2013版SNOMED CT顶层概念调整及属性关系

SNOMED CT是结构化的临床术语集。介绍2013年版的SNOMED CT新增顶层概念"SNOMED CT模型组件"及其亚类"连接概念"。概念含义的逻辑表示通过"定义属性"定义,所有可用作"关系类型"的概念都归在"连接概念"下:"|is a|关系"和"概念模型属性"中的59个"属性关系"。并详细说明"关系"如何完整定义概念,以期为构建中医临床术语系统的研究工作提供参考。     

SNOMED CT与OpenEHR的整合探究

详细介绍SNOMED CT与OpenEHR的发展历史、主要内容、主要架构,通过数据类型转换、原型中的临床术语与SNOMED CT的映射、候选术语集等方法进行SNOMED CT与OpenEHR的整合,从而使原型中的术语更加规范,也为互操作提供可能。     

SNOMED CT在临床路径中应用探讨

介绍医学系统命名法--临床术语(Systematized Nomenclature of Medicine-Clinical Terms,SNOMED CT)的历史发展、内容及应用情况,阐述临床路径的作用与实施原则,深入分析在临床路径中使用SNOMED CT的可能性、具体实施方法和重要意义.标准化术语的支持有利于推动临床路径的合理化调整与推广实施.     

2018年版SNOMED CT国际药物模型体系简介

目的 对新版医学系统命名法-临床术语(Systematized Nomenclature of Medicine-Clinical Terms,SNOMED CT)中的国际药物模型进行介绍,为我国药物模型的构建提供参考.方法 对2018年7月更新的SNOMED CT国际药物模型的设计理念、药物分类体系进行介绍,并以含氨...     

临床医学系统术语SNOMED CT的特点及其应用

SNOMED CT已经成为国际上广泛关注的一种医学参考术语与信息编码。介绍了SNOMED CT的发展历史，着重介绍与分析了其核心内容与特点，最后介绍了SNOMED CT的应用情况。     

医学观察数据的元数据框架反标准化应用

目的：构建医学观察数据的语义模型和元数据框架,为医学观察数据的规范化表达和信息共享提供基础.方法：参照国际标准化组织ISO有关信息技术标准及SNOMED CT、LOINC等医学领域相关国际、国家标准,定义医学观察项目的属性和元数据规范,采用UML建模.结果：医学观察数据的语义模型将医学观察逐步分解,形成类的树状层次结构.第一层可分为体格检查、实验室检查等4个子类;类包含一组特定的属性;属性以数据元的形式,通过元数据进行描述;一组特定属性（数据元）的实例即为规范化的医学观察数据.结论：语义模型和元数据框架规范下的医学观察数据具有完整、清晰的语义和统一的格式.构建元数据框架有利于医学观察数据的标准化,可作为国家卫生数据字典的研发策略.     

基于本体的中西医知识体系对比研究

中医知识体系中包含大量的隐性知识,运用本体构建中医知识体系有利于中医隐性知识的表达与共享。通过对医学系统命名法-临床术语(SNOMED CT)和中医临床术语系统的研究,从本体论的角度分析中西医学知识特点,对发展中医进行提示:利用本体论构建中医知识体系,进而完善中医临床术语系统,促进中医临床知识共享。     

SNOMEDCT层次结构与标识符

SNOMED CT中的概念都通过层级关系相连.介绍了目前SNOMD CT的概念层级结构及分类情况,包括新增加的＂元数据层级＂、＂根元数据概念＂;还介绍了常用的几个标识符及SNOMED CT标识符（SCTID）的结构,包括数据类型、扩展、约束条件、验校码、分区标识符、命名空间等,为学习和借鉴SNOMD CT的标准化方法提供资料.     

临床信息系统数据标准及其应用

临床信息数据是临床信息系统的重要组成部分,对整个医院信息系统建设起着至关重要的作用。本文介绍了国内外临床信息系统数据标准,探讨了HL7、DICOM、SNOMED等标准在临床信息数据集成的作用,分析了一个电子病历项目中以临床业务为核心数据集成的相关问题。     

基于语义表达的中药概念数据模型的设计理念与构建

目的：建立基于语义表达的中药概念数据模型。方法：利用文献分析法结合专家咨询进行中药及相关领域概念抽取、概念间关系设定以及数据模型框架的构建。结果：构建了基于语义表达的中药概念数据模型。结论：基于本体与数据相结合的思路构建基于统一语义表达的中药概念数据模型,有利于理清中药及相关领域概念及关系,方便数据的共享与重用,对于物理数据模型的构建也具有指导作用。     

Research and applications: Semantic analysis of SNOMED CT for a post-coordinated database of histopathology findings

Objective

This research investigated the use of SNOMED CT to represent diagnostic tissue morphologies and notable tissue architectures typically found within a pathologist''s microscopic examination report to identify gaps in expressivity of SNOMED CT for use in anatomic pathology.

