scholarly journals Travel and Triage: Pilot project to detect infections after medical tourism procedures

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Pinar Erdogdu ◽  
Barbara Carothers ◽  
Rebecca Greeley ◽  
Stella Tsai
Keyword(s):  
Public Health ◽  
Data Mining ◽  
New Jersey ◽  
Syndromic Surveillance ◽  
Surgical Site Infections ◽  
Chief Complaint ◽  
Syndromic Surveillance System ◽  
Cosmetic Procedure ◽  
The Us ◽  
Ed Visits

Objective: Medical notes provide a rich source of information that can be used as additional supporting information for healthcare-associated infection (HAI) investigations. The medical notes from 10 New Jersey (NJ) emergency departments (ED) were searched to identify cases of surgical-site infections (SSI).Introduction: EpiCenter, NJ’s statewide syndromic surveillance system, collects ED registration data. The system uses chief complaint data to classify ED visits into syndrome categories and provides alerts to state and local health departments for surveillance anomalies.After the 2014 Ebola outbreak in West Africa, the New Jersey Department of Health (NJDOH) started collecting medical notes including triage notes, which contain more specific ED visit information than chief complaint, from 10 EDs to strengthen HAI syndromic surveillance efforts.In 2017, the NJDOH was aware of one NJ resident whose surgical site was infected following a cosmetic procedure outside of the US. This event triggered an intensive data mining using medical notes collected in EpiCenter. The NJDOH staff searched one week of medical notes data in EpiCenter with a specific keyword to identify additional potential cases of surgical-site infections (SSI) that could be associated with medical tourism.Methods: The NJ resident whose surgical site was infected following a cosmetic procedure outside of the US was interviewed by NJDOH staff for details about their procedure. First, the patient’s interview results were reviewed to prepare a set of SSI and travel related keywords to be used in performing data mining in medical notes collected in EpiCenter. The interviewed patient had tummy tuck and liposuction surgeries; therefore, it was decided to search for “tummy tuck” as a keyword in EpiCenter. The medical notes from August 31, 2017 through September 8, 2017 were reviewed to identify patients who developed SSI following a cosmetic procedure outside of the US.Results: The search yielded 8 ED visits, one of which was identified as possible surgical site infection. The medical notes details indicated that the ED patient, a 21-year old female who had abdominoplasty (tummy tuck) and liposuction surgeries about a month prior, presented with post-surgical complaints such as pain, surgical dehiscence, and purulent drainage at the surgery site. Chief complaint text for the same ED patient indicated the patient had headache and dizziness which were less specific than medical notes.The NJDOH staff contacted the ED to obtain additional information regarding the infection. The lab results from the ED showed that the patient was identified as having a post-surgery infection, which prompted public health to follow-up whether it was an HAI.Conclusions: The limitation for this project was that the keyword search was conducted only on one week of data. The timeframe was kept short to pilot testing the keyword identified. The Centers for Disease Control and Prevention suggests clinicians should consider nontuberculous mycobacteria (NTM) infections in the differential diagnosis for all people who have wound infections after surgery abroad, including surgery that has occurred weeks to months previously (1). Future studies will explore larger data sets with additional keywords (e.g. country and organism) to see if potential cases can be identified as possible HAI and/or outbreak that will lead to public health investigations.

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

2017 ◽  
Vol 132 (1_suppl) ◽  
pp. 73S-79S ◽  
Author(s):  
Elizabeth R. Daly ◽  
Kenneth Dufault ◽  
David J. Swenson ◽  
Paul Lakevicius ◽  
Erin Metcalf ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
New Hampshire ◽  
Syndromic Surveillance ◽  
Situational Awareness ◽  
The United States ◽  
Chief Complaint ◽  
Public Health Response ◽  
Syndromic Surveillance System ◽  
Icd Codes

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.

scholarly journals Outbreak of ED visits related to the use of synthetic cannabinoids, Mayotte Island

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Pascal Vilain ◽  
Salamta Bah-Assoumani ◽  
Ali-Mohamed Youssouf ◽  
Laurent Filleul
Keyword(s):  
Public Health ◽  
Behavioral Disorders ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Adverse Reactions ◽  
Health Agency ◽  
Case Definition ◽  
Syndromic Surveillance System ◽  
Ed Visits ◽  
Mental And Behavioral Disorders

