Best practices for integrating big data into the everyday public health practice

The case for Big Data is clear; however the path to realizing the value is not. The challenge faced by public health is how to harness the value generated by Big Data to drive down disease incidence, increase the effectiveness of intervention programs, and identify at risk populations. This challenge is amplified for public health agencies, given the public health ecosystem is vast and comprised of hundreds of disparate systems and numerous analytical toolsets.

This talk will focus on how public health agencies can move Big Data from an abstract concept to a part of everyday public health practices. Fundamental to this transformation is the need for each public health agency to define a Big Data strategy that supports their mission and objectives. As an extension of the strategy, public health agencies must then carefully inventory and assess their data repositories. This is not a trivial task and requires careful assessment of the actual data versus the expected data. A Big Data roadmap can then be formed that implements the strategy based on the data available to the agency. Key to an achievable road map is walking before you run. Public health agencies have to start with Big Data projects where value can be realized in days and weeks versus months and years. This incremental approach provides agencies the opportunities to rapidly learn from their mistakes without disrupting the public health practice.

As public health agencies continuously execute the Big Data roadmap, they will build the best practices and repeatable processes that work for them based on their operational realities, available resources, and data sets.