overview of cpr ontology
DESCRIPTION
An overview of the methods behind the CPR ontology, its motivation, and contentTRANSCRIPT
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Overview of CPR Ontology
Chime OgbujiCleveland Clinic Foundation
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What is a CPR?
Computer-based Patient Record (CPR): An electronic patient record that resides in a system specifically designed to support users by providing accessibility to complete and accurate data, alerts, reminders, clinical decision support systems, links to medical knowledge, and other aids.
- Institute of Medicine (IOM) 1997
Defines medical records systems of the future and theimportant features that distinguish them for EHRs of 1997
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What is the CPR Ontology?
● Addresses terminology requirements of a CPR● IOM defines a set of requirements for CPR
systems regarding record content – Uniform, core data elements
– Standardized coding systems and formats
– A common data dictionary
– Information on outcomes of care and functional
status
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What is the CPR Ontology?
● Defines a minimal set of terms ● Provide principled, ontological commitment for
the terms used in many of the healthcare information terminology systems
● Relies on the use of foundational ontologies and ontology engineering best practices.
● An upper ontology of clinical medicine– Similar motivation as OGMS
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CPR Ontology goals
● In order to achieve uniformity, it needs to have significant coverage
– Pyramid ontology paradigm: small, well-organized top; wide, idiosyncratic bottom.
● Adopt cogent conceptual models that appeal to an ontological study of clinical medicine
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Reinventing the Wheel?
● Why not re-use GALEN?
– Dated and deprecated● Why not re-use SNOMED-CT?
– Licensing issues and lack of ontological grounding (it lies in towards the bottom of the pyramid)
– Issues with inconsistent and incomplete definitions
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Framework
● BFO– Domain-independent upper ontology
● BioTop– Integrating foundation for both clinical medicine
and the life sciences
● CPR – Clinical medicine: study of medicine based on
direct observation of patients
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Role of BioTop
● A “mediating layer for the life sciences domain”● Proposed as a candidate upper ontology for
SNOMED-CT (covers health care as well)● Coverage of biology and biomedicine at various
levels of granularity● Bridge between formal, upper ontologies and
domain-specific ontologies
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BioTop Coverage
● Supports integration of:– Gene Ontology
– Cell Ontology
– Chemical Entities of Biological Interest
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BioTop's Range of Granularity
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Method(s) behind the Madness
● Realist ontologies (BFO-based)● Situations, findings, & observables (Rector
2008)● Surgical procedures (GALEN)● Representational artifacts v.s. their referents
(Vizeno 2007)● Problems and screenings (Weed 1968)
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Method(s) behind the Madness
● Care act hierarchy and clinical workflow (Bayegan 2002)
● Disease, diagnosis, etiology and the Disease Entity Model (Whitbeck 1977)
● Disease, diagnosis, bodily features, etc. (Scheuermann et al. 2009)
● Integrating anatomy, physiology, and pathology (Rosse et al. 2005)
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General Rules of Thumb
● Use realist ontology approach to the extent that distinctions are useful for real-world clinical informatics problems
– Avoid reductionism trap
● Validate against data and standard, controlled-vocabularies
– Patient data and SNOMED-CT primarily
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Patient Care Activity Hierarchy
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Clinical Findings
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Diseases and Their Manifestations
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Signs and Their Recordings
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Clinical Investigations and Diagnoses
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Validating CPR
● Validated against local controlled vocabulary– Terms used in large, RDF-based HVI patient
registry (200,000+ patients) for outcomes research
– 4051 OWL classes
– Systematically attempted to find a principled location for each class
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Validating CPR
● Validated against SNOMED-CT and FMA extracts
– Recent research on aligning both ontologies and extracting segments from them
– Developed software to perform extraction and place segments within CPR/BioTop/BFO framework
● Opportunity to validate against TMO dataset