Research using electronic health records: not all de-identified datasets are created equal
Vithya Yogarajan 1 , Rajan Ragupathy 2 3
+ Author Affiliations
- Author Affiliations
1 Department of Computer Science, The University of Waikato, Hamilton, New Zealand
2 Pharmacy Services, Waikato District Health Board, Hamilton, New Zealand
3 Corresponding author. Email: rajan.ragupathy@gmail.com
Journal of Primary Health Care 11(1) 14-15 https://doi.org/10.1071/HC19010
Published: 3 April 2019
Journal Compilation © Royal New Zealand College of General Practitioners 2019.
This is an open access article licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
[1] Wallis K, Eggleton K, Dovey S, et al. Research using electronic health records: balancing confidentiality and public good. J Prim Health Care. 2018; 10 288–91.| Research using electronic health records: balancing confidentiality and public good.Crossref | GoogleScholarGoogle Scholar |
[2] O’Keefe CM, Connolly CJ. Privacy and the use of health data for research. Med J Aust. 2010; 193 537–41.
| 21034389PubMed |
[3] Yogarajan V, Mayo M, Pfahringer B. Privacy protection for health information research in New Zealand district health boards. N Z Med J. 2018; 131 19–26.
| 30408815PubMed |
[4] United States Department of Health and Human Services. Guidance regarding methods for de-identification of protected health information in accordance with the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule. HHS.gov. [cited 2019 January 31]. Available from: https://www.hhs.gov/hipaa/for-professionals/privacy/special-topics/de-identification/index.html
[5] Office of the Privacy Commissioner. Comparison paper on health privacy laws. Privacy Commissioner. [cited 2019 January 31]. Available from: https://www.privacy.org.nz/news-and-publications/books-and-articles/comparison-paper-on-health-privacy-laws-2/
[6] Rumbold JMM, Pierscionek B. The effect of the general data protection regulation on medical research. J Med Internet Res. 2017; 19 e47
| The effect of the general data protection regulation on medical research.Crossref | GoogleScholarGoogle Scholar |
[7] Brasher E. Addressing the failure of anonymization: Guidance from the European Union’s General Data Protection Regulation. Columbia Business Law Review Vol. 2018, Issue 3, 2018. [cited 2019 January 31]. Available from: https://cblr.columbia.edu/addressing-the-failure-of-anonymization-guidance-from-the-european-unions-general-data-protection-regulation/
[8] Polonetsky J, Tene O, Finch K. Shades of gray: seeing the full spectrum of practical data de-identification. Santa Clara Law Rev. 2016; 56 593–629.
[9] Yogarajan V, Pfahringer B, Mayo M. Automatic end-to-end de-identification: is high accuracy the only metric? Computers and Society, Cornell University. arXiv:1901.10583 [cs.CY]. [cited 2019 January 31]. Available from: https://arxiv.org/pdf/1901.10583.pdf
[10] Ragupathy R, Yogarajan V. Applying the Reason Model to enhance health record research in the age of ‘big data’. N Z Med J. 2018; 131 65–7.
| 30001309PubMed |
