This is a new elective course intended to introduce students to the many types of data and analytical methods now available that will enhance our ability to investigate and explain the health of communities. These include data that are relevant to measurement of the social economic and genetic determinants of health, the quality and outcomes of health care programs and health care interventions. The quantity and variety of relevant data have increased substantially in the last decade and now include data from: health care administration, electronic medical records, diagnostic laboratories, censuses, vital statistics, environmental exposures, disease and device registries, research data-bases and bio-repositories. To this may be added relevant information extracted from social services, taxation records, education, justice, and corrections services. This is a rapidly changing field. The aims of the course are to introduce students to the different types of data, to provide an overview of the different analytical approaches and to assess the potential value of these big data sets by examining a number of examples of their use.

Objectives: the aims of the course are to provide students with an overview of the different types of data, the different analytical approaches, and to assess the potential value of these big data sets by examining a number of examples of their use. 1) Taxonomy of health data, characteristics of structured and unstructured health data. 2) The value of individually linked data. 3) Different analytic approaches to 'wide' and 'deep' data. 4) Data security and privacy, data sharing, de-identification, and governance. 5) Working with distributed data networks. 6) Examples of the use of big data in health and health care. 7) Examples of the use of big data in policy evaluation.