- Why the syndrome was created? This syndrome was created to monitor tick related emergency room visits using regular expressions in R.
- Syndromic surveillance system (e.g., ESSENCE, R STUDIO, RODS, etc.) Data collected from Epicenter, but parsed and analysed in R/Rstudio
- Data sources the syndrome was used on (e.g., Emergency room, EMS, Air Quality, etc.) Emergency room and Urgent Care
Syndromes
A step-wise article on developing this syndrome definition can be found in the April 2019 NSSP Update https://www.cdc.gov/nssp/news.html
This syndrome is an initial attempt at an improved Drowning and Submersion query in NSSP ESSENCE. It was developed starting with the existing ESSENCE SubSyndrome for DrowningOrSubmersion.
The following syndrome was developed to explore emergency department visit records involving people experiencing homelessness. Trends over time, patient demographics, geographic distribution, and primary reasons for seeking care were explored. Additionally, we have been using this definition, in combination with other illness/injury specific definitions to assess the trends in among people experiencing homelessness (e.g., cold-related illness among people experiencing homelessness during record low temperatures).
This syndrome is a work-in-progress and was created to experiment with Chief Complaint text indicating a language barrier between medical professionals and patient and/or an interpreter is needed to provide medical care.
This was developed on the NSSP ESSENCE CCQV data in the Processed Chief Complaint field. I suspect Triage Notes would also contain this type of information if you receive that field.
This syndrome was created to monitor emergency room visits related to opioid abuse in Suburban Cook County, IL. It is adapted from CDC’s Opioid Overdose v2 syndrome, and expanded to include terms for opioid withdrawal, injection site infections, and patients with underlying opiate abuse or dependence disorders, as well as unintentional overdose with opioids.
Description
The objective of this report is to describe the variation of symptoms being detected as respiratory or influenza-like illness (ILI) syndrome using nurse advice call center (NACC) data and emergency department (ED) chief complaint data compared to laboratory data from one hospital.
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Description
To determine sensitivity and specificity of syndromic surveillance of influenza based on data from SOS Medecins, a healthcare network of emergency general practitioners (GP) in Bordeaux, France.
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Description
The Veterans Health Administration (VHA) operates over 880 outpatient clinics across the nation. The Johns Hopkins Applied Physics Laboratory’s Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE) utilizes VHA ICD9 coded outpatient visit data for the detection of abnormal patterns of disease occurrence. The hemorrhagic illness (HI) syndrome category in ESSENCE is comprised of 25 different ICD9 codes, including 12 codes specific for viral hemorrhagic fever (VHF) (e.g., ebola, yellow fever, CrimeanCongo hemorrhagic fever, lassa, etc.) and 13 nonspecific conditions (e.g., purpura not otherwise specified (NOS), thrombocytopathy, and coagulation defect NOS).
Objective
We sought to evaluate the functionality of the diagnosis codes which fall into the syndrome category of hemorrhagic illness.
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In WA, we've been using a series of increasingly broad queries to monitor measles. The number of visits mentioning measles increases during an outbreak as a result of people seeking care because they were (or think) they were exposed, seeking titers, vaccinations, or having seen reports of measles on the news and concerns than an illness could be measles. As a result, it is important to focus in on visits of highest suspicion as mentions of measles increase.