Use of Emergency Department Data to Monitor and Respond to an Increase in Opioid Overdoses in New Hampshire, 2011-2015

Objectives: Opioid-related overdoses and deaths in New Hampshire have increased substantially in recent years, similar to increases observed across the United States. We queried emergency department (ED) data in New Hampshire to monitor opioid-related ED encounters as part of the public health response to this health problem. Methods: We obtained data on opioid-related ED encounters for the period January 1, 2011, through December 31, 2015, from New Hampshire’s syndromic surveillance ED data system by querying for (1) chief complaint text related to the words “fentanyl,” “heroin,” “opiate,” and “opioid” and (2) opioid-related International Classification of Diseases ( ICD) codes. We then analyzed the data to calculate frequencies of opioid-related ED encounters by age, sex, residence, chief complaint text values, and ICD codes. Results: Opioid-related ED encounters increased by 70% during the study period, from 3300 in 2011 to 5603 in 2015; the largest increases occurred in adults aged 18-29 and in males. Of 20 994 total opioid-related ED visits, we identified 18 554 (88%) using ICD code alone, 690 (3%) using chief complaint text alone, and 1750 (8%) using both chief complaint text and ICD code. For those encounters identified by ICD code only, the corresponding chief complaint text included varied and nonspecific words, with the most common being “pain” (n = 3335, 18%), “overdose” (n = 1555, 8%), “suicidal” (n = 816, 4%), “drug” (n = 803, 4%), and “detox” (n = 750, 4%). Heroin-specific encounters increased by 827%, from 4% of opioid-related encounters in 2011 to 24% of encounters in 2015. Conclusions: Opioid-related ED encounters in New Hampshire increased substantially from 2011 to 2015. Data from New Hampshire’s ED syndromic surveillance system provided timely situational awareness to public health partners to support the overall response to the opioid epidemic.

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Using Syndromic Surveillance Alert Protocols for Epidemiologic Response in Georgia

Online Journal of Public Health Informatics ◽

10.5210/ojphi.v9i1.7707 ◽

2017 ◽

Vol 9 (1) ◽

Author(s):

Rene Borroto ◽

Bill Williamson ◽

Patrick Pitcher ◽

Lance Ballester ◽

Wendy Smith ◽

...

Keyword(s):

Public Health ◽

Emergency Department ◽

Health Care Providers ◽

Syndromic Surveillance ◽

Emergency Department Patient ◽

Chief Complaint ◽

Care Providers ◽

Public Health Response ◽

Presumptive Diagnosis ◽

Notifiable Diseases

ObjectiveDescribe how the Georgia Department of Public Health (DPH) usessyndromic surveillance to initiate review by District Epidemiologists(DEs) to events that may warrant a public health response (1).IntroductionDPH uses its State Electronic Notifiable Disease SurveillanceSystem (SendSS) Syndromic Surveillance (SS) Module to collect,analyze and display results of emergency department patient chiefcomplaint data from hospitals throughout Georgia.MethodsDPH prepares a daily SS report, based upon the analysis ofdaily visits to 112 Emergency Department (EDs). The visits areclassified in 33 syndromes. Queries of chief complaint and dischargediagnosis are done using the internal query capability of SendSS-SSand programming in SAS/BASE. Charting of the absolute countsor percentage of ED visits by syndromes is done using the internalcharting capability of SendSS-SS. A daily SS report includes thefollowing sections:Statewide Emergency Department Visitsby Priority Syndromes(Bioterrorism, BloodyRespiratory,FeverRespiratory, FeverChest, FeverFluAdmit, FeverFluDeaths,VeryIll, andPoxRashFever, Botulism, Poison, BloodyDiarrhea,BloodyVomit, FeverGI, ILI, FeverFlu, RashFever, Diarrhea,Vomit).Statewide Flag Analysis: Is intended to detect statewideflags, by using theChartscapability in SendSS SS.Possible caseswith presumptive diagnosis of potentially notifiable diseases: Isintended to provide early-warning to the DEs of possible cases thatare reportable to public health immediately or within 7 days usingqueries in the Chief Complaint and Preliminary Diagnosis fields ofSendSS-SS.Possible clusters of illness: Since any cluster of illnessmust be reported immediately to DPH, this analysis is aimed atquerying and identifying possible clusters of patients with similarsymptoms (2).Possible travel-related illness: Is intended to identifypatients with symptoms and recent travel history.Other events ofinterest: Exposures to ill patients in institutional settings (e.g. chiefcomplaint indicates that other children in the daycare have similarsymptoms).Trend Analysis: Weekly analysis of seasonality andtrends of 14 syndromes. Finally, specific events are notified to andreviewed by the 18 DEs, who follow up by contacting the InfectionPreventionists of the hospitals to identify the patients using medicalrecords or other hospital-specific identification numbers and followup on the laboratory test results.ResultsSince 05/15/2016, 12 travel-related illnesses, 29 vaccine-preventable diseases, 14 clusters, and 3 chemical exposures havebeen notified to DEs. For instance, a cluster of chickenpox in childrenwas identified after the DE contacted the Infection Preventionist ofa hospital, who provided the DE with the laboratory results and thephysician notes about the symptoms of the patients. These actionshave resulted in earlier awareness of single cases or cluster of illness,prompt reporting of notifiable diseases, and successful interactionbetween DEs and health care providers. In addition, SS continues totrack the onset, peak, and decline of seasonal illnesses.ConclusionsThe implementation of SS in the State of Georgia is helping withthe timely detection and early responses to disease events and couldprove useful in reducing the disease burden caused by a bioterroristattack.