ObjectiveTo confirm and to characterize the increase in emergency department (ED) visits related to the use of synthetic cannabinoids (SC)IntroductionOn October 2016, the Indian Ocean Regional Health Agency was alerted about an increase in ED visits related to adverse reactions associated with use of SC on Mayotte Island. In this context, an investigation based on a syndromic surveillance system was implemented by the regional unit of the French national public health agency.MethodsAn extraction of anonymized records routinely collected by the syndromic surveillance system (1) was carried out from January 1st, 2012 to October 30, 2016. ED visits related to the consumption of SC were identified from ICD-10 codes of the principal diagnostic according to two levels of confidence:- a probable case was defined as ED visit coded X69 (Intentional self-poisoning by and exposure to other and unspecified chemicals and noxious substances). This code has been implemented specifically by ED physicians since august 2015;- a suspect case was defined as ED visit coded: F11 (Mental and behavioral disorders due to use of opioids), F12 (Mental and behavioral disorders due to use of cannabinoids), F16 (Mental and behavioral disorders due to use of hallucinogens), F18 (Mental and behavioral disorders due to use of volatile solvents), F19 (Mental and behavioral disorders due to multiple drug use and use of other psychoactive substances).Based on these data, an epidemic curve and a descriptive analysis of ED visits were carried out.ResultsIn total, 146 ED visits related to adverse events associated with use of SC were registered from January 1st, 2012 to October 30, 2016. The epidemic curve shows two waves between 2015 and 2016 with a particularly high peak in August 2015 (Figure 1). In total, 49% (n=72/146) of these ED visits were probably related to adverse reactions associated to use SC and 51% (n=74/146) meet to the suspect case definition. On the surveillance period, men represented 84% of the patients (n=122) and median age (min – max) was 23 (8-62) years old. When the severity score variable was filled (n = 138), a vital emergency was reported for 4% (n = 5) of patients and 19% of patients were hospitalized.ConclusionsData from syndromic surveillance system allowed to confirm an increase in ED visits related to adverse reactions associated with use of SC in Mayotte Island. To our knowledge, it’s the first time that an outbreak related to use SC is described in the Ocean Indian areaThis phenomenon was particularly marked in 2015 with a peak of ED visits on August 2016.After this outbreak, the regional unit of the French national public health agency recommended the pursuit of the coding X69 in principal diagnosis with the following case definition: any patient with an adverse reaction attributed to synthetic cannabinoid use whether suspected by the medical team or declared by the patient himself or if the patient is in possession of the substance; and to raise awareness ED physicians to the notification of these poisonings to the Regional Addictive Surveillance Center.In conclusion, the young population, weakened by a precarious socio-economic situation, is a target for new synthetic drugs and a threat to public health. This emerging risk in Mayotte must be taken into account and must be actively monitored. In this context, collaborative work with the emergency services must continue in parallel with targeted prevention measures.References1. Vilain P, Maillard O, Raslan-Loubatie J, Abdou MA, Lernout T, Filleul L. Usefulness of Syndromic Surveillance for Early Outbreak Detection in Small Islands: The Case of Mayotte. Online Journal of Public Health Informatics. 2013;5(1):e149.

scholarly journals Characterizing the Effects of Extreme Cold Using Real-time Syndromic Surveillance, Ontario, Canada, 2010-2016

2017 ◽  
Vol 132 (1_suppl) ◽  
pp. 48S-52S ◽  
Author(s):  
Nancy VanStone ◽  
Adam van Dijk ◽  
Timothy Chisamore ◽  
Brian Mosley ◽  
Geoffrey Hall ◽  
...  
Keyword(s):  
Public Health ◽  
Acute Care ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Cold Temperature ◽  
Syndromic Surveillance System ◽  
Southern Ontario ◽  
Threshold Temperatures ◽  
Ed Visits ◽  
Extreme Cold

