scholarly journals Creation of a Kansas Spring Extreme Weather Syndrome Definition and Unique Records

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Zachary M. Stein
Keyword(s):  
Emergency Department ◽  
Health Effects ◽  
Syndromic Surveillance ◽  
Situational Awareness ◽  
Extreme Weather ◽  
Emergency Department Visits ◽  
Surveillance Program ◽  
Weather Events ◽  
Chief Complaints ◽  
Ed Visits

ObjectiveTo evaluate syndrome definitions capturing storm- and extremeweather-related emergency department visits in Kansas hospitalsparticipating in the National Syndromic Surveillance Program(NSSP).IntroductionKansas storms can occur without warning and have potential tocause a multitude of health issues. Extreme weather preparednessand event monitoring for public health effects is being developedas a function of syndromic surveillance at the Kansas Departmentof Health and Environment (KDHE). The Syndromic SurveillanceProgram at KDHE utilized emergency department (ED) data to detectdirect health effects of the weather events in the first 9 months of2016. Current results show injuries directly related to the storms andalso some unexpected health effects that warrant further exploration.MethodsA basic syndrome definition was defined based on extreme springand summer weather events experienced in Kansas. This broaddefinition pulled records from Kansas EDs that included the followingin the Chief Complaint or Triage Notes fields:●Storm●Rain●Torna(dos)●Wind●FloodThis broad syndrome definition was performed on data submittedto the Kansas’s production server through NSSP between January 1stand August 30th, 2016. After the initial pull, duplicate records for thesame patient and visit were removed.The remaining set was then searched by hand to identify termscaught by the syndrome definition that were not related to stormactivity or extreme weather. Record chief complaints were thenscanned by hand to identify common words containing the searchcriteria and then removed. Keywords not of interest to the syndromedefinition that were caught were: migraine, window, drain, restrain,train, and many other proper nouns that contained one of the keywords.These remaining visits were then sorted by nature of visit andunexpected records were recorded for future direction of syndromedefinition development.ResultsThe initial data pull under these conditions yielded 17,691 uniqueemergency department visits from January 1stto August 30thduringthe 2016 year. From this, records were classified based on key wordsresulting in the pull. The table below shows the initial pull results, theremaining records after errant results were expunged, the percentageof visits that were removed, and the most common reason for removal.Of these records remaining after cleaning, 20 were related tostorms, 62 were related to rain, 7 were related to tornado activity,66 were related to wind, and 14 were related to flooding along withthe mixed variable instances shown in the table. A majority of thewind-related ED visits were injuries and the majority of the tornadoactivity events were related to injuries sustained while taking shelter.Many of the injuries mentioning storms were sustained in preparationfor the storm, and a handful were due to mental stresses regardingstorm activity.ConclusionsSyndrome definition development is an iterative process thatwill vary by region. By manually looking at line-level data details,future searches can better accommodate these errant results and falsepositives. These studies will facilitate more rapid extreme weatherresponse in Kansas and allow better situational awareness. Alongwith general storm-related injuries, knowledge of the unusual recordscaught by a syndrome definition can also help direct public educationin preparation of future storms. With injuries sustained while takingshelter and injuries sustained in preparation for the storm, we can takethese unique ED visits and work on interventions to prevent futureoccurrences.

scholarly journals Monitoring Sexual Violence Trends in Emergency Department Visits Using Syndromic Data From the National Syndromic Surveillance Program—United States, January 2017–December 2019

2021 ◽  
Vol 111 (3) ◽  
pp. 485-493
Author(s):  
Ashley Schappell D'Inverno ◽  
Nimi Idaikkadar ◽  
Debra Houry
Keyword(s):  
United States ◽  
Emergency Department ◽  
Sexual Violence ◽  
Syndromic Surveillance ◽  
Age Groups ◽  
The United States ◽  
Emergency Department Visits ◽  
Surveillance Program ◽  
Time Period ◽  
Ed Visits