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Public Health in the Field and the Emergency Operations Center: Methods for Implementing Real-Time Onsite Syndromic Surveillance at Large Public Events

Disaster Medicine and Public Health Preparedness ◽

10.1017/dmp.2013.83 ◽

2013 ◽

Vol 7 (5) ◽

pp. 467-474 ◽

Cited By ~ 2

Author(s):

Kristen Pogreba-Brown ◽

Kyle McKeown ◽

Sarah Santana ◽

Alisa Diggs ◽

Jennifer Stewart ◽

...

Keyword(s):

Public Health ◽

Syndromic Surveillance ◽

Prediction Models ◽

Health Department ◽

The United States ◽

Study Data ◽

Public Health Response ◽

Syndromic Surveillance System ◽

Patient Reports ◽

Public Events

AbstractObjectiveTo develop an onsite syndromic surveillance system for the early detection of public health emergencies and outbreaks at large public events.MethodsAs the third largest public health jurisdiction in the United States, Maricopa County Department of Public Health has worked with academic and first-response partners to create an event-targeted syndromic surveillance (EVENTSS) system. This system complements long-standing traditional emergency department-based surveillance and provides public health agencies with rapid reporting of possible clusters of illness.ResultsAt 6 high profile events, 164 patient reports were collected. Gastrointestinal and neurological syndromes were most commonly reported, followed by multisyndromic reports. Neurological symptoms were significantly increased during hot weather events. The interview rate was 2 to 7 interviews per 50 000 people per hour, depending on the ambient temperature.DiscussionStudy data allowed an estimation of baseline values of illness occurring at large public events. As more data are collected, prediction models can be built to determine threshold levels for public health response.ConclusionsEVENTSS was conducted largely by volunteer public health graduate students, increasing the response capacity for the health department. Onsite epidemiology staff could make informed decisions and take actions quickly in the event of a public health emergency. (Disaster Med Public Health Preparedness. 2013;0:1–8)

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Framework for the Development of Response Protocols for Public Health Syndromic Surveillance Systems: Case Studies of 8 US States

Disaster Medicine and Public Health Preparedness ◽

10.1097/dmp.0b013e31819f4483 ◽

2009 ◽

Vol 3 (S1) ◽

pp. S29-S36 ◽

Cited By ~ 17

Author(s):

Lori Uscher-Pines ◽

Corey L. Farrell ◽

Steven M. Babin ◽

Jacqueline Cattani ◽

Charlotte A. Gaydos ◽

...