Morbidity and mortality from exposure to extreme cold highlight the need for meaningful temperature thresholds to activate public health alerts. We analyzed emergency department (ED) records for cold temperature–related visits collected by the Acute Care Enhanced Surveillance system—a syndromic surveillance system that captures data on ED visits from hospitals in Ontario—for geographic trends related to ambient winter temperature. We used 3 Early Aberration Reporting System algorithms of increasing sensitivity—C1, C2, and C3—to determine the temperature at which anomalous counts of cold temperature–related ED visits occurred in northern and southern Ontario from 2010 to 2016. The C2 algorithm was the most sensitive detection method. Results showed lower threshold temperatures for Acute Care Enhanced Surveillance alerts in northern Ontario than in southern Ontario. Public health alerts for cold temperature warnings that are based on cold temperature–related ED visit counts and ambient temperature may improve the accuracy of public warnings about cold temperature risks.

scholarly journals Flexibility of ED surveillance system to monitor dengue outbreak in Reunion Island

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Pascal Vilain ◽  
Muriel Vincent ◽  
Anne Fouillet ◽  
Katia Mougin-Damour ◽  
Xavier Combes ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Reunion Island ◽  
Regional Office ◽  
Syndromic Surveillance System ◽  
Dengue Outbreak ◽  
Icd 10 ◽  
Réunion Island ◽  
Ed Visits

ObjectiveTo describe the characteristics of ED vitis related to dengue fever and to show how the syndromic surveillance system can be flexible for the monitoring of this outbreak.IntroductionIn Reunion Island, a French overseas territory located in the southwestern of Indian Ocean, the dengue virus circulation is sporadic. Since 2004, between 10 and 221 probable and confirmed autochthonous dengue fever cases have been reported annually. Since January 2018, the island has experienced a large epidemic of DENV serotype 2. As of 4 September 2018, 6,538 confirmed and probable autochthonous cases have been notified1. From the beginning of the epidemic, the regional office of National Public Health Agency (ANSP) in Indian Ocean enhanced the syndromic surveillance system in order to monitor the outbreak and to provide hospital morbidity data to public health authorities.MethodsIn Reunion Island, the syndromic surveillance system called OSCOUR® network (Organisation de la Surveillance Coordonnée des Urgences) is based on all emergency departments (ED)2. Anonymous data are collected daily directly from the patients’ computerized medical files completed during medical consultations. Every day, data files are sent to the ANSP via a regional server over the internet using a file transfer protocol. Each file transmitted to ANSP includes all patient visits to the ED logged during the previous 24 hours (midnight to midnight). Finally, data are integrated in a national database (including control of data quality regarding authorized thesauri) and are made available to the regional office through an online application3.Following the start of dengue outbreak in week 4 of 2018, the regional office organized meetings with physicians in each ED to present the dengue epidemiological update and to recommend the coding of ED visit related to dengue for any suspect case (acute fever disease and two or more of the following signs or symptoms: nausea, vomiting, rash, headache, retro-orbital pain, myalgia). During these meetings, it was found that the version of ICD-10 (International Classification of Diseases) was different from one ED to another. Indeed, some ED used A90, A91 (ICD-10 version: 2015) for visit related to dengue and others used A97 and subdivisions (ICD-10 version: 2016). As the ICD-10 version: 2015 was implemented at the national server, some passages could be excluded. In this context, the thesaurus of medical diagnosis implemented in the national database has been updated so that all codes can be accepted. ED visits related to dengue fever has been then described according to age group, gender and hospitalization.ResultsFrom week 9 of 2018, the syndromic surveillance system was operational to monitor dengue outbreak. The regional office has provided each week, an epidemic curve of ED visits for dengue and a dashboard on descriptive characteristic of these visits. In total, 441 ED visits for dengue were identified from week 9 to week 34 of 2018 (Figure 1). On this period, the weekly number of ED visits for dengue was correlated with the weekly number of probable and confirmed autochthonous cases (rho=0.86, p<0.001). Among these visits, the male/female ratio was 0.92 and median (min-max) age was 44 (2-98) years. The distribution by age group showed that 15-64 year-old (72.1%, n=127) were most affected. Age groups 65 years and more and 0-14 year-old represented respectively 21.8% (n=96) and 6.1% (n=27) of dengue visits. About 30% of dengue visits were hospitalized.ConclusionsAccording Buehler et al., “the flexibility of a surveillance system refers to the system's ability to change as needs change. The adaptation to changing detection needs or operating conditions should occur with minimal additional time, personnel, or other resources. Flexibility generally improves the more data processing is handled centrally rather than distributed to individual data-providing facilities because fewer system and operator behavior changes are needed...” 4.During this dengue outbreak, the syndromic surveillance system seems to have met this purpose. In four weeks (from week 5 to week 9 of 2018), the system was able to adapt to the epidemiological situation with minimal additional resources and personnel. Indeed, updates were not made in the IT systems of each EDs’ but at the level of the national ANSP server (by one person). This surveillance system was also flexible thank to the reactivity of ED physicians who timely implemented coding of visits related to dengue fever.In conclusion, ED surveillance system constitutes an added-value for the dengue outbreak monitoring in Reunion Island. The automated collection and analysis data allowed to provide hospital morbidity (severe dengue) data to public health authorities. Although the epidemic has decreased, this system also allows to continue a routine active surveillance in order to quickly identify a new increase.References1Santé publique France. Surveillance de la dengue à la Réunion. Point épidémiologique au 4 septembre 2018. http://invs.santepubliquefrance.fr/fr/Publications-et-outils/Points-epidemiologiques/Tous-les-numeros/Ocean-Indien/2018/Surveillance-de-la-dengue-a-la-Reunion.-Point-epidemiologique-au-4-septembre-2018. [Accessed September 8, 2018].2Vilain P, Filleul F. La surveillance syndromique à la Réunion : un système de surveillance intégré. [Syndromic surveillance in Reunion Island: integrated surveillance system]. Bulletin de Veille Sanitaire. 2013;(21):9-12. http://invs.santepubliquefrance.fr/fr/Publications-et-outils/Bulletin-de-veille-sanitaire/Tous-les-numeros/Ocean-indien-Reunion-Mayotte/Bulletin-de-veille-sanitaire-ocean-Indien.-N-21-Septembre-2013. [Accessed September 4, 2018].3Fouillet A, Fournet N, Caillère N et al. SurSaUD® Software: A Tool to Support the Data Management, the Analysis and the Dissemination of Results from the French Syndromic Surveillance System. OJPHI. 2013; 5(1): e118.4Buehler JW, Hopkins RS, Overhage JM, Sosin DM, Tong V; CDC Working Group. Framework for evaluating public health surveillance systems for early detection of outbreaks: recommendations from the CDC Working Group. MMWR Recomm Rep. 2004;53(RR-5):1-11.

