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BMC Medical Informatics and Decision Making

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Open Access 01-12-2017 | Software Review

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

Author: Rudolf N. Cardinal

Published in: BMC Medical Informatics and Decision Making | Issue 1/2017

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.

Caldicott F. Information: To share or not to share? The Information Governance Review [Internet]. UK Department of Health. 2013. Available from: https://www.gov.uk/government/publications/the-information-governance-review.

UK Department of Health. Confidentiality: NHS Code of Practice [Internet]. 2003. Available from: https://www.gov.uk/government/publications/confidentiality-nhs-code-of-practice.

UK General Medical Council. Good practice in research and Consent to research [Internet]. 2013. Available from: http://www.gmc-uk.org/Good_practice_in_research_and_consent_to_research.pdf_58834843.pdf.

NHS England. The NHS Constitution for England [Internet]. 2013. Available from: https://www.gov.uk/government/publications/the-nhs-constitution-for-england.

NHS England. The NHS Constitution for England [Internet]. 2015. Available from: https://www.gov.uk/government/publications/the-nhs-constitution-for-england.

Stewart R, Soremekun M, Perera G, Broadbent M, Callard F, Denis M, et al. The South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLAM BRC) case register: development and descriptive data. BMC Psychiatry. 2009;9:51.CrossRefPubMedPubMedCentral

Committee on Strategies for Responsible Sharing of Clinical Trial Data. Concepts and Methods for De-identifying Clinical Trial Data. Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk [Internet]. Washington: Board on Health Sciences Policy, Institute of Medicine; 2015. Available from: https://www.ncbi.nlm.nih.gov/books/NBK285994/.

UK Health and Social Care Information Centre. Anonymisation Standard for Publishing Health and Social Care Data Specification [Internet]. UK Health and Social Care Information Centre. 2013. Available from: http://webarchive.nationalarchives.gov.uk/+/http://www.isb.nhs.uk/documents/isb-1523/amd-20-2010/1523202010spec.pdf.

Garfinkel S. De-identification of personal information (NISTIR 8053) [Internet]. US National Institute of Standards and Technology. 2015. Available from: http://nvlpubs.nist.gov/nistpubs/ir/2015/NIST.IR.8053.pdf.

10.

Information Commissioner’s Office. Anonymisation: managing data protection risk: code of practice [Internet]. UK. 2012. Available from: https://ico.org.uk/media/1061/anonymisation-code.pdf.

11.

Uzuner O, Luo Y, Szolovits P. Evaluating the state-of-the-art in automatic de-identification. J Am Med Inform Assoc JAMIA. 2007;14:550–63.CrossRefPubMed

12.

Ferrández O, South BR, Shen S, Friedlin FJ, Samore MH, Meystre SM. Evaluating current automatic de-identification methods with Veteran’s health administration clinical documents. BMC Med Res Methodol. 2012;12:109.CrossRefPubMedPubMedCentral

13.

Fernandes AC, Cloete D, Broadbent MTM, Hayes RD, Chang C-K, Jackson RG, et al. Development and evaluation of a de-identification procedure for a case register sourced from mental health electronic records. BMC Med Inform Decis Mak. 2013;13:71.CrossRefPubMedPubMedCentral

14.

Neamatullah I, Douglass MM, Lehman LH, Reisner A, Villarroel M, Long WJ, et al. Automated de-identification of free-text medical records. BMC Med Inform Decis Mak. 2008;8:32.CrossRefPubMedPubMedCentral

15.

Erdal BS, Liu J, Ding J, Chen J, Marsh CB, Kamal J, et al. A database de-identification framework to enable direct queries on medical data for secondary use. Methods Inf Med. 2012;51:229–41.CrossRefPubMed

16.

van Rossum G. Python reference manual [Internet]. Centrum voor Wiskunde en Informatica, Report No.: CS-R9525. 1995. Available from: http://www.python.org/.

17.

Gosling J, Joy B, Steele G, Bracha G, Buckley A. The Java Language Specification. Java SE 8 Edition. [Internet]. Oracle Corporation. 2015. Available from: https://docs.oracle.com/javase/specs/jls/se8/jls8.pdf.

18.

Torvalds L. Linux [Internet]. 1991. Available from: http://www.linuxfoundation.org/.

19.

Canonical. Ubuntu 14.04 [Internet]. 2014. Available from: http://www.ubuntu.com/.

20.

Microsoft Corporation. Windows 10 [Internet]. 2015. Available from: http://windows.microsoft.com/.

21.

Bayer M. SQLAlchemy [Internet]. 2016. Available from: http://www.sqlalchemy.org/.

22.

