Big data has been defined as “[e]xtremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.”1 This term has been increasingly used for biomedical research. In this issue of JAMA, Dwyer-Lindgren and colleagues2 analyzed a data set that meets this definition to estimate differences in mortality from chronic respiratory diseases among US counties, based on small area estimation models involving more than 80 million US decedents over a 35-year period, from 1980 through 2014.3 The data presented provide interesting and important insights into chronic respiratory diseases and may identify some areas amenable to public health intervention.2
Mannino DM, Sanderson WT. Using Big Data to Reveal Chronic Respiratory Disease Mortality Patterns and Identify Potential Public Health Interventions. JAMA. 2017;318(12):1112–1114. doi:10.1001/jama.2017.11746
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