Evaluating re-identification risks with respect to the HIPAA privacy rule

The problem addressed in the research is the risks of re-identification of de-identified health data of patients for an “attacker” via voter registration records.
Yes this problem is important because there is a danger of personal data being available to people who are not allowed to be in possession of it and may use it for identity theft. Also, unauthorized disclosure of personal health information may have adverse effects for the persons medical insurance, reputation, and employment.
The type of study of that was done was a case study.
The scope of the study to find a way to assess the risk using risk estimation metrics of likely re-identification cases.
The study was carried out in the department of biomedical informatics at Vanderbilt University in Nashville, TN. It was received by the Journal of American Medical Informatics Association on April 4th 2009. The research for this study was funded by grants from the Vanderbilt Stahlman Faculty Scholar program and the National Human Genome Research Institute.
The researcher makes the assumption that the “attacker” has access to all the identifying information on the de-identified population.
Limitations in this study are based upon the fact that each state has different policies on disclosing voter registration lists so it would be quite costly to conduct analysis on each state. Also, the estimates computed for the study were only as accurate as the population information was accurate because the information was provided by the 2000 Census. Also the 2000 Census was used as an estimate of the current population rather than the current population density.
I did not find any obstacles.
There was not a specific sample of people used other than in the 2000 Census data. The analysis was made based on information in the 2000 Census.
Risk estimation metrics were used as a statistical measure. Three separate equations were shown as being used to assess risk. The first was g-Distinct which measures an individuals uniqueness as compared to others in the population, the expected number of people in the population to be g-Distinct and the total risk equation. The equations and measures used were all explained.
This study raises a lot of anxiety that someone could potentially obtain other identifying information about me simply because I choose to vote in an election. The fact that there could be huge ramifications for oneself because they choose to vote and someone has unauthorized access to your information is a big problem.
The study relates indirectly to patient care because you want to evaluate how to keep a patients information confidential as a part of caring for them. A quality experience for a patient should be good care physically and also good care of their confidential medical information.
This study does contribute to outcome studies. It supports the hypothesis because it establishes an association between voter registries and de-identified data but does not take an actual sample and prove the hypothesis.
This study does apply to health informatics and health information management because it is essentially raising the question of how to protect health information from this new way of “attackers” being able to access patient information from voter registries and de-identified data?
This study is very helpful to those making and passing laws on who can get voter registry lists and helps those who are trying to protect patient information be aware of other ways “attackers” can obtain protected health information.

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