Objectives. To report trends in sexual violence (SV) emergency department (ED) visits in the United States. Methods. We analyzed monthly changes in SV rates (per 100 000 ED visits) from January 2017 to December 2019 using Centers for Disease Control and Prevention’s National Syndromic Surveillance Program data. We stratified the data by sex and age groups. Results. There were 196 948 SV-related ED visits from January 2017 to December 2019. Females had higher rates of SV-related ED visits than males. Across the entire time period, females aged 50 to 59 years showed the highest increase (57.33%) in SV-related ED visits, when stratified by sex and age group. In all strata examined, SV-related ED visits displayed positive trends from January 2017 to December 2019; 10 out of the 24 observed positive trends were statistically significant increases. We also observed seasonal trends with spikes in SV-related ED visits during warmer months and declines during colder months, particularly in ages 0 to 9 years and 10 to 19 years. Conclusions. We identified several significant increases in SV-related ED visits from January 2017 to December 2019. Syndromic surveillance offers near-real-time surveillance of ED visits and can aid in the prevention of SV.

scholarly journals Monitoring Out-of-State Patients during a 2017 Hurricane Response using ESSENCE

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Caleb Wiedeman ◽  
Julie Shaffner ◽  
Kelly Squires ◽  
Jeffrey Leegon ◽  
Rendi Murphree ◽  
...  
Keyword(s):  
Emergency Department ◽  
Syndromic Surveillance ◽  
Situational Awareness ◽  
Chief Complaint ◽  
Free Text ◽  
Chief Complaints ◽  
Major Hurricane ◽  
Ed Visits ◽  
Zip Code ◽  
Hurricane Irma

ObjectiveTo demonstrate the use of ESSENCE in the BioSense Platform to monitor out-of-State patients seeking emergency healthcare in Tennessee during Hurricanes Harvey and Irma.IntroductionSyndromic surveillance is the monitoring of symptom combinations (i.e., syndromes) or other indicators within a population to inform public health actions. The Tennessee Department of Health (TDH) collects emergency department (ED) data from more than 70 hospitals across Tennessee to support statewide syndromic surveillance activities. Hospitals in Tennessee typically provide data within 48 hours of a patient encounter. While syndromic surveillance often supplements disease- or condition-specific surveillance, it can also provide general situational awareness about emergency department patients during an event or response.During Hurricanes Harvey (continental US landfall on August 25, 2017) and Irma (continental US landfall on September 10, 2017), TDH supported all hazards situational awareness using the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) in the BioSense Platform supported by the National Syndromic Surveillance Program (NSSP). The volume of out-of-state patients in Tennessee was monitored to assess the impact on the healthcare system and any geographic- or hospital-specific clustering of out-of-state patients within Tennessee. Results were included in daily State Health Operations Center (SHOC) situation reports and shared with agency response partners such as the Tennessee Emergency Management Agency (TEMA).MethodsData were monitored from August 18, 2017 through September 24, 2017. A simple query was established in ESSENCE using the Patient Location (Full Details) dataset. Data were limited to hospital ED visits reported by Tennessee (Site = “Tennessee”). To monitor ED visits among residents of Texas before, during, and after Major Hurricane Harvey, data were queried for a patient zip code within Texas (State = “Texas”). ED visits among Florida residents were monitored similarly (State = “Florida”) before, during, and after Major Hurricane Irma. Additionally, a free text chief complaint search was implemented for the terms “Harvey”, “Irma, “hurricane”, “evacuee”, “evacuate”, “Florida”, and “Texas”. Chief complaint search results were then filtered to remove encounters with patient zip codes within Tennessee.ResultsFrom August 18, 2017 through September 24, 2017, Tennessee hospital EDs reported 277 patient encounters among Texas residents and 1,041 patient encounters among Florida residents. The number of encounters among patients from Texas remained stable throughout the monitoring period. In contrast, the number of encounters among patients from Florida exceeded the expected value on September 7, peaked September 10 at 116 patient encounters, and returned to expected levels on September 16 (Figure 1). The increase in patients from Florida was evenly distributed across most of Tennessee, with some clustering around a popular tourism area in East Tennessee. No concerning trends in reported syndromes or chief complaints were identified among Texas or Florida patients.The free text chief complaint query first exceeded the expected value on September 9, peaked on September 11 with 5 patient encounters, and returned to expected levels on September 14. From August 18 through September 24, 21 of 30 visits captured by the query were among Florida residents. One Tennessee hospital appeared to be intentionally using the term “Irma” in their chief complaint field to indicate patients from Florida impacted by the hurricane.ConclusionsThe ESSENCE instance in the BioSense platform provided TDH the opportunity to easily locate and monitor out-of-state patients seen in Tennessee hospital EDs. While TDH was unable to validate whether all patients identified as residents of Florida were displaced because of Major Hurricane Irma, the timing of the rise and fall of patient encounters was highly suggestive. Likewise, seeing no substantial increase ED patients with residence in Texas reassured TDH that the effects of Hurricane Harvey were not impacting hospital emergency departments in Tennessee.TDH used information and charts from ESSENCE to support situational awareness in our SHOC and at TEMA. Use of patient zip code to identify out-of-state residents was more sensitive than chief complaint searches by keyword during this event. ESSENCE allowed TDH to see where out-of-state patients appeared to be concentrating in Tennessee and monitor the need for targeting messaging and resources to heavily affected areas. Additionally, close surveillance of chief complaints among out-of-state patients provided assurance that no unusual patterns in illness or injury were occurring.ESSENCE is the only TDH information source capable of rapidly collecting health information on out-of-state patients. ESSENCE allowed TDH to quickly identify a change within the patient population seen at Tennessee emergency departments and monitor the situation until the patient population returned to baseline levels.

