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OS05 - Mining the Gold! (ID 6)
- Event: e-Health 2019 Virtual Meeting
- Type: Oral Session
- Presentations: 1
- Coordinates: 5/27/2019, 10:30 AM - 11:30 AM, Area 4
OS05.01 - Enhancing National-level Population Health Surveillance in Canada and U.S. (ID 175)
The use of new methodologies and technologies such as machine learning or artificial intelligence, combined with non-traditional data sources like mobile applications and social media, provide public health organizations with an opportunity to strengthen the processes currently used to understand and quantify the health of the populations they study. But given the volume and diversity of available options as well as the specialized expertise required to critically evaluate these options, it can be difficult for an organization to identify and test the optimal and most relevant set(s), types and sources of data for use in population monitoring.
Representatives from the Centers for Disease Control and Prevention (US), the Public Health Agency of Canada, Statistics Canada, and MaRS Discovery District will discuss their approach to innovating in public health surveillance. Panelists will describe their use of an incentive-based competition to directly engage with a diverse network of innovators from across the public-private spectrum, the benefits of this approach and their experience selecting and implementing successful solutions and prototypes.
Representatives will share lessons learned, best practices as well as the relevance and applicability of this approach to tackling a broad range of issues and gaps at other health institutions, government agencies and ministries.
New data channels and methodologies are underutilized in the public health sector. Yet the diversity of new data sources and collection mechanisms provides a rich set of options from which health and public health organizations can select and augment their current analytic processes. Within the health and public health context, data from novel sources can introduce a level of responsiveness, scalability and sensitivity that is currently lacking in many traditional reporting methodologies. More importantly, when combined with traditional data, data from these novel sources have the ability to provide researchers and public health agencies with a more detailed, comprehensive and less-episodic view into the determinants of health.
140 Character Summary:
Non-traditional data can supplement existing traditional public health data to enhance the process of creating forward-thinking public health policy.