Cunningham H, Tablan V, Roberts A, Bontcheva K. Getting more out of biomedical documents with GATE’s full lifecycle open source text analytics. PLoS Comput Biol. 2013;9:e1002854.CrossRefPubMedPubMedCentral

23.

Jiang M, Wu Y, Shah A, Priyanka P, Denny JC, Xu H. Extracting and standardizing medication information in clinical text - the MedEx-UIMA system. AMIA Joint Summits on Translational Science Proceedings. 2014;2014:37–42.

24.

Django Software Foundation. Django [Internet]. 2016. Available from: https://www.djangoproject.com/.

25.

Chesneau B. Gunicorn 19.3.0 [Internet]. 2016. Available from: http://gunicorn.org/.

26.

The Apache Software Foundation. Apache HTTP Server 2.4.20 [Internet]. 2016. Available from: https://httpd.apache.org/.

27.

McDonough C. Supervisor: a process control system, version 3.0b2 [Internet]. 2016. Available from: http://supervisord.org/.

28.

Solem A. Celery 3.1.23 [Internet]. 2016. Available from: http://www.celeryproject.org/.

29.

Pivotal Software. RabbitMQ 3.6.1 [Internet]. 2016. Available from: https://www.rabbitmq.com/.

30.

The CherryPy Team. CherryPy 5.1.0 [Internet]. 2016. Available from: http://www.cherrypy.org/.

31.

Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule [Internet]. US Code Fed. Regul. Title 45 Parts 160 162 164. Available from: https://www.hhs.gov/sites/default/files/ocr/privacy/hipaa/administrative/combined/hipaa-simplification-201303.pdf

32.

Kleene SC. Representation of Events in Nerve Nets and Finite Automata. In: Shannon CE, McCarthy J, editors. Automata Studies. Princeton: Princeton University Press; 1956. p. 3–42.

33.

Barnett M. regex 2015.11.14 [Internet]. 2015. Available from: https://pypi.python.org/pypi/regex; https://bitbucket.org/mrabarnett/mrab-regex.

34.

Ling X, Weld D. Temporal information extraction. AAAI-10 Proc. Twenty-Fourth AAAI Conf. Artif Intell. 2010;2010:1385–90.

35.

MySQL. InnoDB FULLTEXT Indexes [Internet]. Oracle Corporation. 2013. Available from: https://dev.mysql.com/doc/refman/5.6/en/innodb-fulltext-index.html.

36.

Kennedy S, Willadsen K. Meld 1.8.4 [Internet]. 2013. Available from: http://meldmerge.org/.

37.

Bellare M, Canetti R, Krawcyk H. Keying hash functions for message authentication. Lect Notes Comput Sci Adv Cryptol - Crypto 96 Proc. 1996;1109:1–15.

38.

Preneel B. The First 30 Years of Cryptographic Hash Functions and the NIST SHA-3 Competition. In: Pieprzyk J, editor. Topics in Cryptology - CT-RSA 2010. CT-RSA 2010. Lecture Notes in Computer Science, vol 5985. Springer, Berlin, Heidelberg; 2010. p. 1–14. Available from: http://link.springer.com/chapter/10.1007/978-3-642-11925-5_1.

39.

MySQL. RENAME TABLE Syntax. Oracle Corporation. 2013. Available from: https://dev.mysql.com/doc/refman/5.6/en/rename-table.html.

40.

Iqbal E, Mallah R, Jackson RG, Ball M, Ibrahim ZM, Broadbent M, et al. Identification of Adverse Drug Events from Free Text Electronic Patient Records and Information in a Large Mental Health Case Register. PLoS One. 2015;10:e0134208.CrossRefPubMedPubMedCentral

41.

Cardinal RN. CRATE source code [Internet]. 2016. Available from: https://github.com/RudolfCardinal/crate.

42.

Cardinal RN. CRATE Python package [Internet]. 2016. Available from: https://pypi.python.org/pypi/crate-anon.

43.

University of Sheffield. GATE: General Architecture for Text Engineering [Internet]. 2016. Available from: https://gate.ac.uk/.

44.

van Os A. Antiword [Internet]. 2005. Available from: http://www.winfield.demon.nl/.

Title: Clinical records anonymisation and text extraction (CRATE): an open-source software system
Author: Rudolf N. Cardinal
Publication date: 01-12-2017
Publisher: BioMed Central
Published in: BMC Medical Informatics and Decision Making / Issue 1/2017
Electronic ISSN: 1472-6947
DOI: https://doi.org/10.1186/s12911-017-0437-1

At a glance: The STEP trials

Springer Medicine

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

Abstract

Background

Results

Conclusions

At a glance: The STEP trials

Springer Medicine

Abstract

Background

Results

Conclusions

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