 Ever wonder what tools epidemiologists use to identify epidemics? A new,
data-based tool developed by Dr. Raoul Ratard, Louisiana State Epidemiologist,
and Technology Engineers, looks for patterns of symptoms that, when taken together, might give
clues to potential public health threats, including epidemics. The process,
called Syndromic Surveillance, is implemented into a system called the Louisiana
Early Event Detection System, or LEEDS. It was developed for the Office of
Public Health, Louisiana Department of Health and Hospitals (OPH/DHH) by
Technology Engineers, and is
being implemented in hospitals throughout the state.
The U.S. Centers for Disease Control and Prevention
(CDC) describes syndromic
surveillance as “surveillance using health-related data that precede diagnosis
and signal a sufficient probability of a case or an outbreak to warrant further
public health response. Though historically syndromic surveillance has been
utilized to target investigation of potential cases, its utility for detecting
outbreaks associated with bioterrorism is increasingly being explored by public
health officials.” 1 The first two stages of the syndromic surveillance process
(data collection and statistical analysis) are performed by the LEEDS system.2
Syndromic Surveillance begins with aggregating raw data and reports from
multiple hospitals and public health units using the LEEDS Internet-based
patient complaint file collection system. Using rules and criteria identifying
pre-diagnostic and non-clinical disease indicators (that is, early events),
LEEDS applies algorithmic sequences and statistical analysis techniques to
monitor trends in syndromes of public health importance and rapidly detect
clusters of symptoms and health complaints that might indicate a disease
outbreak or other public health threat. Some of LEEDS prominent features are:
- Automated system that imports patient complaint files from multiple hospitals, internally processes the files, then maps the complaints to specific symptom and syndrome definitions.
- Retro-maps complaints to the current syndrome and symptom definition
- Archives complaint records
- Prints reports useful in monitoring trends of syndromes statewide and regionally
- Based on Service-Oriented Architecture (SOA), ASP.NET 3.5 technology and Oracle 10g database.
The system also has an integrated manual processing function that allows public health
officials to review and alter records before processing in order to bypass
non-pertinent validation rules where appropriate. Once data is in the system, DHH users can
create and retrieve a range of statistical analysis reports using combinations
of parameters. Reports can be filtered by date range, syndrome, hospital and
region. U.S. Emergency Department Visit statistics are also captured by the
system, giving analysts opportunities to compare Louisiana results to national
statistics.
Some additional features include code table maintenance, historical definitions, and an address book. These features allow OPH/DHH staff to modify and maintain the system through specially designed interfaces to update code data, input data, and internal staff data.
1. CDC. Syndromic Surveillance: an Applied Approach to Outbreak Detection,
Centers for Disease Control and Prevention, United States Department of Health
and Human Services, 2010.
2. CDC. Framework for Evaluating Public Health Surveillance Systems for Early
Detection of Outbreak recommendations from the guidelines working group. MMWR
May 7, 2004; 50(No. RR-13).
3. Ibid.
For more information on the Louisiana Department of Health and Hospitals please click here.
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