Reading List: Big Data and Health

August 4, 2014

The U.S. Chamber of Commerce Foundation has compiled a reading list for those interested in topics related to Big Data and data-driven innovation. This list includes articles from newspapers, magazines, websites, and academic journals. Many of the more notable articles are annotated.

The reading list is divided into 13 sections. (Read the full list here.)


The section below includes items offering an overview of Big Data and health. To add to the list, email


Big Data and Health

Association of the British Pharmaceutical Industry (2013) Big Data Road Map.

This report outlines a four-year plan to bring big data techniques to bear on the health care system in the U.K. While outline the challenges associated with large amounts of data, the report argues that big data can improve cost-savings, patient care and boost investment in related industries.

---- (2014) 360º of Health Data: Harnessing Big Data for Better Health.

Currie, J. (2013) “‘Big Data’ Versus ‘Big Brother’: On the Appropriate Use of Large-scale Data

Collections in Pediatrics,” Pediatrics Vol. 131 No. Supp. 2 pp. S127 -S132, April.

The Economist (2012). The Quantified Self: Counting Every Moment.”

Emam, E. et al. (2012) De-identification Methods for Open Health Data: The Case of the Heritage Health Prize Claims Dataset,” Journal of Medical Internet Research, vol. 14, issue 1.

Goetz, T. (2008) “Scanning Our Skeletons: Bone Images Show Wear and Tear.” Wired Magazine, June 23.

Harding, M. (2013) “Drinking Water Contamination in the United States and Why It Matters for

Infant Health,” Stanford Institute for Economic Policy Research July.

Harding, M. and Lovenheim, M. (2014) “The Effect of Prices on Nutrition: Comparing the Impact of Product- and Nutrient-Specific Taxes,” National Bureau of Economic Research Working Paper, January.

Huber, P. (2013) “The Digital Future of Molecular Medicine: Rethinking FDA Regulation,”

Project FDA Report, Manhattan Institute for Policy Research.

---- (2013) The Cure in the Code: How 20th century law is undermining 21st century medicine, Basic Books.

Institute for Health Technology Transformation (2013) Transforming Health Care through Big Data:  Strategies for leveraging big data in the health care industry

This report outlines beneficial applications of health care data in areas ranging from patient care and quality to clinical decision-making and operational efficiency. Special attention is given to the potential challenges faced by the health industry as it adopts these data-driven solutions.

Kayyali, B., Knott, D. Van Kuike, S. (2013) “The big-data revolution in US health care: Accelerating value and innovation,” McKinsey Global Institute, April.

Mcgregor, C., et al. (2011) “Next Generation Neonatal Health Informatics with Artemis.”

European Federation for Medical Informatics, User Centered Networked Health Care, Moen, A. et al. (eds.), IOS Press.

Mills, M. P. (2012) “With the Tricorder X PRIZE Qualcomm Launches the New Era of Metadata Medicine,” Forbes January.

---- (2012) “Tricorder Update: Social Medicine is the Next Big Thing after Social Media, Forbes May

---- (2013) ObamaCare and Regulatory Lock-In Threatens  the Biggest Healthcare Tech Revolution in History,” Forbes July.

---- (2012) The Solyndrafication of Healthcare Technology, Forbes, June 30.

Rubens, P. (2014) “Can Big Data Crunching Help Feed the World?” BBC Business, March.     

Salathé, M. and Khandelwal, S. (2011) “Assessing Vaccination Sentiments with Online Social Media.” PlOS Computational Biology 7, no. 10, October.

Ungerleider, N. (2013) “This May Be The Most Vital Use Of “Big Data” We’ve Ever Seen,” Fast Company, July

Van Nguyen, T. and Mishra, B. “Modeling Hospitalization Outcomes with Random Decision Trees and Bayesian Feature Selection.”

Weinberger, S. (2008) “Spotting the Hot Zones: Now we Can Monitor Epidemics Hour by Hour.” Wired Magazine, June.

Wiens, J., Guttag, J. Horvitz, E. (2014) “A Study in Transfer Learning: Leveraging Data  from Multiple Hospitals to Enhance Hospital‐Specific Predictions,” Journal of the American Medical Informatics Association, January .