The LEEDS application is a web-based system built for the Louisiana Department of Health and Hospitals. The goal of the system was to create one web-based application to replace the Excel and SAS based syndromic surveillance tools. Syndromic Surveillance is the collection and analysis of pre-diagnostic and non-clinical disease indicators using pre-existing electronic data with the purpose of monitoring trends in syndromes of public health importance and rapidly detecting clusters of symptoms and health complaints that might indicate a disease outbreak or other public health threat.

The system automatically imports and processes multiple hospitals’ emergency department data files and flags each patient record for syndromes by identifying key text strings and complaint codes within the records. System validation checks each data field in each record to ensure that all required fields are included and are formatted correctly. Any records that are rejected by the validation check are pushed back to the hospital for re-submittal. The program also incorporates a manual processing function which allows DHH users to review and alter records before processing, in order to bypass the validation. 

Once data has been brought into the system, DHH users have a multitude of reports to run statistics on various parameters. Reports can be filtered by date range, syndrome, hospital and region. U.S. Emergency Department Visit statistics are also captured by the system to enable reports to compare Louisiana statistics to national statistics.  Additional features included in the LEEDS system are code tables, retro mapping, historical definitions, and an address book. Code tables allow DHH users to alter data items and relationships throughout the system via a user-friendly interface. The retro mapping function is important in the LEEDS system due to the fact that syndrome definitions can be modified by DHH staff. Once the definition has been revised, the retro mapping feature runs through all records in the database and re-maps them according to the new data relationship. The historical definition feature allows DHH users to view all past syndrome definitions when determining whether or not a syndrome should be retro mapped. Finally, the system incorporates an address book which contains hospital staff contact information.

LEEDS can be accessed by both DHH staff and submitting hospital staff through DHH’s Single Sign-On. Hospital staff has limited access to the system, for which credentials are determined upon login. Hospital staff can access certain reports with limited filters in order to retrieve statistics for their hospital and region. 

LEEDS was built using ASP.NET 3.5 and the Oracle 9i database.