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Evaluation of a Sick Employee Online Log System for Tracking Sick Hospital Employees During Two Influenza Seasons

Published online by Cambridge University Press:  02 November 2020

William Cleve
Affiliation:
Vidant Medical Center
Kathy Cochran
Affiliation:
Vidant Medical Center
Keith M. Ramsey
Affiliation:
Vidant Medical Center
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Abstract

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Background: Since 2009, Vidant Health has used a Sick Employee Online Log (SEOL) system to track illnesses among employees and to capture this information in real time. The CDC assessed the 2017–2018 influenza season as a high-severity influenza season, whereas the 2018–2019 influenza season was of moderate severity. Objective: In this research project, we sought to determine whether the influenza season severity would affect either the hospital-based employee illness surveillance system results or would correlate with state influenza-like illness (ILI) visits. Methods: The SEOL system is an internet-based system initiated in December 2008. When a hospital employee calls in sick, the department manager records whether the employee reports the following symptoms: nausea, vomiting, diarrhea, upper respiratory infection, fever, sore throat, headache, conjunctivitis, rash, and/or cough. The information is confidential, with raw data access restricted to review by occupational health and infection control leadership. The correlation value was determined for each symptom using the North Carolina Division of Human Services (NC DHHS) percentage of ILI visits in statewide emergency departments.1 The data collection dates covered January 1–May 31 for each year. In this study, only symptoms related to influenza were included: upper respiratory infection, fever, influenza-like illness, cough and self-reported influenza. Correlation values were calculated using MS Excel software. Results: There were no breaks in confidentiality. All of the correlation values had a correlation value of 0.5 or better (Fig. 1), showing good correlation with the NC DHHS ILI data for both years; however, the more severe 2017–2018 influenza season had correlation values of 0.7 for all symptoms, versus 0.52–0.59 for URI and ILI, respectively, only during 2018–2019. Conclusions: The higher-severity influenza season did correlate with a higher r values when compared to North Carolina’s DHHS ILI emergency department data than did the influenza season of moderate severity. A possible explanation is that a higher-severity influenza season would correlate better than a moderate influenza season because it shows fewer ILI peaks and troughs. In conclusion, the SEOL system served as an early warning that influenza is present among our staff, and it correlates well with the state system for ILI surveillance. Potential limitations of SEOL are that respiratory symptoms are not specific to influenza; thus, they are subject to variation due to other respiratory viruses circulating among our employees.

1. The North Carolina Disease Event Tracking and Epidemiologic Collection Tool. NC DETECT website. http://www.ncdetect.org. Accessed Nov 8, 2019.

Funding: None

Disclosures: None

Type
Poster Presentations
Copyright
© 2020 by The Society for Healthcare Epidemiology of America. All rights reserved.