Protecting Your Genetic Identity: GINA and HIPAA

When launched in 1990, the Human Genome Project was heralded as a scientific endeavor that would provide answers to some of the most vexing questions about how genetic makeup influences human health. However, beyond the unquestionable benefits of the project, planners also foresaw the potential for misuse of genetic information. Thus, in an attempt to address the societal issues surrounding the genomic age, the Program Advisory Committee on the Human Genome established the Ethical, Legal, and Social Implications (ELSI) Working Group in 1989. The group still exists today, and it has a diverse membership that includes genome scientists; medical geneticists; law, ethics, and philosophy experts; and consumers. The ELSI Working Group sponsors research programs related to a number of areas, including genetic counseling, privacy, discrimination, education, and intellectual property. The group is also committed to exploring and proposing options for the development of sound professional and public policies related to human genome research and its applications. Among the most important of these proposals are those that involve legal protection of people's genetic information.

One of the initial problems the ELSI Working Group recognized was that studies identifying disease loci might allow insurers to compile a list of genetic risk factors that could be used to deny coverage to an increasing number of people. Of course, when genetic tests would have negative implications for coverage, the most likely consumer response would be to forgo the tests in order to remain insured. Thus, the ELSI Working Group believed that fear of insurance-related discrimination would lead to underutilization of genetic discoveries, thereby squandering the promise of the Human Genome Project. Indeed, a major goal of genomic research is to develop tests to identify risk factors for various diseases, especially those that are preventable or treatable.

In light of these concerns, the ELSI Working Group has been a vocal proponent of legislation such as the Genetic Information Nondiscrimination Act (GINA), which was signed into law in May 2008. This law bans U.S. employers from using genetic information in hiring, firing, promotion, and compensation decisions, as well as from collecting genetic information from employees. Furthermore, GINA prevents health plans and insurers from denying coverage or boosting premium prices based on a person's genetic information, including his or her family history. It also forbids these organizations from requesting or requiring people to undergo genetic testing.

Unfortunately, the very existence of federal legislation protecting genetic information might inadvertently foster apprehension of genetic testing. The hope is that GINA will provide enough protection to create an atmosphere in which the public feels safe to participate in genetic research, to pursue genetic testing for themselves, and to share the findings with family members who might also be at risk, as well as with health care providers who can help affected individuals treat or manage their conditions.

As previously mentioned, many individuals are afraid to undergo genetic testing for fear of potential genetic discrimination. But what is the basis of this fear, and is it justified? Historically, there have been a number of cases in which genetic information has been misused. For example, the eugenic movement in the United States in the early 1900s was based on the use of "genetic science," which claimed that complex social traits such as alcoholism, criminality, and depression were inherited in a simple fashion. This "science" was cited as justification for policies that restricted immigration into the U.S., as well as for state laws that permitted involuntary sterilization of criminals, mentally disabled individuals, and even unwed mothers. However, eugenics research was ultimately dismissed as significantly flawed, and the movement ceased by 1940.

In addition, there have been a few instances in which valid genetic data were used in a harmful manner. For instance, during the early 1970s, a number of African Americans who were known to be carriers for the mutation associated with sickle-cell anemia were denied insurance coverage or charged higher premiums (Andrews, 1987). Similarly, in 2002, a case settlement required the Burlington Northern and Santa Fe Railway Company to pay up to $2.2 million to employees who were secretly tested for a genetic variation purported to be associated with carpal tunnel syndrome (Burlington Northern and Santa Fe Railway Company, 2002). Although such examples of genetic discrimination remain relatively rare, they are troubling nonetheless.

Certainly, laws that protect genetic information are beneficial in that they help prevent instances of discrimination like those described in the previous paragraphs. But are there any disadvantages to these measures? To answer this question, it is first necessary to appreciate that some people consider genetic risk information to carry an additional, wider burden than medical information, because information about an individual's genetic health risks may also apply to that person's children, parents, siblings, and other relatives. One implication of this so-called "genetic exceptionalism" is that genetic research requires a heightened level of scrutiny compared with many other types of biomedical research.

Several measures exist to help provide this level of scrutiny, at least when it comes to traditional medical research. Specifically, a law called the Privacy Rule, implemented as part of the Health Insurance Portability and Accountability Act (HIPAA) in April 2003, established federal regulations for the use and disclosure of protected health information. Although the intention of these regulations was to further protect every individual's private medical information, the Privacy Rule has had an unforeseen negative impact on clinical, epidemiological, and genetic studies. Specifically, by complying with Privacy Rule regulations, research study offices incur significant cost increases (Armstrong et al., 2005). In addition, HIPAA restrictions on researchers have limited their ability to perform retrospective, chart-based research, as well as to prospectively evaluate patients through follow-up.

For example, before the Privacy Rule, the Cardiovascular Center of the University of Michigan had established a registry of patients to be contacted at certain intervals so doctors could learn more about their treatment outcomes for acute coronary syndrome. Initially, patients were contacted by phone and interviewed after giving their verbal consent. After the Privacy Rule went into effect, however, consent forms had to be mailed to eligible patients, and only those individuals who returned the forms could be contacted by phone for the interview. This change in policy resulted in a reduction in consent for follow-up from 96.4% before the Privacy Rule to 34.0% after its implementation. The Privacy Rule regulations also introduced selection bias in data collection, because only a subset of patients responded to mailed requests for review of their medical materials (Armstrong et al., 2005).

In a national survey of clinical epidemiologists in 2007, the HIPAA Privacy Rule was perceived to have a substantial, negative influence on health research involving human subjects, often adding uncertainty, cost, and delay (Ness, 2007). What is most frustrating to researchers is the absence of evidence that such regulations are making patient records more secure. Also problematic is the fact that the rules apply to any sample or record, even archived samples in which the patient (or surviving family members) may be impossible to track down for consent. What might be the cost to society of the studies that are not being conducted because of such hurdles to obtaining research material? And what is the most economical and fair way to protect an individual's privacy while meeting the public's need for better research-based medicine? The future challenge for policy makers lies in finding a solution that strikes an equitable balance between these two questions.