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Public Health Surveillance and Informatics

Public Health Surveillance and Informatics. Michael Iademarco, MD, MPH Captain, U.S. Public Health Service , . Director , Center for Surveillance, Epidemiology and Laboratory Services CDC Georgia Tech Scientific Collaboration Meeting March 12 , 2014.

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Public Health Surveillance and Informatics

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  1. Public Health Surveillance and Informatics Michael Iademarco, MD, MPH Captain, U.S. Public Health Service , Director, Center for Surveillance, Epidemiology and Laboratory Services CDC Georgia Tech Scientific Collaboration Meeting March 12, 2014 Office of Public Health Scientific Services Office of the Director

  2. Partnership Opportunities • Big Data • How to use big data; approaches to CDC data • Variety of data from diverse sources • Diversity of systems, databases and stewards • Technical approaches to solve data challenges • Public Health Surveillance • Helping CDC see new ways of performing public health surveillance • Tools and techniques • HealthIT • Health Informatics approaches translated to public health • Efficient secondary use of clinical data • Novel Data

  3. Syndromic Surveillance • Systematic process of data collection and analysis • Goal to identify illness cluster early, before diagnosis confirmed • Numerous local systems • BioSense established as a national system, uses EMR data • Receives data feeds from 4,467 facilities; tracks 126 pre-defined syndromes • Uses: Deepwater Horizon, 2009-2010 H1N1 flu pandemic, Dengue fever in Florida and Hawaii

  4. Syndromic Surveillance: BioSense • Standardized tools and procedures • Distributed cloud computing environment • Challenges: environment development, flexible design • IT architecture expertise needed to evaluate the BioSenseplatform • Phenotype classification modeling and simulation applied to BioSense - needs to be able to model novel syndrome definitions

  5. National Notifiable Diseases Surveillance System • Certain diseases/conditions required by law to be reported to states; states voluntarily provide notifications to CDC • Data used to • Monitor disease trends • Assess effectiveness of prevention and control measures • Identify populations or geographic areas at high risk • Formulate prevention strategies • Develop PH policies, and, • Work with international community to identify and contain global outbreaks

  6. National Notifiable Diseases Surveillance System • Recently began a modernization initiative • Developing a robust technology infrastructure(CDC-Platform) • Based on interoperable, standardized data and exchange mechanisms; eventually cloud-based • Industrial engineering expertise needed to help assess and optimize the complex processes and systems being used for data exchange • Need for expertise in validation and tooling to help sharing with partners

  7. CMS Data • Data used to increase understanding of access to care, health care utilization, disease burden and health outcomes • Data accessed through CMS’ Virtual Research Data Center • Challenges: complex and requires use of analytic data management software, visualization tools and methods • There is a need to build capacity for big data analytics and to build aptitude and expertise • There is a need for enabling new types of analytics such as a Hadoop cluster would allow; need for testing

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