scholarly journals Syndromic Surveillance of Emergency Department Visits for Acute Adverse Effects of Marijuana, Tri-County Health Department, Colorado, 2016-2017

2019 ◽  
Vol 134 (2) ◽  
pp. 132-140 ◽  
Author(s):  
Grace E. Marx ◽  
Yushiuan Chen ◽  
Michele Askenazi ◽  
Bernadette A. Albanese
Keyword(s):  
Emergency Department ◽  
Adverse Effects ◽  
Medical Records ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Marijuana Use ◽  
Emergency Department Visits ◽  
Diagnostic Codes ◽  
Icd 10 ◽  
Ed Visits

Objectives: In Colorado, legalization of recreational marijuana in 2014 increased public access to marijuana and might also have led to an increase in emergency department (ED) visits. We examined the validity of using syndromic surveillance data to detect marijuana-associated ED visits by comparing the performance of surveillance queries with physician-reviewed medical records. Methods: We developed queries of combinations of marijuana-specific International Classification of Diseases, Tenth Revision (ICD-10) diagnostic codes or keywords. We applied these queries to ED visit data submitted through the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE) syndromic surveillance system at 3 hospitals during 2016-2017. One physician reviewed the medical records of ED visits identified by ≥1 query and calculated the positive predictive value (PPV) of each query. We defined cases of acute adverse effects of marijuana (AAEM) as determined by the ED provider’s clinical impression during the visit. Results: Of 44 942 total ED visits, ESSENCE queries detected 453 (1%) as potential AAEM cases; a review of 422 (93%) medical records identified 188 (45%) true AAEM cases. Queries using ICD-10 diagnostic codes or keywords in the triage note identified all true AAEM cases; PPV varied by hospital from 36% to 64%. Of the 188 true AAEM cases, 109 (58%) were among men and 178 (95%) reported intentional use of marijuana. Compared with noncases of AAEM, cases were significantly more likely to be among non-Colorado residents than among Colorado residents and were significantly more likely to report edible marijuana use rather than smoked marijuana use ( P < .001). Conclusions: ICD-10 diagnostic codes and triage note keyword queries in ESSENCE, validated by medical record review, can be used to track ED visits for AAEM.

scholarly journals Syndromic Surveillance for Situation Awareness: Understanding Syndrome Performance

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Kristin Arkin
Keyword(s):  
Emergency Department ◽  
Situation Awareness ◽  
Syndromic Surveillance ◽  
Chief Complaint ◽  
Surveillance Program ◽  
Initial Visit ◽  
Word Count ◽  
Data Submission ◽  
Daily Frequency ◽  
Ed Visits

