Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Sharona Hoffman, "Big Data and the Americans with Disabilities Act: Amending the Law to Cover Discrimination Based on Data-Driven Predictions of Future Illnesses"

310 views

Published on

Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.

This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.

The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.

Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.

Published in: Healthcare
  • Be the first to comment

  • Be the first to like this

Sharona Hoffman, "Big Data and the Americans with Disabilities Act: Amending the Law to Cover Discrimination Based on Data-Driven Predictions of Future Illnesses"

  1. 1. BIG DATA AND THE AMERICANS WITH DISABILITIES ACT PROFESSOR SHARONAHOFFMAN CASE WESTERN RESERVEUNIVERSITY
  2. 2. HOW EMPLOYERS OBTAIN MEDICAL BIG DATA • TRADITIONAL -MEDICAL EXAMINATIONS AND INQUIRIES • SOCIAL MEDIA • WELLNESS PROGRAMS • DATA BROKERS
  3. 3. DATA DE-IDENTIFICATION • RISK OF RE-IDENTIFICATION CANNOT BE COMPLETELY ELIMINATED • DE-IDENTIFIED DATA ITSELF CAN ALLOW EMPLOYERS TO DETERMINE THAT CERTAIN ATTRIBUTES ARE UNDESIRABLE
  4. 4. DISEASE PREDICTION • CAUSAL LINK BETWEEN BEHAVIORS OR TRAITS AND DISEASE VULNERABILITY • BIOMARKERS • DATA ALGORITHMS • OTHER PREDICTORS – E.G. BICYCLE PURCHASES, VOTING, CREDIT SCORES
  5. 5. THE AMERICANS WITH DISABILITIES ACT • DEFINITION OF “DISABILITY” • PHYSICAL OR MENTAL IMPAIRMENT THAT SUBSTANTIALLY LIMITS ONE OR MORE MAJOR LIFE ACTIVITIES • RECORD OF SUCH IMPAIRMENT • BEING REGARDED AS HAVING IMPAIRMENT
  6. 6. RECOMMENDED ADA REVISIONS • EXPAND “REGARDED AS” PROVISION TO PROTECT INDIVIDUALS PERCEIVED AS LIKELY TO DEVELOP PHYSICAL OR MENTAL IMPAIRMENT IN FUTURE • CONSISTENT WITH GENETIC INFORMATION NONDISCRIMINATION ACT (GINA)
  7. 7. RECOMMENDED ADA REVISIONS • EXCEPTIONS FOR RISK-TAKING BEHAVIORS (SMOKING, EXCESSIVE DRINKING) • NO EXCEPTION FOR OBESITY • DISCLOSE DATA MINING PRACTICES

×