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学习型健康系统、嵌入式研究与数据标准——给医疗系统领导者的建议

Learning health systems, embedded research, and data standards-recommendations for healthcare system leaders.

作者信息

Richesson Rachel L

机构信息

Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan, USA.

出版信息

JAMIA Open. 2020 Oct 12;3(4):488-491. doi: 10.1093/jamiaopen/ooaa046. eCollection 2020 Dec.

Abstract

Learning health systems that conduct embedded research require infrastructure for the seamless adoption of clinical interventions; this infrastructure should integrate with electronic health record (EHR) systems and enable the use of existing data. As purchasers of EHR systems, and as critical partners, sponsors, and consumers of embedded research, healthcare organizations should advocate for EHR system functionality and data standards that will increase the capacity for embedded research in clinical settings. As stakeholders and proponents for EHR data standards, healthcare leaders should support standards development and promote local adoption to support quality healthcare, continuous improvement, innovative data-driven interventions, and the generation of new knowledge. "Standards-enabled" health systems will be positioned to address emergent and critical research questions, including those related to coronavirus disease 2019 (COVID-19) and future public health threats. The role of a data standards officer or champion could enable health systems to realize this goal.

摘要

开展嵌入式研究的学习型卫生系统需要具备无缝采用临床干预措施的基础设施;该基础设施应与电子健康记录(EHR)系统集成,并能够利用现有数据。作为EHR系统的购买者,以及作为嵌入式研究的关键合作伙伴、赞助者和消费者,医疗保健组织应倡导EHR系统功能和数据标准,以提高临床环境中嵌入式研究的能力。作为EHR数据标准的利益相关者和支持者,医疗保健领导者应支持标准制定并促进本地采用,以支持优质医疗保健、持续改进、创新的数据驱动型干预措施以及新知识的产生。“启用标准”的卫生系统将有能力解决紧急和关键的研究问题,包括与2019冠状病毒病(COVID-19)及未来公共卫生威胁相关的问题。数据标准官员或倡导者的作用可以使卫生系统实现这一目标。

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本文引用的文献

1
Rapid response to COVID-19: health informatics support for outbreak management in an academic health system.
J Am Med Inform Assoc. 2020 Jun 1;27(6):853-859. doi: 10.1093/jamia/ocaa037.
2
Creating a Learning Health System through Rapid-Cycle, Randomized Testing.
N Engl J Med. 2019 Sep 19;381(12):1175-1179. doi: 10.1056/NEJMsb1900856.
3
Validation and Refinement of a Pain Information Model from EHR Flowsheet Data.
Appl Clin Inform. 2018 Jan;9(1):185-198. doi: 10.1055/s-0038-1636508. Epub 2018 Mar 14.
4
Pragmatic (trial) informatics: a perspective from the NIH Health Care Systems Research Collaboratory.
J Am Med Inform Assoc. 2017 Sep 1;24(5):996-1001. doi: 10.1093/jamia/ocx016.
5
The PRECIS-2 tool: designing trials that are fit for purpose.
BMJ. 2015 May 8;350:h2147. doi: 10.1136/bmj.h2147.
6
From triple to quadruple aim: care of the patient requires care of the provider.
Ann Fam Med. 2014 Nov-Dec;12(6):573-6. doi: 10.1370/afm.1713.
7
A comparison of phenotype definitions for diabetes mellitus.
J Am Med Inform Assoc. 2013 Dec;20(e2):e319-26. doi: 10.1136/amiajnl-2013-001952. Epub 2013 Sep 11.
8
Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory.
J Am Med Inform Assoc. 2013 Dec;20(e2):e226-31. doi: 10.1136/amiajnl-2013-001926. Epub 2013 Aug 16.

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