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ISDS 2018 Conference Abstracts

Using Discharge Diagnoses for Early Notification of 
Reportable Diseases in Georgia
Rene Borroto*1, Jessica Grippo1, Karl Soetebier1, Wendy Smith2, Bill Williamson1, 
Patrick Pitcher1, Lance Ballester1 and Cherie Drenzek1
1Georgia Department of Public Health, Atlanta, GA, USA; 2Fulton County Board of Health, Atlanta, GA, USA

Objective
To describe how the Georgia Department of Public Health (DPH) 

uses ICD-9 and ICD-10-based discharge diagnoses (DDx) codes 
assigned to Emergency Department (ED) patients to support the early 
detection and investigation of outbreaks, clusters, and individual cases 
of reportable diseases.

Introduction
The Georgia DPH has used its State Electronic Notifiable Disease 

Surveillance System (SendSS) Syndromic Surveillance (SS) module 
to collect, analyze and display analyses of ED patient visits, including 
DDx data from hospitals throughout Georgia for early detection and 
investigation of cases of reportable diseases before laboratory test 
results are available. Evidence on the value of syndromic surveillance 
approaches for outbreak or event detection is limited (1, 2). Use of 
the DDx field within datasets, specifically as it might be used for 
investigation of outbreaks, clusters, and/or individual cases of 
reportable diseases, has not been widely discussed.

Methods
The DDx field of the ED data set sent to DPH by 120 facilities 

was queried for diseases that are immediately-reportable, as well as 
those reportable within 7 days of diagnosis. The query was performed 
twice a day using a combination of SAS 9.4 and the internal query 
capabilities of SendSS. District Epidemiologists (DE) were notified 
by email, with an Excel file attached that includes the details of the 
patient’s visit. DEs contacted Infection Control Practitioners (ICPs) 
of the facilities where the patients had received a discharge diagnosis 
of a reportable disease. True or false positives were determined after 
the outcome of the follow-up with the ICP had been known and after 
the patient had been entered as a case of reportable disease in SendSS 
by the DE. Hence, if the patient was a confirmed or probable case 
of a reportable disease, it was recorded as a True Positive, and True 
Negative otherwise. This led to the calculation of Predictive Value 
Positive (PVP) by reportable disease.

Results
Table 1 shows the number of notifications sent to DEs that were 

later demonstrated to be True Positives and False Positives. It also 
shows the PVP by diseases being reported, for the period spanning 
from 05/01/2016 to 08/31/2017. Use of these notifications has allowed 
early investigation and identification of 158 cases of notifiable 
diseases by DEs. This includes 25 epi-linked cases (varicella=12, 
pertussis=4, cryptosporidiosis=3, shigellosis=2, malaria=2, and 
viral meningitis=2), as well as two clusters of varicella, one cluster 
of pertussis, and one outbreak of varicella in an elementary school 
that had not been reported to the local health department. A notable 
limitation of this study is that no systematic and exhaustive tracking 
is done of all notifications, as DEs have latitude to decide whether 
to follow up on a specific notification, depending on other local data 
that could be related to the event. Therefore, the PPVs may be biased 
due to over-/under-estimation of unknown size and direction. One 
exception to this is varicella notifications, whose outcomes have 

been exhaustively tracked by the DPH surveillance coordinator of 
this disease.

Conclusions
The use of ED discharge diagnoses to examine potential cases of 

reportable diseases can help improve detection and early response by 
local health departments to outbreaks, clusters, and individual cases 
of reportable diseases. Exhaustive tracking of all the notifications 
by specific diseases may improve the estimation of the PPVs of the 
notifications sent to DEs.

Table 1. True Positives, False Positives, and Predictive Value Positive, by 
reportable disease, State of Georgia.

Source: Discharge Diagnosis field from Emergency Departments and Urgent 
Care Centers sending data to the SS module of SendSS

Keywords
discharge diagnosis; reportable disease; surveillance; emergency 
department

Acknowledgments
We are grateful to the Epidemiologists of the 18 Public Health Districts 
of Georgia for their hard work. We want to acknowledge the excellent 
work done by Carolyn Adam, the Varicella Surveillance Coordinator at 
the Georgia DPH.

References
1.J Buehler, A Sonricker, M Paladini, P Soper, F Mostashari. Syndromic

Surveillance Practice in the United States: Findings from a Survey of
State, Territorial, and Selected Local Health Departments. Advances 
in Disease Surveillance. 2008; 6(3): 1-20.

2.R Hopkins, C Tong, H Burkom, et al. A Practitioner-Driven Research
Agenda for Syndromic Surveillance. Public Health Reports 2017;
132(Supplement1): 116S-126S.

*Rene Borroto
E-mail: rene.borroto@dph.ga.gov

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 10(1):e191, 2018