Healthcare Consent and its Discontents (Part 1 of 3)

Not only is informed consent a joke flippantly perpetrated on patients; I expect that it has inspired numerous other institutions to shield themselves from the legal consequences of misbehavior by offering similar click-through “terms of service.” We now have a society where powerful forces can wring from the rest of us the few rights we have with a click. So it’s great to see informed consent reconsidered from the ground up at the annual conference of the Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School.

Petrie-Flom annual 2016 conference

Petrie-Flom annual 2016 conference

By no means did the speakers and audience at this conference agree on what should be done to fix informed consent (only that it needs fixing). The question of informed consent opens up a rich dialog about the goals of medical research, the relationship between researchers and patients, and what doctors have a right to do. It also raises questions for developers and users of electronic health records, such as:

  • Is it ethical to save all available data on a person?

  • If consent practices get more complex, how are the person’s wishes represented in the record?

  • If preferences for the data released get more complex, can we segment and isolate different types of data?

  • Can we find and notify patients of research results that might affect them, if they choose to be notified?

  • Can we make patient matching and identification more robust?

  • Can we make anonymization more robust?

A few of these topics came up at the conference. The rest of this article summarizes the legal and ethical topics discussed there.

The end of an era: IRBs under attack

The annoying and opaque informed consent forms we all have to sign go back to the 1970s and the creation of Institutional Review Boards (IRBs). Before that lay the wild-west era of patient relationships documented in Rebecca Skloot’s famous Immortal Life of Henrietta Lacks.

IRBs were launched in a very different age, based on assumptions that are already being frayed and will probably no longer hold at all a few years from now:

  • Assumption: Research and treatment are two different activities. Challenge: Now they are being combined in many institutions, and the ideal of a “learning heath system” will make them inextricable.

  • Assumption: Each research project takes place within the walls of a single institution, governed by its IRB. Challenge: Modern research increasingly involves multiple institutions with different governance, as I have reported before.

  • Assumption: A research project is a time-limited activity, lasting generally only about a year. Challenge: Modern research can be longitudinal and combine data sets that go back decades.

  • Assumption: The purpose for which data is collected can be specified by the research project. Challenge: Big data generally runs off of data collected for other purposes, and often has unclear goals.

  • Assumption: Inclusion criteria for each project are narrow. Challenge: Big data ranges over widely different sets of people, often included arbitrarily in data sets.

  • Assumption: Rules are based on phenotypal data: diagnoses, behavior, etc. Challenge: Genetics introduces a whole new set of risks and requirements, including the “right not to know” if testing turns up an individual’s predisposition to disease.

  • Assumption: The risks of research are limited to the individuals who participate. Challenge: As we shall see, big data affects groups as well as individuals.

  • Assumption: Properly de-identified data has an acceptably low risk of being re-identified. Challenge: Privacy researchers are increasingly discovering new risks from combining multiple data sources, a trend called the “mosaic effect.” I will dissect the immediacy of this risk later in the article.

Now that we have a cornucopia of problems, let’s look at possible ways forward.

Chinese menu consent

In the Internet age, many hope, we can provide individuals with a wider range of ethical decisions than the binary, thumbs-up-thumbs-down choice thrust before them by an informed consent form.

What if you could let your specimens or test results be used only for cancer research, or stipulate that they not be used for stem cell research, or even ask for your contributions to be withdrawn from experiments that could lead to discrimination on the basis of race? The appeal of such fine-grained consent springs from our growing realization that (as in the Henrietta Lacks case) our specimens and data may travel far. What if a future government decides to genetically erase certain racial or gender traits? Eugenics is not a theoretical risk; it has been pursued before, and not just by Nazis.

As Catherine M. Hammack said, we cannot anticipate future uses for medical research–especially in the fast-evolving area of genetics, whose possibilities alternate between exciting and terrifying–so a lot of individuals would like to draw their own lines in the sand.

I don’t personally believe we could implement such personalized ethical statements. It’s a problem of ontology. Someone has to list all the potential restrictions individuals may want to impose–and the list has to be updated globally at all research sites when someone adds a new restriction. Then we need to explain the list and how to use it to patients signing up for research. Researchers must finally be trained in the ontology so they can gauge whether a particular use meets the requirements laid down by the patient, possibly decades earlier. This is not a technological problem and isn’t amenable to a technological solution.

More options for consent and control over data will appear in the next part of this article.

About the author

Andy Oram

Andy Oram

Andy Oram writes and edits documents about many aspects of computing, ranging in size from blog postings to full-length books. Topics cover a wide range of computer technologies: data science and machine learning, programming languages, Web performance, Internet of Things, databases, free and open source software, and more. My editorial output at O'Reilly Media included the first books ever published commercially in the United States on Linux, the 2001 title Peer-to-Peer (frequently cited in connection with those technologies), and the 2007 title Beautiful Code. He is a regular correspondent on health IT and health policy for He also contributes to other publications about policy issues related to the Internet and about trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business.