May 17, 2019 Breakthroughs in genetics have often raised complex ethical and legal questions, which loom ever larger as genetic testing is becoming more commonplace, affordable, and comprehensive and genetic editing becomes poised to be a consumer technology. As genetic technologies become more accessible to individuals, the ethical and legal questions around the consumer use of these technologies become more pressing. As these questions become more pressing, now is the time to re-consider what ethical and regulatory safeguards should be implemented and discuss the many questions raised by advancements in consumer genetics. Presentation: Jorge Contreras, Professor, College Of Law and Adjunct Professor, Human Genetics, University of Utah - Direct to Consumer Genetics and Data Ownership Learn more: https://petrieflom.law.harvard.edu/events/details/2019-petrie-flom-center-annual-conference

1. Jorge L. Contreras
May 17, 2019
S.J. Quinney College of Law
Dept. HumanGenetics, School of Medicine
University of Utah

2.  Concealment
 Dishonesty
 Hacking
 Negligence
 Profiteering

3.  Privacy
 Autonomy
 Institutional mistrust
 Human rights
 Free markets
 Wealth sharing
 Intermediary tolls
 Technical capability

4. “You always maintain ownership of your
data”
AncestryT&Cs, https://www.ancestry.com/cs/legal/termsandconditions
 Regain public trust
 Establish ground rules for data use
 White hat approach?

5.  There is no property (copyright) interest
in “mere facts”
 Facts are “as free as the air to common
use” (INS v. AP (1918, Brandeis, J.,
dissenting)
 Congress has consistently rejected
property-like protection for data from the
1880s-1990s
 Courts have refused to recognize (Moore,
Greenberg, Catalona)
 Question: Should a new property right in
health data be recognized by courts or
Congress?

6. Alaska Florida
Georgia
Louisiana
Colorado
Oregon
x
“[g]enetic
information is
the unique
property of the
individual
tested”
“[g]enetic information is
the unique property of
the individual to whom
the information pertains”

7. What would application of personal property rules
to individual health data look like?
(i.e., is this what property advocates really want?)

8.  Excludability
 Alienability and Divisibility
 Valuation and Compensation
 Unstewarded and “Orphan” Data
 Duration
 Tracking

9.  Research involves
▪ huge cohorts
▪ remixing and sharing data
▪ Purposes and goals unknown at time of data collection
 Property requires:
▪ individual “consent”?
▪ Per study? Blanket?
▪ Who to ask?
▪ Control groups?
▪ Population/epidemiological studies?
 Advance ex ante consent/permission (property
rule)
▪ Increased costs
▪ Decreased data
▪ Lower health outcomes overall
 Recognizing an individual property right in health
data could “cripple medical research”. Greenberg
v. Miami Childrens Hosp. (S.D. Fla. 2003)

10.  PCPs, first responders,
hospitals share health data
with:
 State disease registries
 Public health agencies (CDC)
 Drug/vaccine developers
 Limited by Propertization?
 Payment?
 Consent?
▪ What if patients are incapacitated?
Dead?
 Delay?

11.  Privacy
 Private actions
 Governmental enforcement (FTC)
 More?
 Research regulations
 Common Rule
 HIPAA Privacy Rule
 Research misconduct
 Non-discrimination
 Genetic Nondiscrimination Act of 2008
▪ Expand this?
 Contract
 Private enforcement
 Unconscionability backstop
 Tort and Other Relationship-Based Claims
 Breach of Fiduciary Duty (Moore v. Regents)

12.  Property regime creates unanticipated consequences
 Property creates a large bundle of rights
 Moderating property through L&E is a subtractive process
 More harm than good?
 Ex ante barriers to research (and possibly public health)
 Non-property protections already exist (and can be enhanced)
 Regulating data privacy/protection through specific rules (with a
tort liability backstop) is preferable
 More tailored
 Less likely to result in unintended consequences
 Resist IHI propertization

13.  Genetic Property, 106 Geo. L.J. 1 (2016)
 Informed consent results in property-like control
 Liability Rules for Health Data, Health Matrix (2019)
(with Francisca Nordfalk)
 Regulation and liability rules vs. property rules
 Case studies: Utah Pop. dB, Statistics Denmark
 The False Promise of Health Data Ownership, 94 NYU
L. Rev. (2019, forthcoming))
 Property as a flawed framework for health data
 DTC Genetics and Data Ownership (this conference)

14. Jorge L. Contreras
University of Utah
S.J. Quinney College of Law
Salt Lake City, UT
jorge.contreras@law.utah.edu
SSRN page: http://ssrn.com/author=1335192