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国家跨辖区关联数据在线应用系统的开发与实施。

Development and implementation of a national online application system for cross-jurisdictional linked data.

机构信息

Population Health Research Network, University of Western Australia, Perth 6009, Australia.

Telethon Kids Institute, Perth 6009, Australia.

出版信息

Int J Popul Data Sci. 2022 Apr 27;7(1):1732. doi: 10.23889/ijpds.v6i1.1732. eCollection 2022.

DOI:10.23889/ijpds.v6i1.1732
PMID:35520098
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9052959/
Abstract

The Population Health Research Network (PHRN) is an Australian national data linkage infrastructure that links a wide range of health and human services data in privacy-preserving ways. The data linkage infrastructure enables researchers to apply for access to routinely collected, linked, administrative data from the six states and two territories which make up the Commonwealth of Australia, as well as data collected by the Australian Government. The PHRN is a distributed network where data is collected and managed at the respective jurisdictional and/or cross-jurisdictional levels. As a result, access to linked data from multiple jurisdictions requires complex approval processes. This paper describes Australia's approach to enabling access to linked data from multiple jurisdictions. It covers the identification of, and agreement to, a minimum set of data items to be included in a unified national application form, the development and implementation of a national online application system and the harmonisation of business processes for cross-jurisdictional research projects. Utilisation of the online application system and the ongoing challenges of data linkage across jurisdictions are discussed. Changes to the data custodian and ethics committee approval criteria were out of scope for this project.

摘要

人口健康研究网络(PHRN)是澳大利亚国家数据链接基础设施,以保护隐私的方式链接广泛的健康和人类服务数据。该数据链接基础设施使研究人员能够申请访问由构成澳大利亚联邦的六个州和两个地区以及澳大利亚政府收集的常规收集、链接的行政数据。PHRN 是一个分布式网络,数据在各自的司法管辖区和/或跨司法管辖区层面进行收集和管理。因此,需要复杂的审批流程才能访问来自多个司法管辖区的链接数据。本文介绍了澳大利亚从多个司法管辖区获取链接数据的方法。它涵盖了确定和同意将一组最小的数据项包含在统一的国家申请表中,开发和实施国家在线申请系统以及协调跨司法管辖区研究项目的业务流程。讨论了在线申请系统的利用情况以及跨司法管辖区数据链接的持续挑战。本项目不包括数据保管人和伦理委员会审批标准的更改。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2786/9052959/0d8359616a46/ijpds-06-1732-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2786/9052959/618b7b72c9dc/ijpds-06-1732-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2786/9052959/4ef817c5983b/ijpds-06-1732-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2786/9052959/0d8359616a46/ijpds-06-1732-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2786/9052959/618b7b72c9dc/ijpds-06-1732-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2786/9052959/4ef817c5983b/ijpds-06-1732-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2786/9052959/0d8359616a46/ijpds-06-1732-g003.jpg

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本文引用的文献

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The road to hell is paved with good intentions: the experience of applying for national data for linkage and suggestions for improvement.通往地狱之路是由善意铺成的:申请国家数据链接的经验及改进建议。
BMJ Open. 2021 Aug 19;11(8):e047575. doi: 10.1136/bmjopen-2020-047575.
2
The SPOR-Canadian Data Platform: a national initiative to facilitate data rich multi-jurisdictional research.加拿大SPOR数据平台:一项促进多辖区丰富数据研究的全国性倡议。
Int J Popul Data Sci. 2020 Nov 9;5(1):1374. doi: 10.23889/ijpds.v5i1.1374.
3
Accessing routinely collected health data to improve clinical trials: recent experience of access.
获取常规健康数据以改善临床试验:近期获取经验。
Trials. 2021 May 10;22(1):340. doi: 10.1186/s13063-021-05295-5.
4
The Population Health Research Network - Population Data Centre Profile.人群健康研究网络 - 人口数据中心简介
Int J Popul Data Sci. 2019 Nov 20;4(2):1130. doi: 10.23889/ijpds.v4i2.1130.
5
Factors influencing harmonized health data collection, sharing and linkage in Denmark and Switzerland: A systematic review.影响丹麦和瑞士协调健康数据收集、共享和链接的因素:系统评价。
PLoS One. 2019 Dec 12;14(12):e0226015. doi: 10.1371/journal.pone.0226015. eCollection 2019.
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Health data linkage research in Australia remains challenging.澳大利亚的健康数据关联研究仍然具有挑战性。
Intern Med J. 2019 Apr;49(4):539-544. doi: 10.1111/imj.14244.
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Nordic registry-based cohort studies: Possibilities and pitfalls when combining Nordic registry data.基于北欧注册库的队列研究:整合北欧注册库数据时的机遇与陷阱
Scand J Public Health. 2017 Jul;45(17_suppl):14-19. doi: 10.1177/1403494817702336.
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