The Legal And Ethical Concerns That Arise From Using Complex Predictive Analytics In Health Care

Type Journal Article Author I. Glenn Cohen Author Ruben Amarasingham Author Anand Shah Author Bin Xie Author Bernard Lo URL http://content.healthaffairs.org/content/33/7/1139 Volume 33 Issue 7 Pages 1139-1147 Publication Health Affairs ISSN 0278-2715, 1544-5208 Date 07/01/2014 Extra PMID: 25006139 Journal Abbr Health Aff DOI 10.1377/hlthaff.2014.0048 Accessed 2016-11-09 23:47:52 Library Catalog content.healthaffairs.org Language en Abstract Predictive analytics, or the use of electronic algorithms to forecast future events in real time, makes it possible to harness the power of big data to improve the health of patients and lower the cost of health care. However, this opportunity raises policy, ethical, and legal challenges. In this article we analyze the major challenges to implementing predictive analytics in health care settings and make broad recommendations for overcoming challenges raised in the four phases of the life cycle of a predictive analytics model: acquiring data to build the model, building and validating it, testing it in real-world settings, and disseminating and using it more broadly. For instance, we recommend that model developers implement governance structures that include patients and other stakeholders starting in the earliest phases of development. In addition, developers should be allowed to use already collected patient data without explicit consent, provided that they comply with federal regulations regarding research on human subjects and the privacy of health information.