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Electronic Syndromic Surveillance for Influenza-Like Illness Across Treatment Settings

Published online by Cambridge University Press:  19 December 2016

Jessica P. Ridgway*
Affiliation:
Department of Medicine, University of Chicago, Chicago, Illinois
Diane Lauderdale
Affiliation:
Department of Public Health Sciences, University of Chicago, Chicago, Illinois
Ronald Thisted
Affiliation:
Department of Public Health Sciences, University of Chicago, Chicago, Illinois
Ari Robicsek
Affiliation:
Department of Medicine, University of Chicago, Chicago, Illinois Department of Clinical Analytics, NorthShore University HealthSystem, Evanston, Illinois
*
Address correspondence to Jessica P. Ridgway, University of Chicago, 5841 S. Maryland Ave, MC 5065, Chicago, IL 60637 (jessica.ridgway@uchospitals.edu).

Abstract

OBJECTIVE

Syndromic surveillance for influenza-like illness (ILI) is predominantly performed in the outpatient setting. The objective of this study was to compare patterns of ILI activity in outpatient, emergency department (ED), and inpatient settings using an electronic syndromic surveillance algorithm.

DESIGN

Retrospective cohort study over 7.5 years.

SETTING

A large community health system comprised of 5 hospitals and >50 clinics.

METHODS

We applied an electronic syndromic surveillance algorithm for ILI to all primary-care outpatient visits, inpatient encounters, and ED encounters at our health system. Comparisons of ILI activity over time were performed using Spearman’s rank correlation coefficient. Cross correlation was used to compare the timing of ILI activity among treatment settings.

RESULTS

Overall, 4,447,769 patient encounters occurred during the study period; 152,607 of these (3.4%) were consistent with ILI. The correlation coefficient for ILI activity in the outpatient versus ED setting was 0.877, and for the outpatient versus inpatient setting, the correlation coefficient was 0.699. ILI activity among outpatients preceded ILI activity among inpatients by 1 week. ILI activity among children in the outpatient setting preceded ILI activity among adults in all 3 settings by 1 week.

CONCLUSIONS

Syndromic surveillance for ILI in the outpatient setting yields similar results to surveillance in the ED setting, but it produces less similar results than ILI surveillance in the inpatient setting. ILI activity in the pediatric outpatient population is a potential predictor of future ILI activity in the general population.

Infect Control Hosp Epidemiol 2017;38:393–398

Type
Original Articles
Copyright
© 2016 by The Society for Healthcare Epidemiology of America. All rights reserved 

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Footnotes

PREVIOUS PRESENTATION: Preliminary data from this study were previously presented at IDWeek, October 10, 2014 in Philadelphia, Pennsylvania.

References

REFERENCES

1. Overview of influenza surveillance in the United States. Centers for Disease Control and Prevention website. http://www.cdc.gov/flu/weekly/overview.htm. Published 2015. Accessed November 15, 2016.Google Scholar
2. Electronic syndromic surveillance using hospital inpatient and ambulatory clinical care electronic health record data: recommendations from the ISDS meaningful use workgroup. International Society for Disease Surveillance website. http://www.syndromic.org/meaningfuluse/IAData/Recommendations. Published 2012. Accessed November 15, 2016.Google Scholar
3. Health information technology: standards, implementation specifications, and certification criteria for electronic health record technology, 2014 edition; revisions to the permanent certification program for health information technology. Final rule. Fed Register 2012;77:54163–292.Google Scholar
4. Hripcsak, G, Soulakis, ND, Li, L, et al. Syndromic surveillance using ambulatory electronic health records. JAMIA 2009;16:354361.Google Scholar
5. Zhang, Y, May, L, Stoto, MA. Evaluating syndromic surveillance systems at institutions of higher education (IHEs): a retrospective analysis of the 2009 H1N1 influenza pandemic at two universities. BMC Pub Health 2011;11:591.Google Scholar
6. Soulakis, ND, Mostashari, F. Comparison of ambulatory electronic health record and emergency department visit log data for respiratory, fever, and GI syndromes. Adv Dis Surveill 2006;2:168.Google Scholar
7. Costa, MA, Kulldorff, M, Kleinman, K, Yih, WK, Platt, R, Brand, R. Comparing the utility of ambulatory care and emergency room data for disease outbreak detection. Adv Dis Surveill 2007;4:243.Google Scholar
8. Plagianos, MG, Wu, WY, McCullough, C, et al. Syndromic surveillance during pandemic (H1N1) 2009 outbreak, New York, New York, USA. Emerg Infect Dis 2011;17:17241726.Google Scholar
9. Yih, WK, Abrams, A, Hsu, J, Kleinman, K, Kulldorff, M, Platt, R. A comparison of ambulatory care and emergency department encounters as data sources for detection of clusters of lower gastrointestinal illness. Adv Dis Surveill 2005;1:75.Google Scholar
10. Hebert, C, Beaumont, J, Schwartz, G, Robicsek, A. The influence of context on antimicrobial prescribing for febrile respiratory illness: a cohort study. Ann Intern Med 2012;157:160169.Google Scholar
11. Guidance for clinicians on the use of rapid influenza diagnostic tests. Centers for Disease Control and Prevention website. http://www.cdc.gov/flu/professionals/diagnosis/clinician_guidance_ridt.htm#figure1. Published 2014. Accessed March 30, 2015.Google Scholar
12. Keramarou, M, Cottrell, S, Evans, MR, et al. Two waves of pandemic influenza A(H1N1) 2009 in Wales—the possible impact of media coverage on consultation rates, April-December 2009. Eur Communic Dis Bull 2011;16.Google ScholarPubMed
13. Jones, JH, Salathe, M. Early assessment of anxiety and behavioral response to novel swine-origin influenza A(H1N1). PloS One 2009;4:e8032.Google Scholar
14. The 2012–2013 influenza season. Centers for Disease Control and Prevention website. www.cdc.gov/flu/pastseasons/1213season.htm. Published 2013. Accessed May 29, 2015.Google Scholar
15. Fleming, DM, Zambon, M, Bartelds, AI. Population estimates of persons presenting to general practitioners with influenza-like illness, 1987–96: a study of the demography of influenza-like illness in sentinel practice networks in England and Wales, and in The Netherlands. Epidemiol Infect 2000;124:245253.Google Scholar