Keyword(s):

Public Health ◽

Surveillance System ◽

Syndromic Surveillance ◽

The United States ◽

Essential Elements ◽

System Response ◽

Surveillance Systems ◽

Health Departments ◽

Public Health Response ◽

Syndromic Surveillance System

ABSTRACTObjectives: To describe current syndromic surveillance system response protocols in health departments from 8 diverse states in the United States and to develop a framework for health departments to use as a guide in initial design and/or enhancement of response protocols.Methods: Case study design that incorporated in-depth interviews with health department staff, textual analysis of response plans, and a Delphi survey of syndromic surveillance response experts.Results: All 8 states and 30 of the 33 eligible health departments agreed to participate (91% response rate). Fewer than half (48%) of surveyed health departments had a written response protocol, and health departments reported conducting in-depth investigations on fewer than 15% of syndromic surveillance alerts. A convened panel of experts identified 32 essential elements for inclusion in public health protocols for response to syndromic surveillance system alerts.Conclusions: Because of the lack of guidance, limited resources for development of response protocols, and few examples of syndromic surveillance detecting previously unknown events of public health significance, health departments have not prioritized the development and refinement of response protocols. Systems alone, however, are not effective without an organized public health response. The framework proposed here can guide health departments in creating protocols that will be standardized, tested, and relevant given their goals with such systems. (Disaster Med Public Health Preparedness. 2009;3(Suppl 1):S29–S36)

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Real-time monitoring of a mass K2-related overdose outbreak – Connecticut, 2018

Online Journal of Public Health Informatics ◽

10.5210/ojphi.v11i1.9769 ◽

2019 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Kristen Soto ◽

Erin Grogan ◽

Alexander Senetcky ◽

Susan Logan

Keyword(s):

Emergency Department ◽

Real Time ◽

Syndromic Surveillance ◽

Situational Awareness ◽

Chief Complaint ◽

Surveillance Data ◽

Emergency Department Utilization ◽

Syndromic Surveillance System ◽

Ed Visits ◽

State And Local

ObjectiveTo describe the use of syndromic surveillance data for real-time situational awareness of emergency department utilization during a localized mass overdose event related to the substance K2.IntroductionOn August 15, 2018, the Connecticut Department of Public Health (DPH) became aware of a cluster of suspected overdoses in an urban park related to the synthetic cannabinoid K2. Abuse of K2 has been associated with serious adverse effects and overdose clusters have been reported in multiple states. This investigation aimed to characterize the use of syndromic surveillance data to monitor a cluster of suspected overdoses in real time.MethodsThe EpiCenter syndromic surveillance system collects data on all emergency department (ED) visits at Connecticut hospitals. ED visits associated with the event were identified using ad hoc keyword analyses. The number of visits by facility location for the state, county, and city were communicated to state and local partners in real time. Gender, age, and repeated ED visits were assessed. After the event, surveillance findings were summarized for partnersResultsDuring the period of August 15–16, 2018 the number of ED visits with a mention of K2 in the chief complaint increased from three to 30 in the impacted county, compared to a peak of 5 visits during the period of March–July, 2018. An additional 25 ED visits were identified using other related keywords (e.g., weed). After the event, 72 ED visits were identified with K2 and location keywords in the chief complaint or triage notes. These 72 visits comprised 53 unique patients, with 12 patients returning to the ED 2–5 times over the two day period. Of 53 patients, 77% were male and the median age was 40 years (interquartile range 35–51 years). Surveillance findings were shared with partners in real time for situational awareness, and in a summary report on August 21.ConclusionsData from the EpiCenter system were consistent with reports from other data sources regarding this cluster of suspected drug overdoses. Next steps related to this event involve: monitoring data for reference to areas of concentrated substance use, enabling automated alerts to detect clusters of interest, and developing a plan to improve coordinate real-time communication with stakeholderswithin DPH and with external partners during events.

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Monitoring Emergency Department Visits From Puerto Rico in the Aftermath of Hurricane Maria Using Syndromic Surveillance – New York City, 2017

Disaster Medicine and Public Health Preparedness ◽

10.1017/dmp.2019.102 ◽

2019 ◽

Vol 14 (1) ◽

pp. 44-48

Author(s):

Priscilla W. Wong ◽

Hilary B. Parton

Keyword(s):