ObjectiveIn August 2017, a large influx of visitors was expected to view the total solar eclipse in Idaho. The Idaho Syndromic Surveillance program planned to enhance situation awareness during the event. In preparation, we sought to examine syndrome performance of several newly developed chief complaint and combination chief complaint and diagnosis code syndrome definitions to aid in interpretation of syndromic surveillance data during the event.IntroductionThe August 21, 2017 total solar eclipse in Idaho was anticipated to lead to a large influx of visitors in many communities, prompting a widespread effort to assure Idaho was prepared. To support these efforts, the Idaho Syndromic Surveillance program (ISSp) developed a plan to enhance situation awareness during the event by conducting syndromic surveillance using emergency department (ED) visit data contributed to the National Syndromic Surveillance Program’s BioSense platform by Idaho hospitals. ISSp sought input on anticipated threats from state and local emergency management and public health partners, and selected 8 syndromes for surveillance.Ideally, the first electronic message containing information on an emergency department visit is sent to ISSp within 24 hours of the visit and includes the chief complaint for the visit. Data on other variables, such as diagnosis codes, are updated by subsequent messages for several days after the visit. Chief complaint (CC) text and discharge diagnosis (DD) codes are the primary variables used for syndrome match; delay in reporting these variables adversely affects timely syndrome match of visits. Because our plan included development of new syndrome definitions and querying data within 24 hours of visits, earlier than ISSp had done previously for trend analysis, we sought to better understand syndrome performance.MethodsWe defined messages with completed CC and DD as the last message regarding a visit where term count increased from previous messages regarding that visit, indicating new information was added to the field. We retrospectively assessed the total number of ED visits and calculated the daily frequency of completed CC and DD by days since visit date for visits during June 1–July 31, 2017. Additionally, we calculated facility mean word count in CC fields by averaging the word count of parsed, complete CC fields for visits occurring June 1–July 31, 2017 for each facility.During July 10–24, 2017, we calculated the daily frequency of visits occurring in the previous 90 days for total ED visits and syndrome-matched visits for 8 selected syndromes (heat-related illness; cold exposure; influenza-like-illness; nausea, vomiting, and diarrhea; animal/bug bites and stings; drowning/submersion; alcohol/drug intoxication; and medication replacement). Syndrome-matched visits were defined as visits with CC or DD that match the syndrome definition. We calculated the percent of syndrome-matched visits by syndromes defined with CC or CC and DD combined (CCDD) over time. Syndromes with fewer than 5 matched visits were excluded from analysis.ResultsComplete CCs were received for 99.1% of visits and complete DDs were received for 89.8% of visits. Complete CCs were submitted for 58.2% of visits within 1 day of the visit, 88.9% of visits within 3 days, and 98.9% of visits within 7 days. In contrast, complete DDs were submitted for 24.3% of visits within 1 day, 38.7% of visits within 3 days, and 53.7% of visits within 7 days (Table 1).During the observation period, data submission from facilities representing approximately 33% of visits was interrupted for 5 (36%) of 14 days. Heat-related illness, cold exposure, and drowning/submersion, were excluded from syndrome-match analysis. During the 9 days of uninterrupted data submission, 100% syndrome-matched visits for syndromes defined by CC alone and 69.1% syndrome-matched visits for syndromes defined by CCDD were identified within 6–7 days of initial visit. Facilities with interrupted data submission contributed 75% of CC syndrome-matched visits and 33% of CCDD syndrome-matched visits. The facility mean word count in CC fields from these facilities was >15 compared with 2–4 from other facilities.ConclusionsExamination of syndrome performance prior to a known event quantitated differences in timeliness of CC and DD completeness and syndrome match. CCs and DDs in visit messages were not complete within 24 hours of initial visit. CC completion was nearly 34 percentage points greater than DD completeness 1 day after initial visit and did not converge until ≥15 days after initial visit. Higher percentages of syndrome match within 6–7 days of initial visit were seen by CC alone than CCDD defined syndromes. Facilities using longer CCs contributed disproportionately to syndrome matching using CC, but not CCDD syndrome definitions. Syndromic surveillance system characteristics, including timeliness of CCs and DDs, length of CCs, and characteristics of facilities from which data transmission is interrupted should be considered when building syndrome definitions that will be used for surveillance within 7 days of emergency department visits and when interpreting syndromic surveillance findings.

