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PubMedDate not supplied

Clinical classification and terminology: some history and current observations.

The evolution of health terminology has undergone glacial transition over time, although this pace has quickened recently. After a long history of near neglect, unimaginative structure, and factitious development, health terminologies are in an era of unprecedented importance, sophistication, and collaboration. The major highlights of this history are reviewed, together with important intellectual advances in health terminology development. The inescapable conclusion is that we are amidst a major revolution in the role and capabilities of health terminologies, entering an age of large-scale systems for health concept representation with international implications.

Classification↗

PubMedDate not supplied

Evaluation of the quality of information retrieval of clinical findings from a computerized patient database using a semantic terminological model.

OBJECTIVES: To measure the strength of agreement between the concepts and records retrieved from a computerized patient database, in response to physician-derived questions, using a semantic terminological model for clinical findings with those concepts and records excerpted clinically by manual identification. The performance of the semantic terminological model is also compared with the more established retrieval methods of free-text search, ICD-10, and hierarchic retrieval. DESIGN: A clinical database (Diabeta) of 106,000 patient problem record entries containing 2,625 unique concepts in an clinical academic department was used to compare semantic, free-text, ICD-10, and hierarchic data retrieval against a gold standard in response to a battery of 47 clinical questions. MEASUREMENTS: The performance of concept and record retrieval expressed as mean detection rate, positive predictive value, Yates corrected and Mantel-Haenszel chi-squared values, and Cohen kappa value, with significance estimated using the Mann-Whitney test. RESULTS: The semantic terminological model used to retrieve clinically useful concepts from a patient database performed well and better than other methods, with a mean detection rate of 0.86, a positive predictive value of 0.96, a Yates corrected chi-squared value of 1,537, a Mantel-Haenszel chi-squared value of 19,302, and a Cohen kappa of 0.88. Results for record retrieval were even better, with a mean record detection rate of 0.94, a positive predictive value of 0.99, a Yates corrected chi-squared value of 94, 774, a Mantel-Haenszel chi-squared value of 1,550,356, and a Cohen kappa value of 0.94. The mean detection rate, Yates corrected chi-squared value, and Cohen kappa value for semantic retrieval were significantly better than for the other methods. CONCLUSION: The use of a semantic terminological model in this test scenario provides an effective framework for representing clinical finding concepts and their relationships. Although currently incomplete, the model supports improved information retrieval from a patient database in response to clinically relevant questions, when compared with alternative methods of analysis.

Data Interpretation, Statistical↗

PubMedDate not supplied

Terminology for vulvar cytology based on the Bethesda System.

OBJECTIVE: To present a new terminology for vulvar cytology based on the Bethesda System. STUDY DESIGN: Material for cytologic diagnosis was collected by scraping vulvar lesions with a scalpel blade. RESULTS: This terminology was presented for the first time at an International Academy of Cytology conference in Kamuela, Hawaii, in 1997. It is based on the Bethesda System (1994) and WHO system. We recommend the following elements for a vulvar cytologic report: adequacy of specimen, general categorization and descriptive diagnosis. The terminology of vulvar lesions includes benign cellular changes (vulvitis and reactive changes) and epithelial cell abnormalities. If epithelial cell abmormalities are found, the following diagnoses are made: atypical squamous cells of undetermined significance, LSIL, HSIL and vulvar tumors. The most common epithelial tumors are papillary hydradenoma, squamous cell carcinoma and Paget's disease. Five hundred and sixty-three patients with vulvar cytology were examined in our department over 11 years, including 132 with normal vulvas, 220 with vulvitis, 145 with VSIL and 56 with squamous cell carcinoma. Histologic examination of 147 patients (26.11%) showed a sensitivity of 97.70% for benignity and 98.21% for malignancy and 98.87% and 94.82% for specificity, respectively. CONCLUSION: Vulvar cytodiagnosis with the new terminology allows both reporting on the type of vulvar lesions and cancer detection.

Cytological Techniques↗

PubMed2003

Falls prevention within the Australian general practice data model: methodology, information model, and terminology issues.

