Matching clinical data to codes in controlled terminologies is the first step towards achieving standardisation of data for safe and accurate data interoperability. The MoST automated system was used to generate a list of candidate SNOMED CT code mappings. The paper discusses the semantic issues which arose when generating lexical and semantic matches of terms from the archetype model to releva...

the issue of medical errors is currently a global concern which places a heavy financial and emotional burden on communities. a clinical decision support system (cdss) is an electronic system designed to support clinical decision making. considering the increasing importance and use of systematized nomenclature of medicine-clinical terms (snomed-ct), we developed snomed-ct to implement it more ...

STRUCTURAL ANALYSIS AND AUDITING OF SNOMED HIERARCHIES USING ABSTRACTION NETWORKS

Relationship groups are a construct which is particular for the representation of concepts in SNOMED CT. In this paper, the July 2008 version of SNOMED CT is analyzed to determine the usage of relationship groups. Relationship groups are used with 36 out of 65 relations, playing a role in 28% of all concepts. Relationship groups are used in the concept types: "procedure" (including "regime/ther...

Fast and holistic access to the patients’ clinical record is a major requirement of modern medical decision support systems (DSS). While electronic health records (EHRs) have replaced the traditional paper-based records in most healthcare organization, the data entry into these systems remains largely manual. Speech recognition technology promises substitution of the more convenient speech-base...

OBJECTIVE Large and complex terminologies, such as Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), are prone to errors and inconsistencies. Abstraction networks are compact summarizations of the content and structure of a terminology. Abstraction networks have been shown to support terminology quality assurance. In this paper, we introduce an abstraction network derivation met...

Converting information contained in natural language clinical text into computer-amenable structured representations can automate many clinical applications. As a step towards that goal, we present a method which could help in converting novel clinical phrases into new expressions in SNOMED CT, a standard clinical terminology. Since expressions in SNOMED CT are written in terms of their relatio...

Quality assurance in large terminologies is a difficult issue. We present two algorithms that can help terminology developers and users to identify potential areas of improvement. We demonstrate the methodology by applying the algorithms to one of the most popular terminologies, SNOMED-CT. Analysis of the results provides evidence for the thesis that both formal logical and linguistic tools sho...

This paper presents the results of a study in which SNOMED CT has been tested in clinical practice by combining quantitative and qualitative methods. An application has been developed for registration of vascular diseases and procedures using SNOMED CT concepts. We conclude that it requires clinical and technical insight to adapt the terminology to a defined clinical domain.