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

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.

scholarly journals National and Regional Representativeness of Hospital Emergency Department Visit Data in the National Syndromic Surveillance Program, United States, 2014

2016 ◽  
Vol 10 (4) ◽  
pp. 562-569 ◽  
Author(s):  
Ralph J. Coates ◽  
Alejandro Pérez ◽  
Atar Baer ◽  
Hong Zhou ◽  
Roseanne English ◽  
...  
Keyword(s):  
Emergency Department ◽  
Syndromic Surveillance ◽  
Surveillance Program ◽  
Local Health ◽  
Hospital Emergency Department ◽  
Hospital Emergency ◽  
American Hospital ◽  
American Hospital Association ◽  
Ed Visits ◽  
State And Local

AbstractObjectiveWe examined the representativeness of the nonfederal hospital emergency department (ED) visit data in the National Syndromic Surveillance Program (NSSP).MethodsWe used the 2012 American Hospital Association Annual Survey Database, other databases, and information from state and local health departments participating in the NSSP about which hospitals submitted data to the NSSP in October 2014. We compared ED visits for hospitals submitting data with all ED visits in all 50 states and Washington, DC.ResultsApproximately 60.4 million of 134.6 million ED visits nationwide (~45%) were reported to have been submitted to the NSSP. ED visits in 5 of 10 regions and the majority of the states were substantially underrepresented in the NSSP. The NSSP ED visits were similar to national ED visits in terms of many of the characteristics of hospitals and their service areas. However, visits in hospitals with the fewest annual ED visits, in rural trauma centers, and in hospitals serving populations with high percentages of Hispanics and Asians were underrepresented.ConclusionsNSSP nonfederal hospital ED visit data were representative for many hospital characteristics and in some geographic areas but were not very representative nationally and in many locations. Representativeness could be improved by increasing participation in more states and among specific types of hospitals. (Disaster Med Public Health Preparedness. 2016;10:562–569)

scholarly journals Analysis of Emergency Department Visits for Motor Vehicle Injuries in Utah, 2016

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Akanksha Acharya
Keyword(s):  
Emergency Department ◽  
Syndromic Surveillance ◽  
Motor Vehicle ◽  
The United States ◽  
Emergency Department Visits ◽  
Motor Vehicle Crashes ◽  
Vehicle Crashes ◽  
Increased Risk ◽  
Ed Visits ◽  
Motor Vehicle Injuries

ObjectiveTo describe the characteristics of emergency department (ED) visits for motor vehicle injuries in Utah using 2016 syndromic surveillance data.IntroductionMotor vehicle injury is the leading cause of death in injury category in the United States. In 2016, motor vehicle crashes were one of the main causes of death resulting from injury (8.8 per 100,000 population) in Utah. Motor vehicle crashes can lead to physical and economic consequences that impact the lives of individuals and their families. In addition, the treatment of injuries places an enormous burden on hospital Emergency Departments (EDs). Currently; there are no data sources other than syndromic data in the Utah Department of Health to monitor ED visits due to motor vehicle injuries in real time.MethodsUtah participates in the National Syndromic Surveillance Program (NSSP) to which all hospitals in the state submit ED visit data via the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE). ESSENCE was used to analyze 2016 ED visit data. Total population data were obtained from Utah population estimates. Data from 2017 was not included due to major system changes at a major healthcare system that interrupted data feeds resulting in lower than expected data volume.Motor vehicle injury is defined by existing subsyndrome definition in the Centers for Disease Control and Prevention ESSENCE system. All ED visit data were analyzed by querying key terms in the chief complaint field including any mention of: vehicle, wheeler, motorcycle, motor scooter, motor cycle, motor cross, truck, motorbike etc. Exclusion terms included any mention of: car dealership, hit head and car door. Ages were divided into seven groups for data distribution and comparison: 0–17, 18–24, 25–34, 35–44, 45–54, 55–64 and ≥ 65 years.ResultsIn 2016, a total of 28,472 ED visits (2% of total visits) were identified using the motor vehicle injury query. The ED visit rate for motor vehicle injuries was highest among persons aged 18–24 years (1,682 per 100,000 population). Rates continued to decline with increasing age after 18–24 years. The rate of females visiting the ED was higher than males (1,040 versus 826 per 100,000 population respectively; p < 0.01) (Figure 1). The majority of injuries (11722(52%)) were reported between 10:00 a.m. and 5:59 p.m. Injuries were highest August-September (5913(22%)).ConclusionsSyndromic data is a robust source of data for analyzing ED visits due to motor vehicle injuries in real time, and providing information to injury prevention programs for targeting interventions. Our data suggest an increased risk of visiting an ED due to motor vehicle injuries by age group (18-24 year olds), sex (females), month (August-September), and time (10:00 a.m. to 5:59 p.m.). These results do not include visits with incomplete or incorrectly coded chief complaints or discharge codes, patients of motor vehicle injuries who do not present to the ED, or not classified as ‘emergency’ patient class.

