Pay No Attention to Those Tens of Thousands of Women Affected by the Contraception Litigation

Photo: Hobby Lobby

Flickr/Creative Commons—m01229

By Gregory M. Lipper

In her latest column, Linda Greenhouse predicts that the Supreme Court’s order in Zubik v. Burwell will not produce the desired happy compromise between the government and the religious organizations who object to the government’s arranging for their students and staff to receive contraceptive coverage from third parties. Towards the end, Greenhouse also describes how the objectors have inaccurately insisted that these cases are about nuns and only nuns—ignoring the dozens of other plaintiffs whose students and staff number in the tens of thousands—and how legal commentators (some of whom should know better) have gone along:

[T]here is a widespread misunderstanding that the case is about nuns, specifically the Little Sisters of the Poor, a religious order whose mission is to run nursing homes for the elderly poor. Commentary following last week’s decision perpetuated this misunderstanding. “Surely the Obama administration could find a way to provide contraception to women without involving a group of Catholic nuns,” Ramesh Ponneru, a senior editor of National Review, wrote in a Bloomberg News post titled “The Culture War Obama Didn’t Have to Wage.” Richard W. Garnett, a law professor at the University of Notre Dame, wrote on Scotusblog that the Obama administration had “aggressively and unlawfully overreached” in its “strange insistence that a community of nuns who take vows of poverty and care for the elderly poor must serve as a vehicle for delivering free contraception to their employees.” In a Wall Street Journal column titled “Big Win for Little Sisters,” William McGurn wrote that “though it was more a TKO than a straight-up ruling, the Little Sisters prevailed at the Supreme Court Monday in their fight against the Obamacare contraceptive mandate.”

This single-minded focus on Little Sisters of the Poor—which itself employs hundreds of people of different religious faiths in multiple states—overlooked the tens of thousands of women who will lose contraceptive coverage if the objectors prevail:

By my count, the Little Sisters of the Poor (who, as I’ve noted before, advertise themselves as equal-opportunity employers in the nursing home enterprise) are only one of 30 petitioners in the seven Supreme Court cases. The other 29 include Catholic and Baptist colleges, Catholic high schools, individual bishops, two chapters of Catholic Charities, other charities, and several individuals.

If anything, there are more objectors and more affected women than even Greenhouse suggests.

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Use of Estimated Data Should Require Informed Consent

Guest post by Donna M. Gitter, Zichlin School of Business, Baruch College, based on Professor Gitter’s presentation at the Petrie-Flom Center’s 2016 Annual Conference, “Big Data, Health Law, and Bioethics,” held May 6, 2016, at Harvard Law School.

Cross-posted from the Hastings Center’s Bioethics Forum.

The Icelandic biotech firm deCODE Genetics has pioneered a means of determining an individual’s susceptibility to various medical conditions with 99 percent accuracy by gathering information about that person’s relatives, including their medical and genealogical records. Of course, inferences have long been made about a person’s health by observing and gathering information about her relatives. What is unique about deCODE’s approach in Iceland is that the company uses the detailed genealogical records available in that country in order to estimate genotypes of close relatives of individuals who volunteered to participate in research, and extrapolates this information in order to make inferences about hundreds of thousands of living and deceased Icelanders who have not consented to participate in deCODE’s studies. DeCODE’s technique is particularly effective in Iceland, a small island nation that, due to its largely consanguineous population and detailed genealogical records, lends itself particularly well to genetic research.

While Iceland’s detailed genealogical records enable the widespread use of estimated data in Iceland, a large enough U.S. database could be used to make similar inferences about individuals here. While the U.S. lacks a national database similar to Iceland’s, private companies such as 23andme and Ancestry.com have created rough gene maps of several million people, and the National Institutes of Health plans to spend millions of dollars in the coming years sequencing full genome data on tens of thousands of people. These databases could allow the development of estimated data on countless U.S. citizens.

DeCODE plans to use its estimated data for an even bolder new study in Iceland. Having imputed the genotypes of close relatives of volunteers whose DNA had been fully catalogued, deCODE intends to collaborate with Iceland’s National Hospital to link these relatives, without their informed consent, to some of their hospital records, such a surgery codes and prescriptions. When the Icelandic Data Protection Authority (DPA) nixed deCODE’s initial plan, deCODE agreed that it will generate for only a brief period a genetic imputation for those who have not consented, and then delete that imputation from the database. The only accessible data would be statistical results, which would not be traceable to individuals.

Are the individuals from whom estimated data is gathered entitled to informed consent, given that their data will be used for research, even if the data is putatively unidentifiable? In the U.S., consideration of this question must take into account not only the need for privacy enshrined in the federal law of informed consent, but also the right of autonomy, which empowers individuals to decline to participate in research. Although estimated DNA sequences, unlike directly measured sequences, are not very accurate at the individual level, but rather at the group level, individuals may nevertheless object to research participation for moral, ethical, and other reasons. A competing principle, however, is beneficence, and any impediment to deCODE using its estimated data can represent a lost opportunity for the complex disease genetics community.

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