are within the normal range
Semantic Reasoning ExampleHas two outpatient (if possible) measurements
of SBP >140 or DBP > 90 at least one month after taking anti-hypertensive drugs.
Ontology:“Labetalol 100mg” (SCT318445000) is an anti-hypertensive drug (SCT1182007).
CNTRO temporal relation reasoner:5 weeks > one monthDuration (May 1 and March 1) > one month
Implementation Status Meta Ontology
Basic category classes Properties Cardinality constraints Two OWL experts and two CEM experts have
evaluated the meta-ontology to ensure it can faithfully cover the original contents
Automatic Convertor: detailed CEM ontologies
CEM-OWL convertorMeta-Ontology
Shared CEM Ontology
CEM Core Model Ontologies
CEM Secondary Use Ontologies
import
import
import
Download the ontologies Shared Models:
http://informatics.mayo.edu/sharp/CEM2OWL/CEM-Shared.owl
CORE Models:http://informatics.mayo.edu/sharp/CEM2OWL/COREModels/COREStandardLabObs.owlhttp://informatics.mayo.edu/sharp/CEM2OWL/COREModels/COREStandardLabObsCoded.owlhttp://informatics.mayo.edu/sharp/CEM2OWL/COREModels/COREStandardLabObsIntervalQuantitative.owl
http://informatics.mayo.edu/sharp/CEM2OWL/COREModels/COREStandardLabObsNarrative.owlhttp://informatics.mayo.edu/sharp/CEM2OWL/COREModels/COREStandardLabObsOrdinal.owlhttp://informatics.mayo.edu/sharp/CEM2OWL/COREModels/COREStandardLabObsQuantitative.owlhttp://informatics.mayo.edu/sharp/CEM2OWL/COREModels/COREPatient.owlhttp://informatics.mayo.edu/sharp/CEM2OWL/COREModels/CORENotedDrug.owlhttp://informatics.mayo.edu/sharp/CEM2OWL/COREModels/COREDiseaseDisorder.owl
Secondary Use: http://informatics.mayo.edu/sharp/CEM2OWL/SecondaryUse/SecondaryUseDiseaseDisorder.owlhttp://informatics.mayo.edu/sharp/CEM2OWL/SecondaryUse/SecondaryUseNotedDrug.owlhttp://informatics.mayo.edu/sharp/CEM2OWL/SecondaryUse/SecondaryUsePatient.owlhttp://informatics.mayo.edu/sharp/CEM2OWL/SecondaryUse/SecondaryUseStandardLabObsCoded.owl
http://informatics.mayo.edu/sharp/CEM2OWL/SecondaryUse/SecondaryUseStandardLabObsIntervalQuantitative.owl
http://informatics.mayo.edu/sharp/CEM2OWL/SecondaryUse/SecondaryUseStandardLabObsNarrative.owl
http://informatics.mayo.edu/sharp/CEM2OWL/SecondaryUse/SecondaryUseStandardLabObsOrdinal.owl
http://informatics.mayo.edu/sharp/CEM2OWL/SecondaryUse/SecondaryUseStandardLabObsQuantitative.owl
http://informatics.mayo.edu/sharp/CEM2OWL/SecondaryUse/SecondaryUseStandardLabObsTiter.owl
Conclusion and Future Directions Meta-Ontology: semantically defined the basic
classes, properties, their relationships, and constraints
Convertor: CDLOWL Represent SHARPn normalized data using RDF Investigate SWRL/Drools combination for
phenotyping
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