Clinical Terminologies in the NHS: SNOMED CT and dm+d

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Ian David Spiers
Keyword(s):  
Snomed Ct ◽  
Clinical Terminologies

Semantic Integration of Patient Data for Clinical Decision Support in Breast Cancer Care

2013 ◽  
pp. 250-267
Author(s):  
Leonardo Lezcano ◽  
Miguel-Ángel Sicilia ◽  
Eydel Rivero
Keyword(s):  
Breast Cancer ◽  
Decision Support ◽  
Clinical Guidelines ◽  
Clinical Decision ◽  
Semantic Integration ◽  
Semantic Interoperability ◽  
Snomed Ct ◽  
Life Threatening ◽  
Delays In Diagnosis ◽  
Clinical Terminologies

Achieving semantic interoperability between heterogeneous healthcare systems and integrating clinical guidelines in the automatic decision support of healthcare institutions are two key priorities of current medical informatics. They can lead to a significant improvement on patient safety by reducing medical risks and delays in diagnosis, facilitating continuity of care and preventing life threatening adverse events. The present chapter describes a project that addresses those two priorities in the field of Breast Cancer for which effective clinical guidelines are available, as well as the clinical data to apply them. However, the deployment of semantic interoperability techniques based on clinical terminologies such as SNOMED-CT and EHR exchange models such as openEHR and HL7 is required to meaningfully combine the available data. Then data mining techniques are capable of automatically adapting the parameters of clinical guidelines to the particular conditions of each healthcare environment.

Snomed® CT: The Fit with Classification in Health

2003 ◽  
Vol 31 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Diane J Aschman
Keyword(s):  
Information Management ◽  
Medical Records ◽  
Classification Systems ◽  
New Work ◽  
Snomed Ct ◽  
Healthcare Data ◽  
The World ◽  
Primary Means ◽  
Systematized Nomenclature Of Medicine ◽  
Clinical Terminologies

Classification systems are the primary means for automated retrieval and analysis of healthcare data from individual patient medical records. This article will provide a brief history and overview of the two most comprehensive and advanced controlled clinical terminologies in the world: the Systematized Nomenclature of Medicine Reference Terminology (SNOMED® RT), and Clinical Terms Version 3 (CTV3). A discussion will follow of the merger of these two terminologies into a single new work, SNOMED® Clinical Terms (SNOMED® CT), as released in early 2002, how it is used to retrieve data, how it differs from a classification, and the opportunities open to health information management professionals to expand their roles as information managers through their knowledge of SNOMED CT.

scholarly journals Mapping of Wound Infection Concepts

2021 ◽  
Author(s):  
Lorraine J Block ◽  
Charlene Ronquillo ◽  
Nicholas R Hardiker ◽  
Sabrina T Wong ◽  
Leanne M Currie
Keyword(s):  
Health Care ◽  
Wound Infection ◽  
Early Identification ◽  
Snomed Ct ◽  
Mapping Process ◽  
Infection Types ◽  
Clinical Terminologies ◽  
Assessment And Diagnosis

Wound infection is a serious health care complication. Standardized clinical terminologies could be leveraged to support the early identification of wound infection. The purpose of this study was to evaluate the representation of wound infection assessment and diagnosis concepts (N=26) in SNOMED CT and ICNP, using a synthesized procedural framework. A total of 13/26 (50%) assessment and diagnosis concepts had exact matches in SNOMED CT and 2/7 (29%) diagnosis concepts had exact matches in ICNP. This study demonstrated that the source concepts were moderately well represented in SNOMED CT and ICNP; however, further work is necessary to increase the representation of diagnostic infection types. The use of the framework facilitated a systematic, transparent, and repeatable mapping process, with opportunity to extend.

scholarly journals Recent Developments in Clinical Terminologies — SNOMED CT, LOINC, and RxNorm

2018 ◽  
Vol 27 (01) ◽  
pp. 129-139 ◽  
Author(s):  
Oliver Bodenreider ◽  
Ronald Cornet ◽  
Daniel Vreeman
Keyword(s):  
Snomed Ct ◽  
Standard Drug ◽  
Funding Sources ◽  
Current State ◽  
Development Teams ◽  
Recent Developments ◽  
Clinical Terminology ◽  
Systematized Nomenclature Of Medicine ◽  
Evolutionary Paths ◽  
Clinical Terminologies

Objective: To discuss recent developments in clinical terminologies. SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) is the world's largest clinical terminology, developed by an international consortium. LOINC (Logical Observation Identifiers, Names, and Codes) is an international terminology widely used for clinical and laboratory observations. RxNorm is the standard drug terminology in the U.S. Methods and results: We present a brief review of the history, current state, and future development of SNOMED CT, LOINC and RxNorm. We also analyze their similarities and differences, and outline areas for greater interoperability among them. Conclusions: With different starting points, representation formalisms, funding sources, and evolutionary paths, SNOMED CT, LOINC, and RxNorm have evolved over the past few decades into three major clinical terminologies supporting key use cases in clinical practice. Despite their differences, partnerships have been created among their development teams to facilitate interoperability and minimize duplication of effort.

