scholarly journals Inconsistency of Timeliness in a Chief Complaint-Based Syndromic Surveillance System During Two Influenza Epidemic Seasons

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Tao Tao ◽  
Qi Zhao ◽  
Jun Zong ◽  
Xue Li ◽  
Vinod Diwan ◽  
...  
Keyword(s):  
Surveillance System ◽  
Syndromic Surveillance ◽  
Clinical Manifestations ◽  
Chief Complaint ◽  
Influenza Surveillance ◽  
Influenza Epidemic ◽  
Surveillance Network ◽  
Syndromic Surveillance System ◽  
Positive Rate ◽  
Patient Groups

This study estimated the early warning timeliness of a chief complaint-based syndromic surveillance system towards seasonal influenza epidemics. Findings showed that the timliness of ILI data sources changed across two influenza epidemic seasons. ILI reported from different levels of health facilities and patient groups showed distinct timeliness towards influenza epidemics indicated by virus positive rate (VPR) from National Influenza Surveillance Network. The changes of dominant strains, clinical manifestations, population groups affected in different influenza seasons might account for this inconsistency.

scholarly journals Monitoring Respiratory Syncytial Virus Regionally In Children Aged < 5 Years Old Using Emergency Department and Urgent Care Center Chief Complaint Data in Florida’s Syndromic Surveillance System, Week 1, 2010 - Week 32, 2014

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Heather Rubino ◽  
David Atrubin ◽  
Janet J. Hamilton
Keyword(s):  
Surveillance System ◽  
Syndromic Surveillance ◽  
Hospital Admissions ◽  
Care Center ◽  
Laboratory Data ◽  
Chief Complaint ◽  
Urgent Care ◽  
Surveillance Systems ◽  
Syndromic Surveillance System ◽  
Syncytial Virus

ED chief complaint and discharge diagnosis data accessed through a syndromic surveillance system can be used for effective, timely monitoring of RSV hospitalizations in children < 5 years old and may be a more efficient and complete means of monitoring seasonality of RSV activity by region and statewide compared to hospital-based laboratory data reporting. Additionally, this surveillance technique can efficiently monitor RSV activity as well as estimate hospital admissions due to RSV and may be a useful approach for other states with syndromic surveillance systems.

scholarly journals Using a Syndromic Surveillance System to Evaluate the Impact of a Change in Alcohol Law

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Julia A. Dilley ◽  
Atar Baer ◽  
Jeff Duchin ◽  
Julie E. Maher
Keyword(s):  
Surveillance System ◽  
Syndromic Surveillance ◽  
Washington State ◽  
Chief Complaint ◽  
King County ◽  
Syndromic Surveillance System ◽  
Liquor Stores ◽  
Diagnosis Codes ◽  
Ed Visits ◽  
The Impact

In 2011, Washington State voters passed an initiative which closed state liquor stores and opened private sector liquor sales. We examined trends in alcohol-related emergency department (ED) visits associated with this law change. Data were from the King County syndromic surveillance system. Alcohol-related ED visits were identified using chief complaint search strings and diagnosis codes. We used a linear regression model with a spline at the date of law change and controlled for other factors. Significant increases in alcohol-related ED visits were observed associated with the law change among minors (age <21) and adults ages 40 and older.

scholarly journals Validation of Syndromic ILI Data for Use in CDC’s ILINet Surveillance, Pennsylvania

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Sameh W Boktor ◽  
Kristen Waller ◽  
Lenee Blanton ◽  
Krista Kniss
Keyword(s):  
Sore Throat ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Correlation Coefficients ◽  
Chief Complaint ◽  
The State ◽  
Surveillance Data ◽  
Syndromic Surveillance System ◽  
Ed Visits ◽  
Number Of Visits

