advanced terminology systems ppt
TRANSCRIPT
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Advanced Terminology
SystemsMaryelle Grace Joy M. Samson
Angeliness IldefonsoCatherine Mangulabnan
Rowel Ian GuillermoPaulo Gabrielle Malijan
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Primary motivation: the need for valid, comparable data that can be used across information system applications to support clinical decision-making and the evaluation of processes and outcomes of care.
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Vocabulary problem
• failure to achieve a single, integrated terminology with broad coverage of the healthcare domain
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Reasons for Vocabulary Problem:
1) Multiple specialized terminologies has resulted to overlapping content, areas of which no content exists, and large numbers of codes and terms.
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2) Existing terminologies are primarily intended for human interpretation, with computer interpretation as only a secondary role.
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Concept Orientation
• In order to appreciate the significance of concept-oriented approaches, it is important to first understand the definitions of and relationships among objects, concepts and the terms we use.
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Semiotic Triangle
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ISO 1087-1:2000
• Concept – unit of knowledge created by a unique combination of characteristics.
*characteristic is an abstraction of a property of an object of a set of objects.
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• Object – anything perceivable or conceivable.
• Term – verbal designation of a general concept in a specific subject field.
*general concept corresponds to two or more objects which form a group by reason of common properties.
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Evaluation Criteria related to Concept-oriented
Approaches
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• Atomic-based – concepts must be separable into constituent components.
• Compositionality – ability to combine simple concepts into composed concepts
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• Concept permanence – once a concept is defined it should not be deleted from a terminology.
• Language independence – support for multiple linguistic expressions.
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• Multiple hierarchy – accessibility of concepts through all reasonable hierarchal paths with consistency of views.
• Nonambiguity – explicit definition for each term.
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• Nonredundancy – one preferred way of representing a concept or idea
• Synonymy – support for synonyms and consistent mapping of synonyms within and among terminologies
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A single concept may be associated with multiple terms, but a term should represent only one concept.
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Components of AdvancedTerminology Systems
• Terminology Model • Representation Language• Computer-Based Tools
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Terminology Model
• a concept-based representation of a collection of domain-specific terms that is optimized for the management of terminological definitions.
• It encompasses both schemata and type definitions.
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Schemata• incorporate domain-specific
knowledge about the typical constellations of entities, attributes, and events in the real world and, as such, reflect plausible combinations of concepts.
• Ex. “dyspnea” + “severe” = “severe dyspnea”
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Type Definitions
• obligatory conditions that state only the essential properties of a concept.
• Ex. A nursing activity must have a recipient, an action, and a target.
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Representation Language
• GALEN Representation and Integration Language (GRAIL)
• Knowledge Representation Specification Syntax (KRSS)
• Web Ontology Language (OWL)
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Ontology Language
• Represents classes and their properties
• Able to support the formal definition of concepts in terms of their relationships with other concepts, and facilitate reasoning about those concepts
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Computer-Based Tools
• A representation language may be implemented using description logic within a software system or by a suite of software tools.
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Classifications of Terminology Systems
• First-generation terminology systems
• Second-generation terminology systems
• Third-generation systems
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First-generation terminology systems
• consist of a list of enumerated terms, possibly arranged as a single hierarchy.
• Serve a single purpose or a group of closely related purposes and allow minimal computer processing
• NANDA, Nursing Interventions Classification (NIC)
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Nursing Interventions Classification (NIC)
• a comprehensive, standardized system to classify treatments performed by nurses.
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North American Nursing Diagnosis Association (NANDA)
professional organization of nurses standardized nursing terminology that develops, researches, disseminates and refines the nomenclature, criteria, and taxonomy of nursing diagnoses.
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Second-generation terminology systems
• include an abstract terminology model or terminology model schema that describes the organization of the main categories used in a particular terminology or set of terminologies.
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• Can be used for a range of purposes, but they allow only limited computer processing; automatic classification of composed concepts is not possible
• Beta 2 version of the International Classification for Nursing Practice (ICNP)
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Abstract terminology model
• complemented by a thesaurus of elementary descriptors (terms) and templates or rules (grammar)
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Third-generation systems
• support sufficient formalisms to enable computer-based processing
• Include grammar that defines the rules for automated generation and classification of new concepts.
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Advantages of Advanced Terminology Systems
• Allow much greater granularity through controlled composition, while avoiding a combinatorial explosion of precoordinated terms.
• Facilitate two important facets of knowledge representation for computer-based systems that support clinical care
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Two important facets:
• Describing concepts• Manipulating and reasoning
about those concepts using computer-based tools
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Describing concepts
• Nonambiguous representation of concepts.
• Facilitation of data abstraction or de-abstraction without loss of original data.