SNOMED CT: Gemeinsame Sprache für medizinische Daten

2020 ◽  
Vol 25 (04) ◽  
pp. 9-9
Keyword(s):  
Snomed Ct

Das Bundesforschungsministerium hat eine Pilotlizenz für den internationalen Terminologiestandard SNOMED CT erworben.

The use of a Domain Ontology for the Management of Essential Hypertension (Preprint)

2020 ◽  
Author(s):  
Emma Chavez ◽  
Vanessa Perez ◽  
Angélica Urrutia
Keyword(s):  
Decision Making ◽  
Essential Hypertension ◽  
Medical History ◽  
Medical Records ◽  
Medical Training ◽  
Relevant Information ◽  
Domain Ontology ◽  
Free Text ◽  
Snomed Ct ◽  
History Of

BACKGROUND : Currently, hypertension is one of the diseases with greater risk of mortality in the world. Particularly in Chile, 90% of the population with this disease has idiopathic or essential hypertension. Essential hypertension is characterized by high blood pressure rates and it´s cause is unknown, which means that every patient might requires a different treatment, depending on their history and symptoms. Different data, such as history, symptoms, exams, etc., are generated for each patient suffering from the disease. This data is presented in the patient’s medical record, in no order, making it difficult to search for relevant information. Therefore, there is a need for a common, unified vocabulary of the terms that adequately represent the diseased, making searching within the domain more effective. OBJECTIVE The objective of this study is to develop a domain ontology for essential hypertension , therefore arranging the more significant data within the domain as tool for medical training or to support physicians’ decision making will be provided. METHODS The terms used for the ontology were extracted from the medical history of de-identified medical records, of patients with essential hypertension. The Snomed-CT’ collection of medical terms, and clinical guidelines to control the disease were also used. Methontology was used for the design, classes definition and their hierarchy, as well as relationships between concepts and instances. Three criteria were used to validate the ontology, which also helped to measure its quality. Tests were run with a dataset to verify that the tool was created according to the requirements. RESULTS An ontology of 310 instances classified into 37 classes was developed. From these, 4 super classes and 30 relationships were obtained. In the dataset tests, 100% correct and coherent answers were obtained for quality tests (3). CONCLUSIONS The development of this ontology provides a tool for physicians, specialists, and students, among others, that can be incorporated into clinical systems to support decision making regarding essential hypertension. Nevertheless, more instances should be incorporated into the ontology by carrying out further searched in the medical history or free text sections of the medical records of patients with this disease.

scholarly journals Collecting specialty-related medical terms: Development and evaluation of a resource for Spanish

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pilar López-Úbeda ◽  
Alexandra Pomares-Quimbaya ◽  
Manuel Carlos Díaz-Galiano ◽  
Stefan Schulz
Keyword(s):  
Language Processing ◽  
Classification Problem ◽  
Snomed Ct ◽  
Language Resources ◽  
Clinical Specialty ◽  
Controlled Vocabularies ◽  
Clinical Text ◽  
Domain Specific ◽  
Medical Terms ◽  
Core Vocabulary

Abstract Background Controlled vocabularies are fundamental resources for information extraction from clinical texts using natural language processing (NLP). Standard language resources available in the healthcare domain such as the UMLS metathesaurus or SNOMED CT are widely used for this purpose, but with limitations such as lexical ambiguity of clinical terms. However, most of them are unambiguous within text limited to a given clinical specialty. This is one rationale besides others to classify clinical text by the clinical specialty to which they belong. Results This paper addresses this limitation by proposing and applying a method that automatically extracts Spanish medical terms classified and weighted per sub-domain, using Spanish MEDLINE titles and abstracts as input. The hypothesis is biomedical NLP tasks benefit from collections of domain terms that are specific to clinical subdomains. We use PubMed queries that generate sub-domain specific corpora from Spanish titles and abstracts, from which token n-grams are collected and metrics of relevance, discriminatory power, and broadness per sub-domain are computed. The generated term set, called Spanish core vocabulary about clinical specialties (SCOVACLIS), was made available to the scientific community and used in a text classification problem obtaining improvements of 6 percentage points in the F-measure compared to the baseline using Multilayer Perceptron, thus demonstrating the hypothesis that a specialized term set improves NLP tasks. Conclusion The creation and validation of SCOVACLIS support the hypothesis that specific term sets reduce the level of ambiguity when compared to a specialty-independent and broad-scope vocabulary.

scholarly journals Quality assurance and enrichment of biological and biomedical ontologies and terminologies

