Louisiana Early Event Detection System
Detecting epidemics in the early stages of an outbreak
The Louisiana Department of Health (LDH)’s Infectious Disease Epidemiology Section needed help to enhance existing legacy information and data collection systems, as well as develop specialized systems for identifying and tracking outbreaks of infectious and communicable diseases across the state.
The result—the Louisiana Early Event Detection System (LEEDS)—has three main components: the data transfer component, the data analysis processing component, and the reporting component encompass.
With the click of a button, LEEDS automatically ingests emergency room and urgent care data from hundreds of facilities across the state and processes that information into standardized report, which helps public health officials detect epidemics in the early stages of an outbreak. What used to take weeks to process can now be done in minutes.
In initial meetings, TEI analysts consulted with the principal LDH management staff to evaluate existing processes and understand requirements for each proposed system. Existing manual processes, which had been used by the LDH and hospital staff for years, needed to be streamlined. Under the direction of our Chief Software Architect, our analysts developed intuitive browser designs for the four most critical systems used by the Epidemiology Section. They then created unique algorithms using Microsoft’s ASP.Net architecture for use with the existing database, improving overall system functionality. Throughout our contract period, we relied on our agile development methodologies to design, program, and new processes and further enhance existing ones.
TEI migrated the LEEDS database to SQL server from Oracle, increased batch processing speed, added user account management, and updated the system to acceptance and intake of HL7 files. These enhancements expanded the usability of LEEDS, allowing it to accept data from 300 additional emergency care facilities across the state.
The data analysis processing component is a data extraction and transformation tool that allows the program administrator the ability to configure analysis algorithm settings, schedule data loads, review processing results and resolve data discrepancies before the data’s integration into the reporting component. The data is transformed based on disease tracking algorithms into a series of standardized reports for the hospitals and program administrators.