This revised new edition containing numerous new and heavily updated chapters provides readers with the essential information needed to understand the central topics of terminology in healthcare, the understanding of which is an asset to be leveraged in care and research. Twenty-five years ago the notion that terminology should be concept-based was all but unknown in healthcare; now almost all important terminologies are at least partly concept-based. With no general model of what a terminology was or should be, there were no tools to support terminology development and maintenance. Steady progress since then has improved both terminology content and the technology and processes used to sustain that content. This new edition uses real world examples from the health sector to delineate the principal issues and solutions for the field of data representation. It includes a history of terminologies and in particular their use in healthcare, including inter-enterprise clinical andresearch data aggregation.
Terminology, Ontology and their Implementations covers the basis, authoring and use of ontologies and reference terminologies including the formalisms needed to use them safely. The editor and his team of carefully chosen contributors exhaustively reviews the field of concept-based indexing and provides readers with an understanding of natural language processing and its application to health terminologies. The book discusses terminology services and the architecture for terminological servers and consequently serves as the basis for study for all students of health informatics.
Section 1: Introduction to Core Concepts.- Introduction.- History of Terminology and Ontology.- Knowledge Representation and the Logical Basis of Ontology.- Theoretical Foundations of Terminology.- Terminology Requirements and Standards Development.- Terminology Design.- Maintenance.- Quality Control.- Section 2: Realist Ontology.- Realism Based Ontology.- What is an ontology?.- Ontology vs. terminology.- Ontology vs. taxonomy.- Ontologies and databases.- Ontology and the Semantic Web.- Ontology in biomedical informatics.- Bad ontologies.- The concept orientation.- Why ontologies so often fail.- Recipes for success.- Examples of successful ontologies and of how they are being used.- The place of Referent Tracking in Biomedical Informatics.- Introduction: what is Referent Tracking (RT)? How does it relate to ontology? What does it aim to achieve? Why does it matter?.- Basic principles: how RT is build on top of three important distinctions made in realism-basedontology: particulars types, continuants occurrents, referents references.- Syntax and semantics of RT-expressions.- RT as a development tool for ontologies.- Using RT to detect and prevent flaws in scientific research and ambiguities and inconsistencies in reports and papers.- RT as a solution for semantic interoperability.- Werner Ceusters.- Bioontology in Service of Translational Science.- Introduction to Bioontologies and the OBO Foundry.- The Gene Ontology.- Overview of GO Content and Structure.- GO annotation.- Term Enrichment/Pathway Analysis.- Success Stories.- Challenges.- Bioontologies and Data Annotation Systems.- ImmPort/HIPC.- Kidney Precision Medicine Project.- GEO and Array Express.- Disease and Phenotype Annotation for Translational Studies.- Use of Ontologies at Mouse Genome Informatics.- HPO and the Monarch Project.- Compositionality: An Implementation Guide.- Section 3: Terminologies and their Implementation.- Interface Terminologies.- SNOMED CT.- RxNorm andNDF-RT and ATC codes.- LOINC.- SOLOR.- ICD.- CPT.- HCC Codes / Risk Adjustment and MACRA / MIPS.- DRGs.- NCI EVS.- Nursing Terminologies.- RED / MED.- UMLS Metathesauras and knowledge sources.- Section 4: Terminology Services, APIs and Methods.- Terminological Systems.- HL7 FHIR and APIs.- Section 5: Summing it All Up.- Lessons Learned and Suggested Research Agenda.- The future of coding and coding systems.- Conclusion.
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