Advanced terminologies

• Primary motivation for advanced terminology systems:

  • Need for valid, comparable data across information system applications to support clinical decision-making and care outcomes evaluation
• Vocabulary problem in healthcare terminology:

  • Failure to achieve a single, integrated terminology with broad coverage due to multiple specialized terminologies resulting in overlapping content, areas with no content, and large numbers of codes and terms
• Reasons for vocabulary problem:

  • Overlapping content due to multiple specialized terminologies
  • Areas with no content
  • Large numbers of codes and terms
• Concept Orientation importance:

  • Understanding definitions and relationships among objects, concepts, and terms used
• Semiotic Triangle:

  • Depicts relationships among objects (referent), thoughts, and labels (symbols or terms) used to represent thoughts
• Concept:

  • Unit of knowledge created by a unique combination of characteristics
• Characteristic:

  • Abstraction of a property of an object or set of objects
• Object:

  • Anything perceivable or conceivable
• Term:

  • Verbal designation of a general concept in a specific subject field
• Evaluation Criteria for Concept-oriented Approaches:

  • Atomic-based concepts
  • Compositionality
  • Concept permanence
  • Language independence
  • Multiple hierarchy
  • Nonambiguity
  • Nonredundancy
  • Synonymy
• Components of Advanced Terminology Systems:

  • Terminology Model: concept-based representation of domain-specific terms
  • Type Definitions: obligatory conditions stating essential properties of a concept
  • Representation Language: GALEN Representation and Integration Language (GRAIL), Knowledge Representation Specification Syntax (KRSS), Web Ontology Language (OWL)
  • Ontology Language: represents classes and properties, supports formal definition and reasoning
  • Computer-based tools: implement representation language using descriptive logic
• Classifications of Terminology Systems:

  • First-generation: list of enumerated terms, minimal computer processing
  • Second-generation: abstract terminology model, limited computer processing
  • Third-generation: formalisms for computer-based processing
• Advantages of Advanced Terminology Systems:

  • Greater granularity through controlled composition
  • Facilitation of knowledge representation and reasoning in computer-based systems
• Advanced Terminological Approaches in Nursing:

  • ISO18104:2003 developed by ISO Technical Committee 215 (health informatics) working Group 3 (health concept representation) under the collaborative leadership of IMIA-NI and the International Council of Nurses
  • Approved in 2003
  • Covers reference terminology model for nursing diagnoses and nursing actions
  • Built on work originating within the European Committee for Standardization
  • Motivated by a desire to harmonize nursing terminologies globally
• Potential uses of ISO18104:2003:

  • Facilitate nursing representation of nursing diagnosis and nursing action concepts
  • Provide a framework for generating compositional expressions from atomic concepts
  • Facilitate mapping among nursing diagnosis and nursing action concepts
  • Enable systematic evolution of terminologies for harmonization
  • Describe the structure of nursing diagnosis and nursing action concepts for integration with information models
• GALEN:

  • Concept-oriented approach developed within the GALEN Program
  • Utilized for supporting clinical applications, authoring, maintenance, and quality assurance of terminologies
  • GRAIL is an ontology language for representing concepts and their interrelationships
• Tools used in the development of the GRAIL Model:

  • Computer-based modeling environment for collaborative formulation of models
  • Terminology server software system implementing GRAIL
• GALEN advocates 5 fundamental paradigm shifts:

  • User interface shift from selecting codes to describing conditions
  • Structure shift from enumerated codes to composite descriptions
  • Standards shift from a standard coding system to a standard reference model
  • Presentation shift from monolingual to multilingual terminologies
  • Delivery shift from static coding systems to dynamic terminology services
• Function of GALEN:

  • Internally managing and representing the mode
  • Testing the validity of combinations of concepts
  • Constructing valid composed concepts
  • Transforming composed concepts into canonical form
  • Automatically classifying composed concepts into the hierarchy
  • Delivering the model for use by clinical applications and authoring environments
• SNOMED Reference Technology (SNOMED RT):

  • Concept-oriented approach optimized for clinical data retrieval and analysis
  • Represents concepts and relationships using modified KRSS
• Functions of SNOMED RT:

  • Acronym resolution, word completion, term completion, spelling correction
  • Automated classification
  • Conflict management, detection, and resolution
• SNOMED Clinical Terms (SNOMED CT):

  • Developed by College of American Pathologists and UK National Health Service
  • Possesses reference terminology properties and user interface terms
• Web Ontology Language (OWL):

  • Intended for applications to process information
  • Builds on existing recommendations like XML, RDF, and RDF Schema
• Implications for Nursing:

  • Provide nonambiguous concept definitions
  • Facilitate composition of complex concepts
  • Support mapping among terminologies
• Benefits of Clinical Approach:

  • Facilitation of evidence-based practice
  • Matching research subjects to protocols
  • Detection and prevention of adverse drug effects
  • Linking online information resources
  • Increased reliability and validity of data
  • Data mining for clinical research and knowledge discovery