Methods

24 breast biopsy cases were reviewed by two board certified surgical pathologists who independently described the diagnostically important tissue architectures and diagnostic morphologies observed by microscopic examination. In addition, diagnostic comments and details were extracted from the original diagnostic pathology report. 95 unique clinical statements were extracted from 13 malignant and 11 benign breast needle biopsy cases.

Results

75% of the inventoried diagnostic terms and statements could be represented by valid SNOMED CT expressions. The expressions included one pre-coordinated expression and 73 post-coordinated expressions. No valid SNOMED CT expressions could be identified or developed to unambiguously assert the meaning of 21 statements (ie, 25% of inventoried clinical statements). Evaluation of the findings indicated that SNOMED CT lacked sufficient definitional expressions or the SNOMED CT concept model prohibited use of certain defined concepts needed to describe the numerous, diagnostically important tissue architectures and morphologic changes found within a surgical pathology microscopic examination.

Conclusions

Because information gathered during microscopic histopathology examination provides the basis of pathology diagnoses, additional concept definitions for tissue morphometries and modifications to the SNOMED CT concept model are needed and suggested to represent detailed histopathologic findings in computable fashion for purposes of patient information exchange and research.

Trial registration number

UNMC Institutional Review Board ID# 342-11-EP.     

Use of SNOMED CT to Represent Clinical Research Data: A Semantic Characterization of Data Items on Case Report Forms in Vasculitis Research

ObjectiveTo estimate the coverage provided by SNOMED CT for clinical research concepts represented by the items on case report forms (CRFs), as well as the semantic nature of those concepts relevant to post-coordination methods.DesignConvenience samples from CRFs developed by rheumatologists conducting several longitudinal, observational studies of vasculitis were selected. A total of 17 CRFs were used as the basis of analysis for this study, from which a total set of 616 (unique) items were identified. Each unique data item was classified as either a clinical finding or procedure. The items were coded by the presence and nature of SNOMED CT coverage and classified into semantic types by 2 coders.MeasurementsBasic frequency analysis was conducted to determine levels of coverage provided by SNOMED CT. Estimates of coverage by various semantic characterizations were estimated.ResultsMost of the core clinical concepts (88%) from these clinical research data items were covered by SNOMED CT; however, far fewer of the concepts were fully covered (that is, where all aspects of the CRF item could be represented completely without post-coordination; 23%). In addition, a large majority of the concepts (83%) required post-coordination, either to clarify context (e.g., time) or to better capture complex clinical concepts (e.g., disease-related findings). For just over one third of the sampled CRF data items, both types of post-coordination were necessary to fully represent the meaning of the item.ConclusionSNOMED CT appears well-suited for representing a variety of clinical concepts, yet is less suited for representing the full amount of information collected on CRFs.     

Using SNOMED CT to Represent Two Interface Terminologies

Objective

Interface terminologies are designed to support interactions between humans and structured medical information. In particular, many interface terminologies have been developed for structured computer based documentation systems. Experts and policy-makers have recommended that interface terminologies be mapped to reference terminologies. The goal of the current study was to evaluate how well the reference terminology SNOMED CT could map to and represent two interface terminologies, MEDCIN and the Categorical Health Information Structured Lexicon (CHISL).

Design

Automated mappings between SNOMED CT and 500 terms from each of the two interface terminologies were evaluated by human reviewers, who also searched SNOMED CT to identify better mappings when this was judged to be necessary. Reviewers judged whether they believed the interface terms to be clinically appropriate, whether the terms were covered by SNOMED CT concepts and whether the terms' implied semantic structure could be represented by SNOMED CT.

Measurements

Outcomes included concept coverage by SNOMED CT for study terms and their implied semantics. Agreement statistics and compositionality measures were calculated.

Results

The SNOMED CT terminology contained concepts to represent 92.4% of MEDCIN and 95.9% of CHISL terms. Semantic structures implied by study terms were less well covered, with some complex compositional expressions requiring semantics not present in SNOMED CT. Among sampled terms, those from MEDCIN were more complex than those from CHISL, containing an average 3.8 versus 1.8 atomic concepts respectively, p<0.001.

Conclusion

Our findings support using SNOMED CT to provide standardized representations of information created using these two terminologies, but suggest that enriching SNOMED CT semantics would improve representation of the external terms.     

MeSH的概念结构及其意义

通过对MeSH从传统词结构模式向基于概念结构模式转变的研究,重点对MeSH概念结构特征、主题词类构成、语义关系揭示和表述进行分析。从MeSH的结构化组织方式、语义网实现、一体化知识组织模式和兼容发展等方面,对网络环境下主题词表的建设与发展进行论述。