2-Day Fall Workshop on Big Data for Health Policy – Sponsored by IHPME, SAS, and The Fields Institute

PRESENTING the second installment of the oversubscribed 2-Day Big Data Workshop, hosted at The Fields Institute.
November 5 @ 5:30 – 9:30pm
November 6 @ 8:00am – 5:00pm

The goal of this event’s keynote presentations will be to provide a broad view of the significance of Big Data for health policies, as well as setting the scene for the following day about the potential for research with linked data-sets.

Individual presentations the following day will capture relevant topics and will cast the net wide on issues such as social, education, biomedical data, environmental and population data and the strategies used in their analysis and dissemination. Topics will broadly include public health, health care, health human resources, social and education policy, environment, medicines and food and their relevance to health. We hope these presentations encourage collaboration in the policy arena.

We intend for this workshop to create new knowledge, inform future courses, and build new collaborations between researchers, analysts and decision-makers.

REGISTRATION DETAILS – CLOSED 

Registration: http://www.surveygizmo.com/s3/1700836/e-Registration-UofT-Summer-Workshop-on-Big-Data-for-Health
Presentation Registration: http://www.surveygizmo.com/s3/1705545/Presenters-Registration-Form-Big-Data-for-Health

BACKGROUND TO THE WORKSHOP

Health is much more than the absence of measurable disease. And health policy is much more than planning the delivery of healthcare. We know that the future health of Ontarians will be determined by a range of factors –social, economic, environmental and behavioral. The policies that shape these factors reach beyond the hospital and clinic and include education, nutrition, city planning, transport, recreation, environment social services and the economy, among others. A common thread that runs through these inter-connected themes is the need for reliable data to inform policy decisions, which are increasingly required to be justified by evidence and empirical data. This goes far beyond traditional health services and disease surveillance data to include all of domains that go on to affect health, directly or indirectly. Furthermore, data must be linkable – at the level of the individual or at a meaningful geographic or organizational level – so that the relationship on health and other outcomes can be empirically measured. This allows us to apply emerging methods to go above and beyond associations and to study causal mechanisms. Ontario is fortunate to have access to a wide and growing range of data-sets that are relevant and are becoming more accessible. Ontario is also home to many analytical and computing experts, who are contributing to the growing field of data science. Despite the opportunities, many challenges remain. For example, accessibility of the data is difficult for many researchers or policymakers and many are not aware of the range of data available. Other challenges relate to the awareness and knowledge of new and complex techniques that are used to analyze these large data files. Finally, the wide diversity of data needed to inform the broad aspects of health from social, to environmental, to medical, requires multidisciplinary expertise to both understand the components of the data and use the data in its appropriate context. The purpose of the second in our series of research workshops in ‘big data for health’ at the University of Toronto brings together data holders researchers analysts and policy makers to learn more about what is currently possible and what might be achievable in the future. We hope this workshop will create new knowledge, and build new collaborations between researchers, analysts and decision-makers.

Sponsored by SAS: Business Analytics and Business Intelligence Software THE POWER TO KNOW
and by The Institute for Health Policy, Management & Evaluation (IHPME)
Hosted at The Fields Institute for Research and Mathematical Sciences