Fast Healthcare Interoperability Resources, Clinical Quality Language, and Systematized Nomenclature of Medicine-Clinical Terms in Representing Clinical Evidence Logic Statements for the Use of Imaging Procedures: Descriptive Study
Fast Healthcare Interoperability Resources, Clinical Quality Language, and Systematized Nomenclature of Medicine-Clinical Terms in Representing Clinical Evidence Logic Statements for the Use of Imaging Procedures: Descriptive Study
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DOI：
10.2196/13590
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发表时间：
2019-04-01
影响因子：
3.2
通讯作者：
Khorasani, Ramin
中科院分区：
文献类型：
--
作者：
Odigie, Eseosa;Lacson, Ronilda;Khorasani, Ramin
背景：循证指南和建议可以转化为“如果-那么”临床证据逻辑声明（CELS）。成像相关CELS以标准化格式在哈佛医学院证据库（HLE）中表示。目的：我们的目的是（1）使用已建立的系统化医学术语-临床术语描述CELS的表示（SNOMED CT），临床质量语言（CQL），和快速医疗保健互操作性资源（FHIR）标准，以及（2）评估使用这些标准表示成像的局限性-方法：该研究免于机构审查委员会的审查，因为它不涉及人类受试者。从证据来源中提取影像学相关临床建议，并翻译成CELS。CELS的临床术语用SNOMED CT表示，条件-动作逻辑用CQL和FHIR表示。结果：截至2018年12月，共有765名CELS在HLE中被代表。我们能够使用SNOMED CT、CQL和FHIR完全代表765例CELS中的137例（17.9%）。我们能够代表条款使用SNOMED CT的时间组成部分的行动（“然后”）在CQL和FHIR的755 765（98.7%）CELS.Conclusions声明：CELS表示为共享的临床决策支持（CDS）知识文物使用现有的标准SNOMED CT，FHIR，CQL，以促进和加速采用循证实践。标准化的局限性仍然存在，可以通过添加一组标准术语和值集以及向CQL框架添加时间框架来最小化。
Background: Evidence-based guidelines and recommendations can be transformed into "If-Then" Clinical Evidence Logic Statements (CELS). Imaging-related CELS were represented in standardized formats in the Harvard Medical School Library of Evidence (HLE).Objective: We aimed to (1) describe the representation of CELS using established Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), Clinical Quality Language (CQL), and Fast Healthcare Interoperability Resources (FHIR) standards and (2) assess the limitations of using these standards to represent imaging-related CELS.Methods: This study was exempt from review by the Institutional Review Board as it involved no human subjects. Imaging-related clinical recommendations were extracted from evidence sources and translated into CELS. The clinical terminologies of CELS were represented using SNOMED CT and the condition-action logic was represented in CQL and FHIR. Numbers of fully and partially represented CELS were tallied.Results: A total of 765 CELS were represented in the HLE as of December 2018. We were able to fully represent 137 of 765 (17.9%) CELS using SNOMED CT, CQL, and FHIR. We were able to represent terms using SNOMED CT in the temporal component for action ("Then") statements in CQL and FHIR in 755 of 765 (98.7%) CELS.Conclusions: CELS were represented as shareable clinical decision support (CDS) knowledge artifacts using existing standards-SNOMED CT, FHIR, and CQL-to promote and accelerate adoption of evidence-based practice. Limitations to standardization persist, which could be minimized with an add-on set of standard terms and value sets and by adding time frames to the CQL framework.