CHLPI clinical instructor Carmel Shachar is speaking at the 10AM panel, “Overcoming the Downsides of Big Data.”
“Big Data” is a phrase that has been used pervasively by the media and the lay public in the last several years. While many definitions are possible, the common denominator seems to include the “three V’s” – Volume (vast amounts of data), Variety (significant heterogeneity in the type of data available in the set), and Velocity (speed at which a data scientist or user can access and analyze the data).
Defined as such, health care has become one of the key emerging use cases for big data. For example, Fitbit and Apple’s ResearchKit can provide researchers access to vast stores of biometric data on users from which to test hypotheses on nutrition, fitness, disease progression, treatment success, and the like. The Centers for Medicare & Medicaid Services (CMS) have vast stores of billing data that can be mined to promote high value care and prevent fraud; the same is true of private health insurers. And hospitals have attempted to reduce re-admission rates by targeting patients that predictive algorithms indicate are at highest risk based on analysis of available data collected from existing patient records.
Underlying these and many other potential uses, however, are a series of legal and ethical challenges relating to, among other things, privacy, discrimination, intellectual property, tort, and informed consent, as well as research and clinical ethics.
This conference, and anticipated edited volume, will aim 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.