Emergency Department ◽

New York ◽

New York City ◽

Puerto Rico ◽

York City ◽

Surveillance System ◽

Syndromic Surveillance ◽

Situational Awareness ◽

Syndromic Surveillance System ◽

Ed Visits

ABSTRACTObjective:Syndromic surveillance has been useful for routine surveillance on a variety of health outcomes and for informing situational awareness during public health emergencies. Following the landfall of Hurricane Maria in 2017, the New York City (NYC) Department of Health and Mental Hygiene (DOHMH) implemented an enhanced syndromic surveillance system to characterize related emergency department (ED) visits.Methods:ED visits with any mention of specific key words (“Puerto,” “Rico,” “hurricane,” “Maria”) in the ED chief complaint or Puerto Rico patient home Zip Code were identified from the DOHMH syndromic surveillance system in the 8-week window leading up to and following landfall. Visit volume comparisons pre- and post-Hurricane Maria were performed using Fisher’s exact test.Results:Analyses identified an overall increase in NYC ED utilization relating to Puerto Rico following Hurricane Maria landfall. In particular, there was a small but significant increase in visits involving a medication refill or essential medical equipment. Visits for other outcomes, such as mental illness, also increased, but the differences were not statistically significant.Conclusions:Gaining this situational awareness of medical service use was informative following Hurricane Maria, and, following any natural disaster, the same surveillance methods could be easily established to aid an effective emergency response.

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Establishing a nationwide emergency department-based syndromic surveillance system for better public health responses in Taiwan

BMC Public Health ◽

10.1186/1471-2458-8-18 ◽

2008 ◽

Vol 8 (1) ◽

Cited By ~ 50

Author(s):

Tsung-Shu Joseph Wu ◽

Fuh-Yuan Frank Shih ◽

Muh-Yong Yen ◽

Jiunn-Shyan Julian Wu ◽

Shiou-Wen Lu ◽

...

Keyword(s):

Public Health ◽

Emergency Department ◽

Surveillance System ◽

Syndromic Surveillance ◽

Syndromic Surveillance System

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Development and validation of an automated emergency department-based syndromic surveillance system to enhance public health surveillance in Yukon: a lower-resourced and remote setting

BMC Public Health ◽

10.1186/s12889-021-11132-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Etran Bouchouar ◽

Benjamin M. Hetman ◽

Brendan Hanley

Keyword(s):

Public Health ◽

Emergency Department ◽

Surveillance System ◽

Syndromic Surveillance ◽

Validation Dataset ◽

Free Text ◽

Mass Gathering ◽

Syndromic Surveillance System ◽

Development And Validation ◽

Remote Setting

Abstract Background Automated Emergency Department syndromic surveillance systems (ED-SyS) are useful tools in routine surveillance activities and during mass gathering events to rapidly detect public health threats. To improve the existing surveillance infrastructure in a lower-resourced rural/remote setting and enhance monitoring during an upcoming mass gathering event, an automated low-cost and low-resources ED-SyS was developed and validated in Yukon, Canada. Methods Syndromes of interest were identified in consultation with the local public health authorities. For each syndrome, case definitions were developed using published resources and expert elicitation. Natural language processing algorithms were then written using Stata LP 15.1 (Texas, USA) to detect syndromic cases from three different fields (e.g., triage notes; chief complaint; discharge diagnosis), comprising of free-text and standardized codes. Validation was conducted using data from 19,082 visits between October 1, 2018 to April 30, 2019. The National Ambulatory Care Reporting System (NACRS) records were used as a reference for the inclusion of International Classification of Disease, 10th edition (ICD-10) diagnosis codes. The automatic identification of cases was then manually validated by two raters and results were used to calculate positive predicted values for each syndrome and identify improvements to the detection algorithms. Results A daily secure file transfer of Yukon’s Meditech ED-Tracker system data and an aberration detection plan was set up. A total of six syndromes were originally identified for the syndromic surveillance system (e.g., Gastrointestinal, Influenza-like-Illness, Mumps, Neurological Infections, Rash, Respiratory), with an additional syndrome added to assist in detecting potential cases of COVID-19. The positive predictive value for the automated detection of each syndrome ranged from 48.8–89.5% to 62.5–94.1% after implementing improvements identified during validation. As expected, no records were flagged for COVID-19 from our validation dataset. Conclusions The development and validation of automated ED-SyS in lower-resourced settings can be achieved without sophisticated platforms, intensive resources, time or costs. Validation is an important step for measuring the accuracy of syndromic surveillance, and ensuring it performs adequately in a local context. The use of three different fields and integration of both free-text and structured fields improved case detection.

