De-identification of Data and Specimens

There are two important federal regulations related to the use of “individually identifiable health information.”

1. The first, the HIPAA Privacy Rule, restricts use of of protected health information (PHI) by a “covered entity.” HIPAA permits a covered entity to create information that is not individually identifiable by following specific standards for de-identification.

2. The second regulation, Protection for Human Subjects (45 CFR 46), also known as the Common Rule, outlines protections for individuals who participate in research, including protections related to data and specimens collected from individuals for both primary and secondary research. Research with data and specimens that are collected for another purpose (secondary research) must be de-identified to be considered not human subjects research.¹

According to the U.S. Department of Health and Human Services,

The process of de-identification, by which identifiers are removed from the health information, mitigates privacy risks to individuals and thereby supports the secondary use of data for comparative effectiveness studies, policy assessment, life sciences research, and other endeavors.

More information about HIPAA compliance is available on Fred Hutch’s IRB website.

Methods for creating de-identified datasets

The HIPAA Privacy Rule provides two methods for de-identification of PHI. The first method, expert determination, refers to expert application and evaluation of methods to de-identify data. The second, safe harbor, refers to removal of specific identifiers from a data set.

⚠️ While it is possible to de-identify your data yourself, unless you are an expert, we suggest that you seek out an expert to help you instead. There are nuances regarding privacy that you may miss without ample experience.

The “expert determination” method

The HIPAA Privacy Rule defines de-identification by expert determination as a process where a person with:

appropriate knowledge of and experience with generally accepted statistical and scientific principles and methods for rendering information not individually identifiable,

is able to apply these principles and methods to determine:

that the risk is very small that the information could be used, alone or in combination with other reasonably available information, by an anticipated recipient to identify an individual who is a subject of the information,

and where this person is able to document:

the methods and results of the analysis that justify such determination.

In summary, an expert in methods for de-identification can apply scientific and statistical principles to de-identify data as long as the risk of re-identification is very small, and must be able to document their methods and reasoning. More guidance on the expert determination method for de-identification is on the HHS website.

The “safe harbor” method

A data set is considered de-identified using the safe harbor method if the following identifiers are removed:

1. Names
2. Geographic subdivisions smaller than the state
3. All elements of dates (except the year); all ages over 89, including the year
4. Telephone numbers
5. Vehicle identifiers and serial numbers, including license plate numbers
6. Fax numbers
7. Device identifiers and serial numbers
8. Email addresses
9. Web Universal Resource Locators (URLs)
10. Social security numbers
11. Internet Protocol (IP) addresses
12. Medical record numbers
13. Biometric identifiers, including finger and voice prints
14. Health plan beneficiary numbers
15. Full-face photographs and any comparable images
16. Account numbers
17. Any other unique identifying number, characteristic, or code
18. Certificate/license numbers

Additionally, the remaining information can not be used, either alone or in combination with other information, to identify an individual in the data set. More guidance on using the safe harbor method for de-identification is on the HHS website.

Limited datasets

Similar to a de-identified data set, a limited data set excludes specific direct identifiers. However, a limited data set may include city, state, ZIP code, elements of a date (e.g. date of birth), and other characteristics or codes not listed as direct identifiers. Limited data sets may only be used for purposes of research, public health, and health care operations; and they are governed by a data use agreement. Unlike de-identified data sets, limited data sets are still considered to be PHI because they may contain identifiable information.

De-identification of biospecimens

The HIPAA Privacy Rule affects biospecimen resources when human specimens are accompanied by PHI. The Common Rule outlines when research studies involving biospecimens are considered human subjects research. Any research study where an “investigator obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens,” is considered human subjects research. Only secondary research involving coded private information and coded biospecimens is considered not human subjects research. See the Office of Human Research Protection’s guidance on biospecimens use in research for more information on when biospecimens are considered coded or non-identifiable.

Ethical considerations for use of de-identified data and specimens

The story of Henrietta Lacks, her descendants, and the creation of HeLa cells, acted as a catalyst for proposed policy changes around biospecimen use and started a broader public discussion around the ethics of genomic research, especially secondary research with specimens.^{2, 3} Recent studies have confirmed that genomic data can never be truly anonymized, and that it may be possible to re-identify seemingly de-identified data.^{2, 4} These ongoing public conversations and scholarly debates about the ethical issues associated with biospecimen research led to the proposal of major changes to the Common Rule, which would have considered biospecimens “inherently identifiable.”^{5, 6} Ultimately, the new Common Rule, which went into effect in 2018, maintained existing regulations around secondary biospecimen use, but continues to spark discussion around the individual autonomy and consent, harm and stigmatization of identified groups, and the public benefits of secondary research.^{4, 5, 7, 8, 9}

Other resources

Protecting Personal Health Information in Research: Understanding the HIPAA Privacy Rule, NIH Booklet (NIH Publication Number 03-5388).

Johns Hopkins Protecting Human Subjects Identifiers page.

ITCR Training Network: Ethical Data Handling for Cancer Research course, Chapter 3: De-identification.

References

1. Implementing regulatory broad consent under the revised common rule: Clarifying key points and the need for evidence. The Journal of Law, Medicine & Ethics. 2019;47(2):213-231. doi: https://doi.org/10.1177/1073110519857277. ↩

2. Beskow, L. M. (2016). Lessons from HeLa cells: the ethics and policy of biospecimens. Annual review of genomics and human genetics, 17, 395-417. doi: 10.1146/annurev-genom-083115-022536. ↩ ↩²

3. Callaway, E. (2013). HeLa publication brews bioethical storm. Nature, 1, 12689. Accessed at: https://www.nature.com/articles/nature.2013.12689. ↩

4. Lee, S. S. J. (2021). The ethics of consent in a shifting genomic ecosystem. Annual review of biomedical data science, 4, 145-164. doi: https://doi.org/10.1146/annurev-biodatasci-030221- 125715 ↩ ↩²

5. Spector-Bagdady K, Trinidad G, Kardia S, et al. Reported Interest in Notification Regarding Use of Health Information and Biospecimens. JAMA. 2022;328(5):474–476. doi:10.1001/jama.2022.9740 ↩ ↩²

6. Lynch, H., Wolf, L., & Barnes, M. (2019). Implementing Regulatory Broad Consent Under the Revised Common Rule: Clarifying Key Points and the Need for Evidence. Journal of Law, Medicine & Ethics, 47(2), 213-231. doi:10.1177/1073110519857277 ↩

7. Spector-Bagdady, K., Tang, S., Jabbour, S., Price, W. N., Bracic, A., Creary, M. S., … & Wiens, J. (2021). Respecting Autonomy And Enabling Diversity: The Effect Of Eligibility And Enrollment On Research Data Demographics: Study examines the effect of eligibility and enrollment on research data demographics. Health Affairs, 40(12), 1892-1899. doi: https://doi.org/10.1377/hlthaff.2021.01197 ↩

8. Spector‐Bagdady, K., & Beever, J. (2020). Rethinking the Importance of the Individual within a Community of Data. Hastings Center Report, 50(4), 9-11. doi:10.1002/hast.1112. ↩

9. Lee, S. S. J. (2021). Obligations of the “gift”: Reciprocity and responsibility in precision medicine. The American Journal of Bioethics, 21(4), 57-66. doi: 10.1080/15265161.2020.1851813 ↩