In the early 2000s, handling genetic information as exceptional, including legal or regulatory protections, garnered strong support. It was argued that genomic information may need special policy and practice protections within the context of electronic health records (EHRs). In 2008, the Genetic Information Nondiscrimination Act (GINA) was enacted to protect patients from health insurance companies discriminating against an individual based on genetic information.
More recently it has been argued that genetic exceptionalism is past its expiration date as we move into a blended genomic/big data era of medicine, yet exceptionalism practices continue to permeate clinical healthcare today. Garrison et al. recently relayed a call to action to update verbiage from genetic exceptionalism to genomic contextualism in that we recognize a fundamental duality of genetic information. This allows room in the argument for different types of genetic information to be handled differently while acknowledging that genomic information is similar and yet distinct from other health-related information. Genomic contextualism would allow for a case-by-case analysis of the technology and the context of its use (e.g., clinical practice, research, secondary findings).
Others argue that genetic information is indeed distinct from other health-related information but not to the extent of requiring legal/regulatory protections, similar to other sensitive health-related data such as HIV status. Additionally, Evans et al. argue that the EHR has sufficient privacy standards to hold other sensitive information such as social security numbers and that the fundamental nature of an EHR is to house highly personal information. Similarly, a systematic review reported that the public had concern over privacy of genetic information, with 60% agreeing that maintaining privacy was not possible; however, 96% agreed that a direct-to-consumer testing company had protected their privacy, with 74% saying their information would be similarly or better protected in an EHR. With increasing technological capabilities in EHRs, it is possible to mask or hide genetic data from subsets of providers and there is not consensus on how, when, or from whom genetic information should be masked.  Rigorous protection and masking of genetic information is argued to impede further scientific progress and clinical translation into routine clinical practices.