112. Sick Employee Online Log System for Tracking Employee Illnesses during the 2017-18 Influenza Season Provided Real-Time Surveillance and Early Detection of Influenza-Like Illnesses Among Employees
Session: Oral Abstract Session: Healthcare Epidemiology: Hot Topics
Thursday, October 4, 2018: 9:30 AM
Room: S 157

 

Background: Vidant Health is an 8-hospital, 1542-bed system (including the 908-bed teaching hospital for The Brody School of Medicine at East Carolina University) with over 12,000 employees, and uses a sick employee online log (SEOL) to track illnesses among employees.  Influenza-like illness (ILI) surveillance is collected from sentinel sites across the state of North Carolina (NC) by the Department of Health. Our goals were to determine the utility of the SEOL to monitor ILI among employees, and to compare trends with the NC ILI-system for Influenza surveillance.

Methods: When an employee calls in sick, symptoms for ILI in both the SEOL system and NC ILI-system include fever plus cough and/or sore throat. SEOL is an internet-based system, so information is collected and analyzed in real time. The number of sick hospital employees with influenza-like illness (ILI) per week during the 2017-2018 Influenza season was compared both to those employees reporting “Flu,” and to the NC ILI numbers from the sentinel sites using MS Excel.

Results: The data analyzed was from October 2017-April 2018. First, while lesser actual numbers of sick employees reported “Flu,” there was a correlation value of 0.93 between those reporting “Flu” and those reporting ILI symptoms (see Figure 1).  Secondly, the SEOL results are available daily, while the NC ILI-data is reported 7-12 days from entry; however, the peaks in ILI paralleled those of the peaks in SEOL data for employees reporting symptoms of ILI (see Figure 2) with a correlation value of 0.79 between the two. Finally, there were no breaks in confidentiality for those employees utilizing the SEOL.

Conclusion: The SEOL provided a real-time tool to monitor employee illnesses due to ILI during Influenza season, and without the lag time of the ILI-surveillance by the state. This system maintained confidentiality with a convenient method for data entry. These findings conclude that the SEOL system data correlated positively with the state ILI data, and provided an early detection system for the appearance of influenza among our employees.

 

Keith M. Ramsey, MD, FIDSA, FSHEA, M. Kathy Cochran, RN, MS, CIC and William Cleve, MT, MPH, Infection Control, Vidant Medical Center, Greenville, NC

Disclosures:

K. M. Ramsey, None

M. K. Cochran, None

W. Cleve, None

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