The Louisiana Office of Public Health conducts ED syndromic surveillance using the Louisiana Early Event Detection System (LEEDS). Using outpatient data for syndromic surveillance is a relatively new concept, brought about due to the increasing use of EHRs and HIEs making such data readily available. Previously, there has been limited means of syndrome classification validation for the LEEDS data and the GNOHIE data has not been studied widely as a population sample, so this analysis and comparison is valuable on both fronts. Due to differences in the types of data (ADT messages from EDs and CCD from outpatient clinics), as well as different patient populations and site visit capability, the percentages of patients classified as ILI between data sets are unequal. The main focus of this analysis is determining whether the ILI classifiers applied to both data sets detect similar syndrome trends.
Each indicator used in the study represents the percentage of total patients seen that week who are classified as ILI cases. The study period covered the 13-14 influenza season, CDC week 1340 through 1420 (9/29/2013-5/17/2014). Two ILI classifiers were applied to both the GNOHIE and LEEDS data:the first classifier consisted of ICD-9 influenza codes and the second classifier consisted of keywords applied to encounter notes(GNOHIE data) and chief complaint, admit reason and diagnoses (LEEDS data). A graph of the data, below, shows the four data sets.
Objective
The goal of this analysis is to compare the results of influenza-like illness (ILI) text and International Classification of Diseases (ICD) code classifiers applied to the Louisiana Office of Public Health’s (OPH) syndromic surveillance data reported by New Orleans area emergency departments and the Greater New Orleans Health Information Exchange’s (GNOHIE) data reported by New Orleans area outpatient clinics.