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Increase in emergency department visits related to cannabis reported using syndromic surveillance system

European Journal of Public Health ◽

10.1093/eurpub/cky272 ◽

2019 ◽

Vol 29 (4) ◽

pp. 621-625 ◽

Cited By ~ 4

Author(s):

G N Noel ◽

A M Maghoo ◽

F F Franke ◽

G V Viudes ◽

P M Minodier

Keyword(s):

Emergency Department ◽

Surveillance System ◽

Syndromic Surveillance ◽

Age Groups ◽

The United States ◽

Cross Sectional Study ◽

Emergency Department Visits ◽

Cross Sectional ◽

Syndromic Surveillance System ◽

Icd 10

Abstract Background Cannabis is illegal in France but, as in many countries, legalization is under debate. In the United States, an increase of emergency department (ED) visits related to cannabis exposure (CE) in infants and adults was reported. In France, a retrospective observational study also suggested an increase of CE in children under 6 years old. This study only included toddlers and the data sources used did not allow repeated analysis for monitoring. Methods Our study aimed to evaluate the trend in visits for CE in ED in patients younger than 27 years old in Southern France. A cross-sectional study using the Electronic Emergency Department Abstracts (EEDA) included in the national Syndromic Surveillance System. CE visits were defined using International Classification of Disease (ICD-10). Results From 2009 to 2014, 16 EDs consistently reported EEDA with <5% missing diagnosis code. Seven hundred and ninety seven patients were admitted for CE including 49 (4.1%) children under 8 years old. From 2009–11 to 2012–14, the rate of CE visits increased significantly across all age groups. The highest increase was in the 8–14 years old (+144%; 1.85–4.51, P < 0.001) and was also significant in children under 8 (0.53–1.06; P = 0.02). Among children under 8, hospitalization rate (75.5% vs. 16.8%; P < 0.001) and intensive care unit admissions (4.1% vs. 0.1%; P < 0.001) were higher compared with patients older than 8 years. Conclusion These trends occurred despite cannabis remaining illegal. EEDA could be useful for monitoring CE in EDs.

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Tracking drug-related overdoses at the local level: Using Syndromic Surveillance in the CO-NCR

Online Journal of Public Health Informatics ◽

10.5210/ojphi.v10i1.8977 ◽

2018 ◽

Vol 10 (1) ◽

Author(s):

Emery Shekiro ◽

Lily Sussman ◽

Talia Brown

Keyword(s):