The iterative development of the Falls Risk Assessment and Management System (FRAMS) drew upon research evidence and early consumer and clinician input through focus groups, interviews, direct observations, and an online questionnaire. Clinical vignettes were used to validate the clinical model and program logic, input, and output. The information model was developed within the Australian General Practice Data Model (GPDM) framework. The online FRAMS implementation used available Internet (TCP/IP), messaging (HL7, XML), knowledge representation (Arden Syntax), and classification (ICD10-AM, ICPC2) standards. Although it could accommodate most of the falls prevention information elements, the GPDM required extension for prevention and prescribing risk management. Existing classifications could not classify all falls prevention concepts. The lack of explicit rules for terminology and data definitions allowed multiple concept representations across the terminology-architecture interface. Patients were more enthusiastic than clinicians. A usable standards-based online-distributed decision support system for falls prevention can be implemented within the GPDM, but a comprehensive terminology is required. The conceptual interface between terminology and architecture requires standardization, preferably within a reference information model. Developments in electronic decision support must be guided by evidence-based clinical and information models and knowledge ontologies. The safety and quality of knowledge-based decision support systems must be monitored. Further examination of falls and other clinical domains within the GPDM is needed.

Accidental Falls↗

PubMed2004

Terminology and classification of the cortical dysplasias.

BACKGROUND: There have been difficulties in achieving a uniform terminology in the literature regarding issues of classification with respect to focal cortical dysplasias (FCDs) associated with epilepsy. OBJECTIVE: S: To review and refine the current terminology and classification issues of potential clinical relevance to epileptologists, neuroradiologists, and neuropathologists dealing with FCD. METHODS: A panel discussion of epileptologists, neuropathologists, and neuroradiologists with special expertise in FCD was held. RESULTS: The panel proposed 1) a specific terminology for the different types of abnormal cells encountered in the cerebral cortex of patients with FCD; 2) a reappraisal of the different histopathologic abnormalities usually subsumed under the term "microdysgenesis," and suggested that this terminology be abandoned; and 3) a more detailed yet straightforward classification of the various histopathologic features that usually are included under the heterogeneous term of "focal cortical dysplasia." CONCLUSION: The panel hopes that these proposals will stimulate the debate toward more specific clinical, imaging, histopathologic, and prognostic correlations in patients with FCD associated with epilepsy.

Brain Diseases↗

PubMed2005

[Anatomical terminology in ophthalmology].

The purpose of this article is inform ophthalmologists of the International Anatomical Terminology in the Portuguese language edited by the Federation Committee on Anatomical Terminology (FCAT). In Brazil the International Anatomical Terminology was translated by the Anatomical Terminology Commission of the Brazilian Society of Anatomy.

Brazil↗

PubMed1997

Strategies and tools for creating a common nursing terminology within a large health maintenance organization.

A common nursing terminology is essential for outcomes research, data comparability and clinical documentation in an electronic health record. Kaiser Permanente has recognized the need to develop a common nursing and medical terminology across the program. The Interregional Nursing Nomenclature Committee has developed a model for developing a common nursing terminology integrated with other healthcare terminologies.

Health Maintenance Organizations↗

PubMed1998

Integrating sources for a clinical reference terminology: experience linking SNOMED to LOINC and drug vocabularies.

Achieving the promise of higher quality, lower cost and more available health care through electronic medical records requires the support of a comprehensive clinical reference terminology. In a previous paper we described SNOMED RT (reference terminology), and the data structures and logic syntax that support the transformation of the SNOMED III nomenclature into the SNOMED RT reference terminology. In this paper, we describe an approach to linking SNOMED RT to existing nomenclatures in the area of laboratory test names (LOINC) and therapeutic drugs (Multum's MediSource Drug Lexicon), in order to achieve an integrated whole that solves the problem of a clinical reference terminology.

Clinical Laboratory Techniques↗

PubMed1998

Lessons learned from co-operative terminology work in the medical domain.

High-quality terminologies are crucial for communication, documentation, and information retrieval. The creation, adoption, and maintenance of such terminologies is a complex task that requires human co-operation. We have developed a terminology server that supports remote, asynchronous co-operation and allows data inconsistencies that can later be resolved through human discussion. We have employed the terminology server in two projects and report on the lessons learned, which have led us to extend our approach.

Artificial Intelligence↗

PubMed1999

Desiderata for a clinical terminology server.

