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Accelerating Public Health Surveillance Programs: A Case Study in Public-Private Partnerships

Jun 04, 2024

Utilizing data critical to helping public health leaders drive decision-making and targeted efforts to improve population health. Data used can be challenging to collect and are oftentimes months, and even years old, which may create challenges when trying to better understand current state. Additionally, these data usually require additional cleansing, analytics, and visualization efforts to turn into actionable insights. With timely, near real-time data, public health officials and policymakers can be better equipped to address community challenges and identify creative solutions to combat population health disparities.

Data-based initiatives and interventions needed to drive meaningful change cannot be done alone. If we want to be proactive on how we problem solve collectively within public health, newer and more creative approaches will need to be evaluated. A synergistic approach to partnerships is imperative to analyze community needs and develop solutions to challenges public health leaders face around data, analytics, and informatics.

Register for this webinar to learn how stronger and more synergistic partnerships between public health and private entities can help improve health outcomes across the country. Experts from the University of Mississippi, Quest Diagnostics and the CDC will share their data, analytics, and informatics strategies and partnership approach.

Learning Objectives:

1.) Overview of a University of Mississippi hepatitis clearance cascade and barriers faced with tracking and monitoring data outbreaks of infectious diseases.

2.) Understanding how a synergistic partnership between the CDC and Quest Diagnostics helped address these barriers and are helping to combat population health disparities nationwide.

3.) Awareness of solutions available to assist in challenges public health entities face around data, analytics, and informatics.

REGISTER HERE: Webinar Registration - Zoom


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