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The increasing use of technology in health has enabled collection and storage of data at an exponential rate. Data is at the heart of “Health Analytics”, where it can be used to understand the current system, project the impact of changes, or evaluate and intervention. Data in healthcare data are scattered and fragmented, available from various sources, governmental or non-governmental health organizations, commercial or non-commercial, national wide or state wide; recorded at various aggregation temporal levels, event-level, monthly or yearly, and at various aggregation spatial levels, census tract, zip code, county, state or national; and with various levels of accuracy. Some data can be called “Big Data”, which is characterized by large Volume (from Terabytes to Exabytes) and Complexity (heterogeneity, depth, dimensionality, dependencies).
In our work, we use a variety of data sources (often combined), along with robust methodological tools from the mathematical sciences to move along a continuum from Information to Data to Knowledge to Decisions. Data can be useful in understanding 'Who, Where, What, or When' in the system.