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APHA Scientific Session and Event Listing

Recorded presentation

Christine Adamski, MSN¹, Karla R. Armenti, ScD², and David J. Swenson². (1) New Hampshire Department of Health and Human Services, Communicable Disease Surveillance Section, 29 Hazen Drive, Concord, NH 03301, (2) New Hampshire Department of Health and Human Services, Health Statistics and Data Management Section, 29 Hazen Drive, Concord, NH 03301, (603) 271-7366, dswenson@dhhs.state.nh.us

Background: The Automated Hospital Emergency Department Data (AHEDD) System was designed for early statewide detection of bioterrorism and naturally occurring health risks. Initial development includes real-time data collection from four pilot hospitals, an automated syndromic surveillance application, and raw data analysis for further investigation and follow-up. The system was designed to free hospital and State staff from manual reporting and analysis; and has a broad application for Public Health, collecting both chief complaint and diagnosis codes. As the project expands we will examine poisoning, asthma, and injury surveillance; electronic disease reporting from diagnosis codes; and data linkage with the Environmental Health Tracking Program.

Method: Real-time transmissions from the four hospitals are loaded into an Oracle database; an automated Java-based surveillance system charts emergency department chief complaints and diagnosis codes in eight syndromes by hospital, town, county, and state. A signal alert is determined by a syndrome count that exceeds its thirty-day baseline by three standard deviations. Access to raw data empowers State Clinical and epidemiological staff with greater investigation capacity resulting in decreased hospital follow-up.

Results: The system runs in parallel with existing infectious disease surveillance applications allowing comparison and validation, and has proven sensitive in the detection of alert signals. Epidemiological staff internally investigated and closed a constitutional spike case due to clinic flu shots and respiratory and gastrointestinal spike cases due to Monday holiday activity after Christmas and New Years day. Soon hospitals will be able to view their syndrome charts and receive real-time data discrepancy feedback.

Learning Objectives: At the conclusion of the session, the participant (learner) in this session will be able to

• Describe how chief complaints and diagnosis codes are used to detect disease alert signals in the AHEDD syndromic surveillance system.
• Articulate how disease alert signals are investigated and resolved.
• Describe the importance of access to raw data for investigation.
• Describe the utility of an automated syndromic surveillance system in early detection of bioterrorism and naturally occurring health risks.

Keywords: Data Collection, Data/Surveillance

Presenting author's disclosure statement:

Any relevant financial relationships? No

Recorded presentation