2020 ◽  
Vol 20 (S10) ◽  
Author(s):  
Ankur Agrawal ◽  
Licong Cui
Keyword(s):  
Quality Assurance ◽  
Cancer Registries ◽  
Supplement Issue ◽  
Biomedical Ontologies ◽  
Snomed Ct ◽  
Unified Medical Language System ◽  
Domain Specific ◽  
Healthcare Settings ◽  
Domain Specific Knowledge ◽  
Enrichment Techniques

AbstractBiological and biomedical ontologies and terminologies are used to organize and store various domain-specific knowledge to provide standardization of terminology usage and to improve interoperability. The growing number of such ontologies and terminologies and their increasing adoption in clinical, research and healthcare settings call for effective and efficient quality assurance and semantic enrichment techniques of these ontologies and terminologies. In this editorial, we provide an introductory summary of nine articles included in this supplement issue for quality assurance and enrichment of biological and biomedical ontologies and terminologies. The articles cover a range of standards including SNOMED CT, National Cancer Institute Thesaurus, Unified Medical Language System, North American Association of Central Cancer Registries and OBO Foundry Ontologies.

Terminological cooperation in the biomedical field

Terminology ◽  
2021 ◽  
Vol 27 (1) ◽  
pp. 10-34
Author(s):  
Maria-Cornelia Wermuth
Keyword(s):  
Patient Care ◽  
Language Use ◽  
Medical Terminology ◽  
Snomed Ct ◽  
Societal Relevance ◽  
Efficient Communication ◽  
Systematic Nomenclature ◽  
Biomedical Field ◽  
Cost Efficient ◽  
Further Development

Abstract This paper deals with collaborative terminological activities in the biomedical field. Efficient communication based on uniform language use is a prerequisite for safe and cost-efficient patient care. Terminological consistency and standardization are therefore central issues in healthcare with high societal relevance. The objectives of this contribution are (1) to show how actors from different disciplines and institutions are involved in the standardization of medical terminology and electronic terminology systems; (2) to describe how translation-oriented terminological principles affect the translation of the Systematic Nomenclature of Medicine – Clinical Terms (SNOMED CT). The challenges of this approach will be discussed and some suggestions for its further development will be made.

The Expressiveness of SNOMED CT for Wound Care: Mapping a standardised Item Set for Leg Ulcers to SNOMED CT (Preprint)

2021 ◽  
Author(s):  
Jens Hüsers ◽  
Mareike Przysucha ◽  
Moritz Esdar ◽  
Swen Malte JOHN ◽  
Ursula Hertha Hübner
Keyword(s):  
Health Care Professionals ◽  
Information Exchange ◽  
Chronic Wounds ◽  
Wound Care ◽  
Information Model ◽  
Coverage Rate ◽  
Clinical Usefulness ◽  
Leg Ulcers ◽  
Snomed Ct ◽  
Mapping Procedure

BACKGROUND Chronic health conditions are on the rise and are putting high economic pressure on health systems as they require well-coordinated prevention and treatment. Among chronic conditions, chronic wounds such as cardiovascular leg ulcers have a high prevalence. Their treatment is highly interdisciplinary and regularly spans multiple care settings and organizations, thus placing particularly high demands on interoperable information exchange that can be achieved using international semantic standards such as SNOMED CT. OBJECTIVE This study aims to investigate the expressiveness of SNOMED CT in the domain of wound care, and thereby its clinical usefulness and the potential need for extensions. METHODS A clinically consented and profession independent wound care item set, the German National Consensus for the Documentation of Leg Wounds (NKDUC), was mapped onto the international reference terminology SNOMED CT. Prior to the mapping, the NKDUC was transformed into an information model that served to systematically identify the relevant items. The mapping process itself was carried out in accordance with the formalism of ISO/TR 12300. As a result, the reliability, equivalence, and coverage rate were determined. RESULTS The developed information model revealed 268 items to be mapped. Conducted by three health care professionals, the mapping resulted in “moderate” reliability (K=0.512). Regarding the two best equivalence categories, the coverage rate of SNOMED CT was 67.2% overall and 64.3% specifically for wounds. CONCLUSIONS The results yielded acceptable reliability values for the mapping procedure. The overall coverage rate shows that two-thirds of the items could be mapped symmetrically, which is a substantial portion of the source item set. Some wound care sections, such as general medical condition and wound assessment, were covered better than other sections (wound status, diagnostics, and therapy). These deficiencies can be mitigated either by post-coordination or the inclusion of new concepts in SNOMED CT. This study contributes to pushing interoperability in the domain of wound care and thereby responds to the high demand for information exchange in this field. Overall, this study adds another puzzle piece to the general knowledge about SNOMED CT in terms of its clinical usefulness and its need for further extensions.

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