Flu Pandemic Initiative: building a rapid detection network for influenza
In the coming flu season, the Centers for Disease Control and Prevention (CDC) estimates that deaths related to the new influenza A (H1N1) virus could reach up to 90,000. With the next flu pandemic upon us, we must work together to improve how we monitor the disease.
The U.S. Department of Health and Human Services (HHS) and the CDC are collaborating with Cerner to create a Flu Pandemic Initiative, a secure, HIPAA-compliant, rapid detection network for H1N1.
The new initiative will supply each state’s public health department, Cerner clients and the CDC with situational awareness information to help triage resources. Through this Flu Pandemic Initiative, Cerner can provide public health organizations and Cerner clients with valuable, near real-time data to assist in monitoring health trends. Examples include elevated temperature as a percentage of emergency department visits in a geographic area, or percent of patients with influenza A labs ordered who are hospitalized immediately.
The initiative will not replace existing public health reporting requirements. Rather, it will help all participants and other public health organizations make decisions based on summarized information from a national, Cerner-based network of clinical systems. In addition, the network will help your organization and other Cerner clients become better prepared to handle H1N1 and meet new federal public health reporting requirements.
Cerner is committed to making this happen. We are funding all the direct costs for the network, and we are creating the technical platform to enable it. Your participation, however, is a key part of making this national initiative a success.
To learn how your organization can participate in this free initiative, email fluinitiative@cerner.com.
More Information:
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Summary-level data is available to participating organizations through our online reporting and collaboration tool, uCern. Your organization will have access to local and national data that is updated in near-real time.