Objective: Discuss use of syndromic surveillance as a source for the state’s ILI/Influenza surveillanceDiscuss reliability of syndromic data and methods to address problems caused by data outliers and inconsistencies.Introduction: ILINet is a CDC program that has been used for years for influenza-like illness (ILI) surveillance, using a network of outpatient providers who volunteer to track and report weekly the number of visits due to ILI and the total number of visits to their practice. Pennsylvania has a network of 95 providers and urgent care clinics that submit data to ILINet. However, ongoing challenges in recruiting and retaining providers, and inconsistent weekly reporting are barriers to receiving accurate, representative, and timely ILI surveillance data year-round. Syndromic surveillance data have been used to enhance outpatient ILI surveillance in a number of jurisdictions, including Pennsylvania. At present, 156 hospitals, or 90% of all Pennsylvania hospitals with emergency departments (EDs), send chief complaint and other information on their ED visits to the Department of Health’s (PADOH) syndromic surveillance system. PADOH evaluated the consistency and reliability of ILI syndromic data as compared to ILINet data, to confirm that syndromic data were suitable for use in ILINet.Methods: Pennsylvania ILINet data from the past 6 influenza seasons (2011-2012 to 2016-2017, or 314 weeks of data) were downloaded from the CDC’s ILINet website. The statewide weekly percent of visits due to ILI in ILINet was used as the standard for comparisons. For syndromic surveillance, PADOH uses the Epicenter platform hosted by Health Monitoring Systems (HMS); visit-level data are also stored in SAS datasets at PADOH, and HMS forwards a subset of data to the National Syndromic Surveillance System Program. Using syndromic data from the same time period, the proportion of weeks with no syndromic data available was calculated for each facility. A state-developed ILI algorithm (very similar to the 2016 algorithm developed by the ISDS Syndrome Definitions Workgroup) was applied to ED visit chief complaint data to identify visits likely to be due to ILI. The algorithm flags the ER visit as ILI if chief complaint has any combinations of words for flu or fever plus either cough and sore throat or fever and both cough or sore throat . The percent of ED visits due to ILI per the syndromic algorithm (ILIsyn) was calculated for each week by hospital and state-wide. Facility ILIsyn trends were compared to the State level percent ILI data from ILINet by visually examining plots and by calculating Pearson correlation coefficients. Facilities that had >=15 weeks where ILIsyn differed from percent ILI in ILINet by more than 5% were considered to be poorly correlated.Results: A total of 156 hospitals were evaluated in the study. Twenty of the hospitals were excluded because they did not have syndromic data for at least 50% of the weeks in the study period, and an additional 20 were excluded because they had not agreed to have data forwarded to CDC. Of the remaining 116 facilities, individual facility correlation coefficients between ILIsyn and ILINet trends ranged from 0.03 to 0.82 (examples are in Figure 1). Twenty-four hospitals (20.7%) were determined to be poorly correlated. When data from the remaining 92 hospitals were combined, the state ILINet and state-wide ILIsyn trends were strongly correlated statistically and graphically (r=0.82, p <0.0001, Figure 2). Syndromic data from these 92 facilities were deemed acceptable for inclusion in ILINet. Conclusions: Syndromic surveillance data are a valuable source for ILI surveillance. However, evaluation at the hospital-specific level revealed that useful information is not obtained from all facilities. This project demonstrated that validation of data at the facility level is crucial to obtaining reliable and meaningful information. More work is needed to understand which factors distinguish well-correlated from poorly-correlated facilities, and how to improve the quality of information obtained from poorly-correlated facilities.

scholarly journals The National Capitol Region’s Emergency Department Syndromic Surveillance System: 
Do Chief Complaint and Discharge Diagnosis Yield Different Results?

2003 ◽  
Vol 9 (3) ◽  
pp. 393-396 ◽  
Author(s):  
Elizabeth M. Begier ◽  
Denise Sockwell ◽  
Leslie M. Branch ◽  
John O. Davies-Cole ◽  
LaVerne H. Jones ◽  
...  
Keyword(s):  
Emergency Department ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Chief Complaint ◽  
Discharge Diagnosis ◽  
Syndromic Surveillance System

scholarly journals Using Syndromic Surveillance to Classify and Capture Non-Fatal Occupational Injuries and Illnesses

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Marija Borjan ◽  
Margaret Lumia
Keyword(s):  
Real Time ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Occupational Injuries ◽  
Chief Complaint ◽  
Surveillance Data ◽  
Free Text ◽  
Syndromic Surveillance System ◽  
Work Related ◽  
Data Source

