Accountability Act (HIPAA) Privacy Rule (such as participant name and date of birth) are reasonable identifiers that researchers should consider removing from their datasets when de-identifying them (USHHS, 2015a, 2015b).
The premise of de-identifying datasets is that by removing all personal identifiers, the participants’ identities likely cannot be determined by those who see the data. Even after datasets are de-identified, however, a slight risk remains that participants can be re-identified, if someone had the interest in and means to do so. Therefore, researchers and ethicists debate the extent to which data can truly be de-identified.
Typically researchers must de-identify their datasets when they plan to share them with researchers outside the original study team (such as for secondary data analysis), when the data are to be made publicly available, or when they prepare data for long-term storage. Adequately de-identifying datasets may take considerable effort, depending on the type of information collected. Numerous procedures exist for removing or masking identifiers in quantitative datasets. For example, a specific process is required for removing all HIPAA identifiers from quantitative datasets in research that must follow the HIPAA Privacy Rule (USHHS, 2015a, 2015b).
Processes for de-identifying qualitative data are not as straightforward. Overall, it is very difficult to de-identify qualitative data. Researchers typically modify easily-identifiable data in interview transcripts. For example, proper names said by the participant, such as “my friend Bob,” are removed and replaced with a general description (“my friend”) or a pseudonym. However, that step alone likely does not make qualitative data de-identified. Larger segments, including very specific or unusual experiences, may need to be redacted from transcripts to preserve participants’ identities. Social and behavioral scientists must therefore be mindful of the quality of their data—both quantitative and qualitative—if a large amount of stripping must be done to de-identify them, and whether the necessary context will still remain to allow for valid interpretations to be made by others.
When de-identifying data for sharing or storage, the master list linking personal identifiers to the study data does not necessarily have to be destroyed. Institutional review boards often allow the original researcher to maintain the master list that links the participants’ names to their identification numbers, but that list must be stored securely and not shared.
More questions? See #18, #20, and #24.
Question #20 What Makes Data Anonymous?
Data are anonymous when they are not linked to any participant identifiers. In other words, the identity of a participant cannot be determined through his or her data. If the data are truly anonymous, even the study team cannot determine participants’ identities. Researchers often choose to collect data anonymously for studies on stigmatized or illegal behaviors. Then, if unauthorized persons gain access to the data—or if the data were purposefully shared with other researchers for secondary analyses—participants’ identities could not be detected because identifying information was never collected or known by the researchers at all. Importantly, data do not need to be anonymous to be considered ethical; employing secure procedures for limiting a confidentiality breach of identifiable data is ethically sufficient. Only in certain situations where extra protections are needed is it preferable to collect data anonymously. However, some researchers—regardless of whether the research topic is sensitive or not—choose to collect data anonymously for a study because they do not need participants’ identifiers to answer their research questions.
If you want to collect data anonymously, you must consider several factors. First, your study design matters. Collecting anonymous data is likely an unrealistic option for research that requires data to be linked from multiple interactions with the same participant, such as in longitudinal research. In these situations, researchers should keep a master list linking participant names to their participant identification numbers so they can ensure that data are collected from the same participant at each time point. Participants can therefore be identified by anyone who has access to this list. Researchers who want their data to be anonymous should consider employing a study design that has only a single interaction with participants, such as a one-time interview or survey.
Second, consider how you are going to collect data. Collecting anonymous data is not possible when you (or another member of the research team) meet in person with a participant to conduct an interview or survey, for example. By conducting a face-to-face interview, you know what the person looks like and therefore can identify him or her, even if you do not know the participant’s name or have any other identifiers. Depending on the topic of the study, being identified as a participant (even without any disclosure of information discussed) could be potentially stigmatizing. For similar reasons, if a researcher wants to collect data anonymously, participants can neither be video recorded nor have their pictures taken because they can be visually identified. Data from audio-recorded interviews are also not considered anonymous because participants’ voices are unique, like fingerprints, and therefore considered identifiable.
Third, consider the kinds of data to be collected. For data to be anonymous, you cannot collect any information that can identify a participant. This information includes, for example, participant names, email addresses, and date of birth. Eighteen specific identifiers are listed in the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule (USHHS, 2015b). The Family Educational Rights and Privacy Act Regulations (FERPA) also provide a list of direct and indirect identifiers (USDE, 2017). Some identifiers may be unique to a particular study participant, such as a description of a tattoo, and when known, could identify the participant. A combination of identifiers when viewed together, such as ethnicity, sexual orientation, and age, could also reveal the identity of a study participant in some situations, especially when research is conducted in small towns or communities.
Data that were originally collected with personal identifiers can become anonymous data, in theory, if all personal identifiers are removed from the data and any documents linking identities and data are destroyed.
Ultimately, it may be difficult to collect data that are truly anonymous. Often researchers want to know identifying information to provide context to the data or to maintain long-term contact with participants. If you need to collect participant identifiers but are concerned about the negative implications of others potentially discovering the identities of participants in your research study, use strict procedures to protect the confidentiality of study data and consider obtaining verbal consent, so that participants’ names are not linked to the study though their signature on a consent form.
More questions? See #19, #23, and #25.
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