C-D3-02: Syndromic Surveillance Reporting Via CDCs Public Health Information Grid

  • March 2010,
  • 54.2;
  • DOI: https://doi.org/10.3121/cmr.8.1.54-a

Abstract

Background: CDC is building a public health information grid to connect public health stakeholders nationwide. The grid will enable efficient and secure sharing of data and applications between public health authorities at the national, state, and local levels as well as researchers and other interested parties ( ). The grid may also support federated analysis of distributed data sources to detect clusters that might be invisible to smaller, isolated systems. Grid protocols allow data owners to control data access. Broad sharing of data, however, requires a model to customize the level of patient identifiers seen by users depending upon their role. We describe here a work-in-progress implementation of an ambulatory syndromic surveillance module on the public health grid, including a model for sharing reports with different levels of granularity depending upon user privileges.

Methods: We are installing a grid node at Atrius Health, a large multisite, multispecialty ambulatory medical practice serving over 600,000 patients predominantly in eastern Massachusetts. Standard CDC-defined ICD-9-and temperature-based syndrome algorithms developed for the National Bioterrorism Demonstration Project ( ) will be applied to ambulatory encounter data gathered nightly by the Electronic medical record Support for Public Health system (ESP, esphealth.org). ESP consists of a dedicated server populated with nightly extracts of comprehensive encounter data from the electronic medical record system of Atrius Health (JAMIA 2009:16:18). ESP currently analyzes this data to submit fully-identifiable case reports on patients with notifiable conditions to the state health department ( ). The syndromic surveillance addition to ESP will modify ESPs reporting module to vary the level of report granularity according to users’ access privileges. ESP reports will include fully de-identified aggregate counts stratified by time period and zip code for basic grid users; semi-identified unit records with age, gender, and geo-code for intermediate users; and fully identifiable unit records with patient names and addresses for highly privileged users such as the state health department.

Results: Installation is currently underway.

Conclusions: Controlled distribution of syndromic surveillance data through the CDC’s nascent grid will help develop the emerging paradigm for sharing public health information and applications.

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