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Data De-Identification

Definition - What does Data De-Identification mean?

Data de-indentification is a computing standard in which sensitive medical information contained in electronic health records (EHR) can be de-identified so that unauthorized users are unable to read the actual content since it is no longer in its original state. There are two types of data de-indeficiation and they are the statistical method which makes the EHR disconnected to the individual. The second type is deletion of the 18 most common identifiers. Some of these include:

  • Names
  • Cities, street numbers, etc.
  • Date elements such as birthdate, discharge date, etc.
  • Phone numbers
  • Social Security numbers
  • Medical record numbers
  • E-mail addresses

Techopedia explains Data De-Identification

The de-identifying of data is a proven method in which to de-identify patient data thus keeping it secure. With EHRs rapidly growing in usage throughout various health care institutions, facilities and private practices, privacy groups and legislators are akin to confidentiality assurance for all patients. Not considered the easiest of programming techniques, the data de-identification process can ironically make the designated data unprotected by current privacy laws. That is, once the data is de-identified, it is not considered actual protected medical data.

The way around this is to include a re-identification code. The information can only be re-identified, however, so long as the code is not identifiably connected to the individual for whom the EHR pertains. It should have no way of being translated to reveal their identity. The other strategy is to keep the code ultra-confidential. The person assigning the code must not use nor disclose the actual code for any other reasons other than to re-identify the information. As far as further instructions on de-identifying via statistical methods, the Department of Health and Human Services has these on their website. Done properly, statistical de-identifying should not be obvious.

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