scholarly journals Using ESSENCE to Detect Bomb-Making Activity: What’s Appropriate?

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Andrew Torgerson
Keyword(s):  
Public Health ◽  
Law Enforcement ◽  
Syndromic Surveillance ◽  
Chief Complaint ◽  
Surveillance Data ◽  
Chemical Mechanism ◽  
Mass Gathering ◽  
Surveillance Period ◽  
Saint Louis ◽  
Ed Visits

ObjectiveTo describe a novel application of ESSENCE by the Saint Louis County Department of Public Health (DPH) in preparation for a mass gathering and to encourage discussion about the appropriateness of sharing syndromic surveillance data with law enforcement partners.IntroductionIn preparation for mass gathering events, DPH conducts enhanced syndromic surveillance activities to detect potential cases of anthrax, tularemia, plague, and other potentially bioterrorism-related communicable diseases. While preparing for Saint Louis to host a Presidential Debate on October 9, 2016, DPH was asked by a partner organization whether we could also detect emergency department (ED) visits for injuries (e.g., burns to the hands or forearms) that could possibly indicate bomb-making activities.MethodsUsing the Electronic Surveillance System for the Notification of Community-Based Epidemics (ESSENCE), version 1.9, DPH developed a simple query to detect visits to EDs in Saint Louis City or Saint Louis County with chief complaints including the word “burn” and either “hand” or “arm.” A DPH epidemiologist reviewed the results of the query daily for two weeks before and after the debate (i.e., from September 25, 2016 to October 23, 2016). If any single ED visit was thought to be “suspicious” – if, for example, the chief complaint mentioned an explosive or chemical mechanism of injury – then DPH would contact the ED for details and relay the resulting information to the county’s Emergency Operations Center.ResultsDuring the 29 day surveillance period, ESSENCE detected 27 ED visits related to arm or hand burns. The ESSENCE query returned a median of 1 ED visit per day (IQR 0 to 2 visits). Of these, one was deemed to merit further investigation – two days before the debate, a patient presented to an ED in Saint Louis County complaining of a burned hand. The patient’s chief complaint data also mentioned “explosion of unspecified explosive materials.” Upon investigation, DPH learned that the patient had been injured by a homemade sparkler bomb. Subsequently, law enforcement determined that the sparkler bomb had been made without any malicious intent.ConclusionsDPH succeeded in using ESSENCE to detect injuries related to bomb-making. However, this application of ESSENCE differs in at least two ways from more traditional uses of syndromic surveillance. First, conventional syndromic surveillance is designed to detect trends in ED visits resulting from an outbreak already in progress or a bioterrorist attack already carried out. In this case, syndromic surveillance was used to detect a single event that could be a prelude to an attack. The potential to prevent widespread injury or illness is a strength of this approach. Second, conventional syndromic surveillance identifies potential outbreak cases or, in the case of a bioterrorist attack, potential victims. In this case, syndromic surveillance was used to identify a potential perpetrator of an attack. While public health and law enforcement agencies would ideally coordinate their investigative efforts in the wake of an attack, this practice has led to conversations within DPH about the appropriateness of routinely sharing public health surveillance data with law enforcement. 