ObjectivesTo evaluate the use of a real-time surveillance tool to track a variety of occupationally-related emergency room visits through the state based syndromic surveillance system, EpiCenter.IntroductionThis study uses data from the New Jersey syndromic surveillance system (EpiCenter) as a data source to enhance surveillance of current non-fatal occupational injuries, illnesses, and poisonings. EpiCenter was originally developed for early detection and monitoring of the health of communities using chief complaints from people seeking acute care in hospital emergency rooms to identify health trends. Currently, syndromic surveillance has not been widely applied to identify occupational injuries and illnesses. Incorporating syndromic surveillance data from EpiCenter, along with hospital discharge data, will enhance the classification and capture of work-related non-fatal injuries with possible improved efforts at prevention.MethodsEpiCenter Emergency Department data from January to December 2014 was evaluated, using work-related keywords and ICD-9 codes, to determine its ability to capture non-fatal work-related injuries. A collection of keywords and phrases specific to work-related injuries was developed by manually assessing the free text chief complaint data field’s. Sensitivity, specificity, and positive predictive value (PPV), along with descriptive statistics was used to evaluate and summarize the occupational injuries identified in EpiCenter.ResultsOverall, 11,919 (0.3%) possible work-related injuries were identified via EpiCenter. Of these visits 956 (8%) indicated Workman’s Compensation as payer. Events that resulted in the greatest number of ED visits were falls, slips, trips (1,679, 14%). Nature of injury included cuts, lacerations (1,041, 9%), burns (255, 2%), and sprains, strains, tears (185, 2). The part of the body most affected were the back (1,414, 12%). This work-related classifier achieved a sensitivity of 5.4%, a specificity of 99.8%, and a PPV of 2.8%.ConclusionsEvaluating the ability and performance of a new and existing surveillance data source to capture work-related injuries can lead to enhancements in current data collection methods. This evaluation successfully demonstrated that the chief complaint reporting system can yield real-time knowledge of incidents and local conditions for use in identifying opportunities for prevention of work-related injuries. 

scholarly journals Detecting Suicide-Related Emergency Department Visits Among Adults Using the District of Columbia Syndromic Surveillance System

2017 ◽  
Vol 132 (1_suppl) ◽  
pp. 88S-94S ◽  
Author(s):  
S. Janet Kuramoto-Crawford ◽  
Erica L. Spies ◽  
John Davies-Cole
Keyword(s):  
Emergency Department ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
District Of Columbia ◽  
Chief Complaint ◽  
Emergency Department Visits ◽  
Added Value ◽  
Discharge Diagnosis ◽  
Syndromic Surveillance System ◽  
Ed Visits

Objectives: Limited studies have examined the usefulness of syndromic surveillance to monitor emergency department (ED) visits involving suicidal ideation or attempt. The objectives of this study were to (1) examine whether syndromic surveillance of chief complaint data can detect suicide-related ED visits among adults and (2) assess the added value of using hospital ED data on discharge diagnoses to detect suicide-related visits. Methods: The study data came from the District of Columbia electronic syndromic surveillance system, which provides daily information on ED visits at 8 hospitals in Washington, DC. We detected suicide-related visits by searching for terms in the chief complaints and discharge diagnoses of 248 939 ED visits for which data were available for October 1, 2015, to September 30, 2016. We examined whether detection of suicide-related visits according to chief complaint data, discharge diagnosis data, or both varied by patient sex, age, or hospital. Results: The syndromic surveillance system detected 1540 suicide-related ED visits, 950 (62%) of which were detected through chief complaint data and 590 (38%) from discharge diagnosis data. The source of detection for suicide-related ED visits did not vary by patient sex or age. However, whether the suicide-related terms were mentioned in the chief complaint or discharge diagnosis differed across hospitals. Conclusions: ED syndromic surveillance systems based on chief complaint data alone would underestimate the number of suicide-related ED visits. Incorporating the discharge diagnosis into the case definition could help improve detection.

Algorithm for Statistical Detection of Peaks - Syndromic Surveillance System for the Athens 2004 Olympic Games

2004 ◽  
Author(s):  
Urania G. Dafni ◽  
S. Tsiodras ◽  
D. Panagiotakos ◽  
K. Gkolfinopoulou ◽  
G. Kouvatscas ◽  
...  
Keyword(s):  
Surveillance System ◽  
Syndromic Surveillance ◽  
Olympic Games ◽  
Syndromic Surveillance System ◽  
Statistical Detection
Sign in / Sign up

Export Citation Format

Share Document