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

2019 ◽  
Vol 11 (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.

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.

scholarly journals Assessing Prior Pain Visits and Medical History Risk Factors for Opioid Overdose

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Andrew Walsh
Keyword(s):  
Emergency Department ◽  
Logistic Regression ◽  
Odds Ratio ◽  
The United States ◽  
Emergency Department Visits ◽  
Specific Patient ◽  
Syndromic Surveillance System ◽  
Chief Complaints ◽  
History Of ◽  
Ed Visits

Objective: Identifying text features of emergency department visits associated with risk of future drug overdose.Introduction: Opioid overdoses are a growing cause of mortality in the United States.1 Medical prescriptions for opioids are a risk factor for overdose2. This observation raises concerns that patients may seek multiple opioid prescriptions, possibly increasing their overdose risk. One route for obtaining those prescriptions is visiting the emergency department (ED) for pain-related complaints. Here, two hypotheses related to prescription seeking and overdoses are tested. (1) Overdose patients have a larger number of prior ED visits than matched controls. (2) Overdose patients have distinct patterns of pain-related complaints compared to matched controls.Methods: ED registrations were collected via the EpiCenter syndromic surveillance system. Regular expression searches on chief complaints identified overdose visits. Overdose visits were matched with control visits from the same facility with maximal similarity of gender, age, home location and arrival time.A year of prior ED visits for cases and controls were matched using facility-specific patient identifiers or birthdate, gender and home location.Patient history chief complaints were sanitized to standardize spelling, expand abbreviations and consolidate phrases. Word frequency comparisons between groups identified candidate terms for modeling.Odds ratios of patient history terms were calculated with univariate logistic regression. Multivariate lasso logistic regression selected covariates for prediction. These models were fit to data from one quarter and cutoffs for covariate inclusion were validated on the following quarter’s data. Model predictions were validated on a 1% sample of ED registrations from the next quarter.Results: Quarter three of 2016 yielded 23,769 overdose ED visits and matching controls; quarter four yielded 21,957 pairs; and 15,824 ED visits were sampled from the first quarter of 2017 including 130 overdose visits.Contrary to expectations, patients in the control group averaged 0.7 additional ED visits in the prior year relative to controls; this pattern was consistent across quarters and regardless of how prior visits were matched (Fig 1).Prior visits for various pain categories were also more common among control patients than overdose patients (e.g. odds ratio for “back pain”: 0.78). Terms associated with drug use (e.g. “detox” odds ratio: 2.66) and mental health concerns (e.g. “psychological” odds ratio: 4.28) were most consistently overrepresented in the history of overdose patients (Table 1). Terms associated with chronic disease were most overrepresented in the history of control patients (Table 2).The best predictive model achieved a sensitivity of 57% and a specificity of 86% on test data (Fig 2).Conclusions: While a history of more overall ED visits and more ED visits related to pain were not associated with overdose ED visits, vocabulary of prior ED visits did predict future overdose ED visits. Performance of predictive models exceeded expectations, given the relative scarcity of overdoses among ED visits and the simplicity of chief complaints used for prediction. The correlation between past and future overdose visits highlights the need for targeted intervention to break addiction cycles.

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