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• Nonambiguous mapping of terminologies
• Data reuse in different contexts
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Manipulating and reasoning about those concepts using computer-based tools
• Automated classification of new concepts
• Ability to support multiple inheritance of defining characteristics
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Advanced Terminological Approaches in Nursing
• ISO 18104:2003• GALEN• SNOMED RT
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ISO 18104:2003
• Developed by ISO Technical Committee 215 (Health Informatics) Working Group 3 (Health Concept Representation) under the collaborative leadership of the International Medical Informatics Association – Nursing Special Interest Group (IMIA-NI) and the International Council of Nurses
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• Approved in 2003• Covers reference terminology
models for nursing diagnoses and nursing actions
• The model built on work origination within the European Committee for Standardization
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• Development was partly motivated by a desire to harmonize the plethora of nursing terminologies in use around the world
• Intended to be “consistent with the goals and objectives of other specific health terminology models in order to provide a more unified reference health model”
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Potential uses:• Facilitate the representation of
nursing diagnosis and nursing action concepts and their relationships in a manner suitable for computer processing
• Provide a framework for the generation of compositional expressions from atomic concepts within a reference terminology
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• Facilitate the mapping among nursing diagnosis and nursing action concepts from various terminologies
• Enable the systematic evaluation of terminologies and associated terminology models for purpose of harmonization
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• Provide a language to describe the structure of nursing diagnosis and nursing action concepts to enable appropriate integration with information models
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GALEN
• A concept-oriented approach developed within the GALEN Program
• Used in a range of ways, from directly supporting clinical applications to supporting the authoring, maintenance, and quality assurance of other kinds of terminologies
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• GRAIL is an ontology language for representing concepts and their interrelationships – the source material for construction of terminology models.
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Two sets of tools used in development of GRAIL Model:
• Computer-based modeling environment
• Terminology server
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Computer-based modeling environment
• Facilitates the collaborative formulation of models
• Allows authoring of clinical knowledge at different levels of abstraction
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Terminology server• a software system that implements
GRAIL• A major motivation for applying
GALEN to nursing was the desire to meet the requirements of users of clinical applications, and the need to provide a reusable and extensible model of nursing terminology
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GALEN advocates five fundamental paradigm shifts:
• user interface• structure• establishing
standards• presentation• delivery
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In the user interface
• to shift from selecting codes to describing conditions
• allow a central concept to be described through simple forms.
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In the structure
• to shift from enumerated codes to composite descriptions
• terminologies are internally analogously to a dictionary and a grammar
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• traditional coding systems are more like a phrase book; each sentence must be listed separately.
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In establishing standards
• to shift from a standard coding system to a standard reference model.
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GALEN Common Reference Model
• provides a common means of representing coding and classification systems so that they can be inter-related - a common dictionary and grammar.
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In delivery• to shift from static coding
systems as data to dynamic terminology services as software.
• GALEN originated the idea of a terminology server and is participating actively in the CorbaMed effort at standardizing the software interface.
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In presentation
• to shift from translations of monolingual terminologies to multilingual terminologies.
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Functions of GALEN:
• Internally managing and representing the mode
• Testing the validity of combinations of concepts
• Constructing valid composed concepts
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• Transforming composed concepts into canonical form
• Automatically classifying composed concepts into the hierarchy
• Deliver the model for use by clinical applications and other kinds of authoring environments
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SNOMED Reference Technology (SNOMED RT)
• An alternative concept-oriented approach; developed through the collaboration between the College of American Pathologists and Kaiser Permanente, based on SNOMED International.
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• Is a reference terminology optimized for clinical data retrieval and analysis
• Concepts and relationships are represented using modified KRSS rather than GRAIL
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Functions of SNOMED RT:• Acronym resolution, word
completion, term completion, spelling correction, display of the authoritative form of the term entered by the user, and decomposition of unrecognized input
• Automated classification• Conflict management, detection,
and resolution
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SNOMED Clinical Terms (SNOMED CT)
• Developed by College of American Pathologists and UK National Health Service
• Possesses both reference terminology properties and user interface terms.
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Emerging Approaches
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Web Ontology Language (OWL)
• intended for use where applications, not humans, are to process information.
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OWL builds on existing recommendations such as:
• eXtensible Markup Language (XML) – surface syntax for structured documents
• Resource Description Framework (RDF) – a data model for resources
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• RDF Schema – a vocabulary for describing the properties and classes of resources
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IMPLICATIONS FOR NURSING
• Provide for nonambiguous concept definitions
• Facilitate composition of complex concepts from more primitive concepts
• Support mapping among terminologies.
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Benefits of clinical approach:
• Facilitation of evidence-based practice
• Matching of potential research subjects to research protocols for which they are potentially eligible.
• Detection of and prevention of potential adverse drug effects
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• Linking online information resources
• Increased reliability and validity of data for quality evaluation
• Data mining for purposes such as clinical research, health services research, or knowledge discovery.
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