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临床记录匿名化与文本提取(CRATE):一个开源软件系统。

Clinical records anonymisation and text extraction (CRATE): an open-source software system.

作者信息

Cardinal Rudolf N

机构信息

Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Sir William Hardy Building, Downing Site, Cambridge, CB2 3EB, UK.

Cambridgeshire & Peterborough NHS Foundation Trust and Cambridge University Hospitals NHS Foundation Trust, Liaison Psychiatry Service, Box 190, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.

出版信息

BMC Med Inform Decis Mak. 2017 Apr 26;17(1):50. doi: 10.1186/s12911-017-0437-1.

Abstract

BACKGROUND

Electronic medical records contain information of value for research, but contain identifiable and often highly sensitive confidential information. Patient-identifiable information cannot in general be shared outside clinical care teams without explicit consent, but anonymisation/de-identification allows research uses of clinical data without explicit consent.

RESULTS

This article presents CRATE (Clinical Records Anonymisation and Text Extraction), an open-source software system with separable functions: (1) it anonymises or de-identifies arbitrary relational databases, with sensitivity and precision similar to previous comparable systems; (2) it uses public secure cryptographic methods to map patient identifiers to research identifiers (pseudonyms); (3) it connects relational databases to external tools for natural language processing; (4) it provides a web front end for research and administrative functions; and (5) it supports a specific model through which patients may consent to be contacted about research.

CONCLUSIONS

Creation and management of a research database from sensitive clinical records with secure pseudonym generation, full-text indexing, and a consent-to-contact process is possible and practical using entirely free and open-source software.

摘要

背景

电子病历包含有研究价值的信息,但也包含可识别且通常高度敏感的机密信息。一般而言,未经明确同意,患者可识别信息不得在临床护理团队之外共享,但匿名化/去识别化允许在未经明确同意的情况下对临床数据进行研究使用。

结果

本文介绍了CRATE(临床记录匿名化与文本提取),这是一个具有可分离功能的开源软件系统:(1)它对任意关系数据库进行匿名化或去识别化处理,其敏感度和精确度与之前类似系统相近;(2)它使用公共安全加密方法将患者标识符映射为研究标识符(化名);(3)它将关系数据库与用于自然语言处理的外部工具相连接;(4)它为研究和管理功能提供一个网络前端;(5)它支持一种特定模式,通过该模式患者可以同意就研究事宜被联系。

结论

使用完全免费的开源软件,通过安全化名生成、全文索引以及同意被联系的流程,从敏感临床记录创建和管理研究数据库是可行且实际的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/5405523/2faf568c7dd6/12911_2017_437_Fig1_HTML.jpg

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