Chapter 18 advanced terminology systems

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

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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.

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