Upload
minette-din
View
201
Download
2
Tags:
Embed Size (px)
Citation preview
Chapter 18: Advanced Terminology Systems
By: Minette DinBSN-2A
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
Vocabulary problem
Failure to achieve a single, integrated terminology with broad coverage of the healthcare domain
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.2.) Existing terminologies are primarily intended for human interpretation, with computer interpretation as only a secondary role.
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.
Semiotic Triangle
Thought or Reference
Sym
boliz
es
Refers
to
Symbol Stands for SUN
SOLEIL
REFERENT
The semiotic triangle depicts the relationships among objects in the perceivable and conceivable world (referent), thoughts about things in the world, and the labels (symbols of terms) used to represent thoughts about things in the world
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.Object- anything perceivable or
conceivable.Term- verbal designation of a general
concept in specific subject field. *general concept corresponds to two or more objects which form a group by reason of common properties.
Evaluation Criteria related to Concept-oriented Approaches
Atomic-based – concepts must be seperable into constituent components.
compositionality – ablity to combine simple concepts into composed concepts
Concept permanence – once a concept is defined it should not be deleted from a terminology
Language independence – support for multiple linguistic expressions.
Multiple hierarchy – accessibility of concepts through all reasonable hierarchal paths with consistency of views.
Nonambiguity – explicit definition for each term.
Nonredundancy – one preferred way of representing a concept or idea
Synonymy support for synonyms and consistent mapping of synonyms within and among terminologies
A single concept may be associated with multiple terms, but a term should represent only one concept.
Components of Advanced Terminology Systems
• Terminology Model• Representation Language• Computer-Based Tools
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.
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”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.
Schemata
Representation Language
GALEN Representation and Integration Language (GRAIL)
Knowledge Representation Specification Syntax (KRSS)
Web Ontology Language (OWL)
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
Computer-Based tools
A representation language may be implemented using descriptin logic within a software system or by a suite of software tools.
Classifications of Terminology systems
First-generation terminology systemsSecond-generation terminology
systemsThird-generation systems
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)
Nursing Interventions Classification (NIC)
A comprehensive, standardized system to classify treatments performed by nurses
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.
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.
Can be used for a range of purposes, but they allow limited computer processing; automatic classification of composed concepts is not possible
Beta 2 version of the International Classification for Nursing Practice (ICNP)
Abstract terminology model
Complemented by a thesaurus of elementary descriptors (terms) and templates or rules (grammar)
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.
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
Two important facets:
Describing conceptsManipulating and reasoning about
those concepts using computer-based tools
Describing concepts
• Nonambiguous representation of concepts
• Facilitation of data abstraction or de-abstraction without loss of original data.
• Nonambiguous mapping of terminologies
• Data reuse in different contexts
Manipulating and reasoning about those concepts using
computer-based tools
Automated classification of new concepts
Ability to support multiple inheritance of defining characterictics
Advanced terminological approaches in Nursing
• ISO 18104:2003• GALEN• SNOMED RT
ISO 18104:2003
Developed by ISO Technical Committee 215 (health informatics) working Gorup 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
Approved in 2003Covers reference terminology model for
nursing diagnoses and nursing actions
The model built on work origination within the European Committee for Standardization
Development was partly motivared 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”
Potential uses:
Facilitate nursing representation of nursinh diagnosis and nursing action concept 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
Facilitate the mapping among nursing diagnosis and nursing action concepts from various action
Enable the systematic evolution of terminologies and associated terminology models for purpose of harmonization
Provide a language to describe the structure of nursing diagnosis and nursing action concepts to enable appropriate integration with information models
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
GRAIL is an ontology language for representing concepts and their interrelationships – the source material for construction of terminology models
Two sets of tools used in development of GRAIL Model:
• Computer-based modeling environment
• Terminology server
Computer-based modeling environment
• Facilitates the collaborative formulation of models
• Allows authoring of clinical knowledge at different levels of abstraction
Terminology server
A software systems that implements GRAIL
A major motivation for applying GALEN to nursing was the desire to meet the requirements of users of clinical application, and the need to provide a reusable and extensible model of nursing terminology
GALEN advocates 5 fundamental paradigm shifts:
• User interface• Structure• Establishing standards• Presentation• Delivery
The user interface
• To shift from selecting codes to describing conditions
• Allow a central concept to be described through simple forms.
In the structure
To shift from enumerated codes to composite descriptions
Terminologies are internally analogouslt to a dictionary and a grammar
Traditional coding systems are more like a phrase book; each sentencs must be listed separately
In establishing standards
To shift from a standard coding system to a standard reference model
GALEN Common Reference Model
Provides a common means of representing coding and classification systems so that they can be interrelated – a common dictionary and grammar
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
In presentation
To shift from translations of monolingual terminologies to multilingual terminologies
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
Deliver the model for use by clinical applications and other kinds of authoring environments
SNOMED Reference Technology (SNOMED RT)
An alternative concept- oriented approach; developed through the collaboration between the College of American Pathologist and Kaiser Permanent, based on SNOMED International.
Is a reference terminology optimized for clinical data retrieval and analysis
Concepts and relationships are represented using modified KRSS rather than GRAIL
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 classificationConflict management, detection, and
resolution
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.
Emerging Approaches
Web Ontology Language (OWL)
Intended for use where applications, not humans, are to process information
OWL builds on existing recommendations such as: *eXtensible Markup Language (XML) – surface syntax for structures documents
* Resource Description Framework (RFD) – a data model for resources
* RDF Schema – a vocabulary for describing the properties and classes of resources
Implication for Nursing
Provide for nonambiguous concept definitions
Facilitate composition of complex concepts from more primitive concepts
Support mapping among terminologies
Benefits of Clinical Approach:
Facilitation of evidence-based practiceMatching of potential research subjects
to research protocols for which they are potentially eligible.
Detection of and prevention of potential adverse drug effects
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.
ENDTHE
END