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将 HIE CT 术语映射到 LOINC®:通过创建新术语分析内容相关的覆盖范围和覆盖范围的改进。

Mapping of HIE CT terms to LOINC®: analysis of content-dependent coverage and coverage improvement through new term creation.

机构信息

Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Center for Biomedical Informatics, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.

出版信息

J Am Med Inform Assoc. 2019 Jan 1;26(1):19-27. doi: 10.1093/jamia/ocy135.

DOI:10.1093/jamia/ocy135
PMID:30445562
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7587153/
Abstract

OBJECTIVE

We describe and evaluate the mapping of computerized tomography (CT) terms from 40 hospitals participating in a health information exchange (HIE) to a standard terminology.

METHODS

Proprietary CT exam terms and corresponding exam frequency data were obtained from 40 participant HIE sites that transmitted radiology data to the HIE from January 2013 through October 2015. These terms were mapped to the Logical Observations Identifiers Names and Codes (LOINC®) terminology using the Regenstrief LOINC mapping assistant (RELMA) beginning in January 2016. Terms without initial LOINC match were submitted to LOINC as new term requests on an ongoing basis. After new LOINC terms were created, proprietary terms without an initial match were reviewed and mapped to these new LOINC terms where appropriate. Content type and token coverage were calculated for the LOINC version at the time of initial mapping (v2.54) and for the most recently released version at the time of our analysis (v2.63). Descriptive analysis was performed to assess for significant differences in content-dependent coverage between the 2 versions.

RESULTS

LOINC's content type and token coverages of HIE CT exam terms for version 2.54 were 83% and 95%, respectively. Two-hundred-fifteen new LOINC CT terms were created in the interval between the releases of version 2.54 and 2.63, and content type and token coverages, respectively, increased to 93% and 99% (P < .001).

CONCLUSION

LOINC's content type coverage of proprietary CT terms across 40 HIE sites was 83% but improved significantly to 93% following new term creation.

摘要

目的

我们描述并评估了来自参与健康信息交换(HIE)的 40 家医院的计算机断层扫描(CT)术语向标准术语的映射。

方法

从 2013 年 1 月至 2015 年 10 月通过 HIE 传输放射学数据的 40 个参与 HIE 站点获得了专有的 CT 检查术语及其相应的检查频率数据。从 2016 年 1 月开始,使用 Regenstrief LOINC 映射助手(RELMA)将这些术语映射到逻辑观察标识符名称和代码(LOINC®)术语。最初没有 LOINC 匹配的术语将作为新术语请求持续提交给 LOINC。创建新的 LOINC 术语后,将审查最初没有匹配的专有术语,并在适当的情况下将其映射到这些新的 LOINC 术语。在初始映射时(v2.54)和在我们分析时最新发布的版本(v2.63)计算 LOINC 版本的内容类型和标记覆盖率。进行描述性分析,以评估两个版本之间内容相关覆盖率的显着差异。

结果

LOINC 的 v2.54 版本的 HIE CT 检查术语的内容类型和标记覆盖率分别为 83%和 95%。在 v2.54 和 v2.63 版本之间的间隔内创建了 215 个新的 LOINC CT 术语,内容类型和标记覆盖率分别增加到 93%和 99%(P < 0.001)。

结论

在 40 个 HIE 站点中,LOINC 专有的 CT 术语的内容类型覆盖率为 83%,但在创建新术语后显着提高到 93%。

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Standard Lexicons, Coding Systems and Ontologies for Interoperability and Semantic Computation in Imaging.用于成像中互操作性和语义计算的标准词汇表、编码系统和本体
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J Am Med Inform Assoc. 2017 Jan;24(1):30-38. doi: 10.1093/jamia/ocw035. Epub 2016 May 13.
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AMIA Annu Symp Proc. 2013 Nov 16;2013:94-102. eCollection 2013.
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LOINC® - A Universal Catalog of Individual Clinical Observations and Uniform Representation of Enumerated Collections.逻辑观测标识符名称和编码系统(LOINC®)——个体临床观察的通用目录及枚举集合的统一表示。
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A rationale for parsimonious laboratory term mapping by frequency.一种基于频率的简约实验室术语映射的基本原理。
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