II. USING DATA
Being able to gather data is one step toward improving health—data needs
to be aggregated and shared in order to truly harness its power to shape health
by spotting trends not visible at an individual patient level. 64 At a global level,
harnessing even greater data can help identify trends regardless of whether
the payer is public or private and provide important tools for research, public
health, and preparedness. 65 But, for such public health and research efforts to
be successful, there needs to be greater harmonization between different
nations’ requirements for the collection and utilization of health
information. 66
A. Research collaborations
Health data has a broad range of uses. 67 For example, health data can be
used for medical research, population health, and healthcare delivery systems
improvement. 68 Interest in techniques such as data mining69 and “big data”
analytics70 may help improve health quality and lead to advances in
population health by identifying key trends. 71 When available, EHRs provide
“longitudinal, comprehensive, and interoperable” data and serve as a
“repository of electronically maintained information about an individual’s
64. Hiller, supra note 38, at 251 (“Big data, analytics, and predictive algorithms are poised
to play a large part in the transformation of health-care delivery in the United States,
determining who will benefit and, unfortunately, who may suffer from its insights. Health-care reform depends on cost savings derived from the application of sophisticated data
analytics to the ever-expanding mass of data collected from and about individual patients.”).
65. See generally A New Era for the Healthcare Industry, Cloud Computing Changes
the Game, ACCENTURE (2016), https://www.accenture.com/us-en/~/media/Accenture/Conv
ersion-Assets/DotCom/Documents/Global/PDF/Technology_2/Accenture-New-Era-
Healthcare-Industry-Cloud-Computing-Changes-Game.pdf.
66. Rebecca Li et al., Global Clinical Trials: Ethics, Harmonization & Commitments to
Transparency, 5 HARVARD PUB. HEALTH REV. 1, 6 (2015) (“The more that clinical trial
regulations differ from country to country, the more difficult it will be to establish common
approaches to current pressing ethical issues.”).
67. BEN GOLDACRE E T AL., WHO CONSULTA TION ON DA TA AND RESUL TS SHARING DURING
PUBLIC HEALTH EMERGENCIES: BACKGROUND BRIEFING 18 (Sept. 2015), http://www.
who.int/medicines/ebola-treatment/background_briefing_on_data_results_sharing_during_
phes.pdf (“There are also numerous policy initiatives around data sharing in science more
broadly, outside of emergency settings.”).
68. Id.
69. Bill Palace, What is data mining?, http://www.anderson.ucla.edu/faculty/jason.frand/
teacher/technologies/palace/ datamining.htm (last visited Nov. 11, 2016) (defining data mining
as the “process of analyzing data from different perspectives and summarizing it into useful
information . . . that can be used to increase revenue, cuts costs, or both”).
70. Joachim Roski, Creating Value in Health Care through Big Data: Opportunities and
Policy Implications, HEALTH AFFAIRS 1115, 1116 (2014) (attempting to define the term “big
data”).
71. ACCENTURE, supra note 65, at 14.