Clinical terminology servers are distinguished from more broadly based terminology servers intended for nomenclature development or mediation across classifications. Focusing upon the consistent and comparable entry of clinical observations, findings, and events, key desiderata are enumerated and expanded. These include 1) word normalization, 2) word completion, 3) target terminology specification, 4) spelling correction, 5) lexical matching, 6) term completion, 7) semantic locality, 8) term composition and 9) decomposition. Comparisons of this functionality to previously published models and specifications are made. Experience with a clinical terminology server, Metaphrase, is described.

Abstracting and Indexing↗

PubMed1999

Clinical terminology: why is it so hard?

Despite years of work, no re-usable clinical terminology has yet been demonstrated in widespread use. This paper puts forward ten reasons why developing such terminologies is hard. All stem from underestimating the change entailed in using terminology in software for 'patient centred' systems rather than for its traditional functions of statistical and financial reporting. Firstly, the increase in scale and complexity are enormous. Secondly, the resulting scale exceeds what can be managed manually with the rigour required by software, but building appropriate rigorous representations on the necessary scale is, in itself, a hard problem. Thirdly, 'clinical pragmatics'--practical data entry, presentation and retrieval for clinical tasks--must be taken into account, so that the intrinsic differences between the needs of users and the needs of software are addressed. This implies that validation of clinical terminologies must include validation in use as implemented in software.

Medical Informatics↗

PubMed2001

Synonymy of medical terminology from the point of view of comparative linguistics.

The aim of the paper is to look at the medical terminology in three different languages--English, Russian and Slovak and to estimate the trends of synonym formation as well as their emphasizes role in communication. The author that the problem of synonymy is peculiar especially to clinical medicine terminology, i.e. it relates only to a small extent anatomical nomenclature. According to motivative signs of terms, synonyms are divided into 2 groups: equivalent and interpretative synonyms. In keeping with criteria determined by basic characteristics of a term in medical terminology there are often preferred international expressions. In recent years a great number of English expressions have entered into medical terminology due to the fact that English had became a language of international communication. From the practical point view undoubtedly, it is a positive tendency, because it facilitates international communication. In this respect Russian orthography is considered to be an exception, since Cyrillic alphabet often makes international communication more complicated. (Ref. 10.).

Linguistics↗

PubMed2001

An evaluation of the utility of the CEN categorical structure for nursing diagnoses as a terminology model for integrating nursing diagnosis concepts into SNOMED.

We evaluated the utility of the CEN Categorical Structure for Nursing Diagnoses as a terminology model for integrating nursing diagnosis concepts into SNOMED. First, we dissected nursing diagnosis term phrases from two source terminologies (North American Nursing Diagnosis Association (NANDA) Taxonomy 1 and Omaha System) into the semantic categories of the CEN categorical structure. Second, we critically analyzed the similarities between the semantic links in the CEN model and the semantic links used to formally define diagnostic concepts in SNOMED RT and SNOMED CT. Our findings demonstrated that focus, bearer, and judgment were present in 100% of the NANDA and Omaha term phrases. The Omaha term phrases contained no additional descriptors beyond those considered mandatory in the CEN model. In contrast, at least 3% of NANDA diagnoses included a term in each semantic category of the categorical structure. The comparison among the semantic links showed that neither SNOMED RT and SNOMED CT currently contain all the semantic links needed to model the two source terminologies for integration. In conclusion, our findings support the potential utility of the CEN categorical structure as a terminology model for dissecting nursing diagnostic concepts for integration into SNOMED RT and SNOMED CT. However, in order to accomplish this task, appropriate semantic links must be added to SNOMED RT and SNOMED CT.

Nursing Diagnosis↗

PubMed2001

Mediating between nursing intervention terminology systems.

The purpose of this study is to explore the use of formal systems as a way of mediating between diverse nursing intervention terminology systems. Existing approaches to mediation, such as the UMLS Metathesaurus, make heavy use of surface language. This compromises their capacity for managing similarities and differences between terminology systems. Within this study an initial ontology, derived from three existing terminology systems, was built using the GALEN approach. The ontology overcomes many of the barriers to effective mediation; it represents a rich integrated hierarchy that may be used to identify both direct and indirect mappings between concepts from diverse terminology systems. The approach used forms part of a formative, evolutionary development methodology in which potential mappings are validated and the results fed back into the next round of development.