Public Health ◽

Emergency Department ◽

Real Time ◽

Drug Overdose ◽

Syndromic Surveillance ◽

Case Definition ◽

Chief Complaint ◽

Discharge Diagnosis ◽

Diagnosis Codes ◽

Drug Overdoses

Objective: In order to better describe local drug-related overdoses, we developed a novel syndromic case definition using discharge diagnosis codes from emergency department data in the Colorado North Central Region (CO-NCR). Secondarily, we used free text fields to understand the use of unspecified diagnosis fields.Introduction: The United States is in the midst of a drug crisis; drug-related overdoses are the leading cause of unintentional death in the country. In Colorado the rate of fatal drug overdose increased 68% from 2002-2014 (9.7 deaths per 100,000 to 16.3 per 100,000, respectively)1, and non-fatal overdose also increased during this time period (23% increase in emergency department visits since 2011)2. The CDC’s National Syndromic Surveillance Program (NSSP) provides near-real time monitoring of emergency department (ED) events across the country, with information uploaded daily on patient demographics, chief complaint for visit, diagnosis codes, triage notes, and more. Colorado North Central Region (CO-NCR) receives data for 4 local public health agencies from 25 hospitals across Adams, Arapahoe, Boulder, Denver, Douglas, and Jefferson Counties.Access to local syndromic data in near-real time provides valuable information for local public health program planning, policy, and evaluation efforts. However, use of these data also comes with many challenges. For example, we learned from key informant interviews with ED staff in Boulder and Denver counties, about concern with the accuracy and specificity of drug-related diagnosis codes, specifically for opioid-related overdoses.Methods: Boulder County Public Health (BCPH) and Denver Public Health (DPH) developed a query in Early Notification of Community Based Epidemics (ESSENCE) using ICD-10-CM codes to identify cases of drug-related overdose [T36-T51] from October 2016 to September 2017. The Case definition included unintentional, self-harm, assault and undetermined poisonings, but did not include cases coded as adverse effects or underdosing of medication. Cases identified in the query were stratified by demographic factors (i.e., gender and age) and substance used in poisoning. The first diagnosis code in the file was considered the primary diagnosis. Chief complaint and triage note fields were examined to further describe unspecified cases and to describe how patients present to emergency departments in the CO-NCR. We also explored whether detection of drug overdose visits captured by discharge diagnosis data varied by patient sex, age, or county.Results: The query identified 2,366 drug-related overdoses in the CO-NCR. The prevalence of drug overdoses differed across age groups. The detection of drug overdoses was highest among our youth and young adult populations; 16 to 20 year olds (16.0%), 21-25 year olds (11.4%), 26-30 year olds (11.4%). Females comprised 56.1% of probable general drug overdoses. The majority of primary diagnoses (31.0%) included poisonings related to diuretics and other unspecified drugs (T50), narcotics (T40) (12.6%), or non-opioid analgesics (T39) (7.8%). For some cases with unspecified drug overdose codes there was additional information about drugs used and narcan administration found in the triage notes and chief complaint fields.Conclusions: Syndromic surveillance offers the opportunity to capture drug-related overdose data in near-real time. We found variation in drug-related overdose by demographic groups. Unspecified drug overdose codes are extremely common, which likely negatively impacts the quality of drug-specific surveillance. Leveraging chief complaint and triage notes could improve our understanding of factors involved in drug-related overdose with limitations in discharge diagnosis. Chart reviews and access to more fields from the ED electronic health record could improve local drug surveillance.

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Development and Validation of an Automated Emergency Department-Based Syndromic Surveillance System for Use at a Mass Gathering Event (2020 Arctic Winter Games, Yukon Canada) During a Global Pandemic: Implications for Lower Resourced and Remote Settings

10.21203/rs.3.rs-54086/v1 ◽

2020 ◽

Author(s):

Etran Bouchouar ◽

Benjamin M. Hetman ◽

Brendan Hanley

Keyword(s):

Public Health ◽

Emergency Department ◽

Surveillance System ◽

Syndromic Surveillance ◽

The Arctic ◽

Validation Dataset ◽

Mass Gathering ◽

Syndromic Surveillance System ◽

Local Public Health ◽

Global Pandemic

Abstract Background: Automated syndromic surveillance systems are useful tools for rapidly identifying health risks during times when routine surveillance and follow-up cannot meet the demands of the population. In Yukon, Canada, the Arctic Winter Games were scheduled in March 2020, and were expected to increase the local population beyond the capacity of local public health surveillance. An emergency department-based automated syndromic surveillance system was therefore developed and validated using local hospitalization records for use during the event. Methods: Syndromes of interest were identified in consultation with the local public health authorities. For each syndrome, case definitions were developed using published resources and expert elicitation. Natural language processing algorithms were then written to detect syndromic cases from three different fields (triage notes; chief complaint; discharge diagnosis) using Yukon emergency department case data containing information from 19,082 visits over the period of October 1, 2018 to April 30, 2019. The automatic identification of cases was then manually validated by two raters and results were used to calculate positive predicted values for each syndrome and identify improvements to the detection algorithms. Results: A total of six syndromes were originally identified for the syndromic surveillance system (e.g., Gastrointestinal, Influenza-like-Illness, Mumps, Neurological Infections, Rash, Respiratory), with an additional syndrome added to assist in detecting potential cases of COVID-19. The positive predictive value for the automated detection of each syndrome ranged from 48.8%-89.5% to 62.5%-94.1% after implementing improvements identified during validation. As expected, no records were flagged for COVID-19 from our validation dataset. However, the system was rapidly adapted into an additional surveillance tool for use in the COVID-19 pandemic. Conclusions: Validation is an important step for measuring the accuracy of syndromic surveillance, and ensuring it performs adequately in a local context. Ultimately, the 2020 Arctic Winter Games were cancelled due to the risks associated with mass gatherings during the global pandemic of COVID-19 and could not therefore be tested under a mass gathering scenario. However, the results from our validation study suggest that our surveillance system may be useful for future mass gathering events and proved a timely development for integration into Yukon’s COVID-19 surveillance infrastructure.

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