Nursing↗

PubMed2002

Terminology extraction from text to build an ontology in surgical intensive care.

In many medical fields, the maintenance of unabiguous terminologies, the comparison and aggregation of different terminologies go through the building of formal specialized clinical terminologies, the ontologies. In this paper, we describe the building of an ontology in the surgical intensive care medical domain. We considered textual reports as the main source of information and a natural language processing tool, the SYNTEX software, is used to build the ontology. We have tested the possibility for an expert to build a sizeable ontology in a reasonable time. The quality of the ontology has been evaluated according to its capacity to cover the ICD-10 terminology in the field. Examples of coding activity with the ontology are proposed and discussed.

Critical Care↗

PubMed2003

Mining terminological knowledge in large biomedical corpora.

Terminological knowledge of the biomedical domain is important for natural language processing (NLP) and information retrieval (IR) applications, and a number of terminological knowledge sources, such as LocusLink, GeneBank, and the UMLS, already exist. However, because of the tremendous amount of research activity in the field, new terms and symbols are continually being created, many of which are published in the literature, but are not available in any of the other resources. Therefore, effective mining of the literature for new terminology is critical for furthering NLP and IR applications. Abbreviations are widely used in the biomedical domain, and the understanding of abbreviations requires a terminological knowledge base that consists of abbreviations with their associated senses. In previous work, several methods have been developed for automatic construction of abbreviation knowledge bases from parenthetical expressions. However, these methods pair abbreviations and their expansions based on manually crafted patterns or rules. In this paper, we propose an automatic method, which is not based on patterns or rules but is based on the use of collocations, to extract a set of related terms from parenthetical expressions including abbreviations associated with their expansions and other types of related terms such as synonyms, or hyponyms etc. Our method is based on the observation that terms associated with parenthetical expressions i) are usually related, and ii) are often collocations because they tend to co-occur more often than expected by chance. Our method was applied to the collection of MEDLINE abstracts. The method and the results were evaluated using two collections: Berman's handcrafted abbreviation list and the LocusLink collection.

Abstracting and Indexing↗

PubMed2003

Putting data integration into practice: using biomedical terminologies to add structure to existing data sources.

A major purpose of biomedical terminologies is to provide uniform concept representation, allowing for improved methods of analysis of biomedical information. While this goal is being realized in bioinformatics, with the emergence of the Gene Ontology as a standard, there is still no real standard for the representation of clinical concepts. As discoveries in biology and clinical medicine move from parallel to intersecting paths, standardized representation will become more important. A large portion of significant data, however, is mainly represented as free text, upon which conducting computer-based inferencing is nearly impossible. In order to test our hypothesis that existing biomedical terminologies, specifically the UMLS Metathesaurus and SNOMED CT, could be used as templates to implement semantic and logical relationships over free text data that is important both clinically and biologically, we chose to analyze OMIM (Online Mendelian Inheritance in Man). After finding OMIM entries' conceptual equivalents in each respective terminology, we extracted the semantic relationships that were present and evaluated a subset of them for semantic, logical, and biological legitimacy. Our study reveals the possibility of putting the knowledge present in biomedical terminologies to its intended use, with potentially clinically significant consequences.

Databases, Genetic↗

PubMed2003

An architecture for standardized terminology services by wrapping and integration of existing applications.

Research on terminology services has resulted in development of applications and definition of standards, but has not yet led to widespread use of (standardized) terminology services in practice. Current terminology services offer functionality both for concept representation and lexical knowledge representation, hampering the possibility of combining the strengths of dedicated (concept and lexical) services. We therefore propose an extensible architecture in which concept-related and lexicon-related components are integrated and made available through a uniform interface. This interface can be extended in order to conform to existing standards, making it possible to use dedicated (third-party) components in a standardized way. As a proof of concept and a reference implementation, a SOAP-based Java implementation of the terminology service is being developed, providing wrappers for Protégé and UMLS Knowledge Source Server. Other systems, such as the Description Logic-based reasoner RACER can be easily integrated by implementation of an appropriate wrapper.

Software↗