scholarly journals Evaluation of ESSENCE Syndromic Definitions for ED Visits Related to Falls in Icy Weather

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Jessica Hensley ◽  
Sandra Gonzalez ◽  
Derry Stover ◽  
Thomas Safranek ◽  
Ming Qu
Keyword(s):  
Public Health ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
Syndromic Surveillance ◽  
Hospital Admissions ◽  
Chief Complaint ◽  
Surveillance Program ◽  
Search Terms ◽  
Ed Visits ◽  
Sensitivity Specificity

ObjectiveThis project evaluated and compared two ESSENCE syndromic surveillance definitions for emergency department (ED) visits related to injuries associated with falls in icy weather using 2016-2017 data from two hospitals in Douglas County, Nebraska. The project determined the validity of the syndromic surveillance definition as applied to chief complaint and triage notes and compared the chief complaint data alone to chief complaint plus triage notes definitions to find the most reliable definition for ED visits resulting from fall-related injuries.IntroductionIcy weather events increase the risk for injury from falls on untreated or inadequately treated surfaces. These events often result in ED visits, which represents a significant public health and economic impact1.The goal of this project was to start the process toward an evaluation of the public health impact and the economic impact of falls associated to icy weather in Douglas County, NE for the ultimate purpose of designing and implementing injury prevention related public health protection measures. Additionally, the validated definition will be used by NE DHHS Occupational Health Surveillance Program to identify work related ice-related fall injuries that were covered by workers compensation. To achieve the goal, the first step was to identify a valid and reliable syndromic surveillance. Specifically, this project looked at the applicability of the ESSENCE syndromic surveillance definitions related to injuries associated with falls. Two syndromic surveillance definitions were compared, one that includes triage note and chief complaint search terms, and another that only includes chief complaint. The hypothesis was that the ESSENCE syndromic surveillance definition that includes triage note and chief complaint search terms, rather than the syndromic surveillance definition that only includes chief complaint, would be more effective at identifying ED visits resulting from fall-related injuries.MethodsThis project included 751 EDs visits from two hospitals located in Douglas County Nebraska, during ice events on December 16-18, 2016, January 10-12, 2017, and January 15-18, 2017.Two ESSENCE syndromic surveillance definitions, “Chief Complaint or Triage Note” and “Chief Complaint Only,” were used to identify fall-related ED visits from two participating EDs in Douglas County, NE. In the chief complaint and the triage note fields, the keywords selected were: fall, fell, or slip. In that the ESSENCE time series analysis indicated the increase in the number of falls were associated with ice events from baseline, an assumption was made that the increase was a result of the weather. Then, the Syndromic Surveillance Event Detection of Nebraska database was used to find the patient and visit identification numbers. These two identification numbers were used to identify the EHRs needed for a gold standard review. Chart data was used to evaluate the reliability and validity of the two syndromic surveillance definitions for the detection of falls on the study dates. This analysis was used to find the sensitivity, specificity and predictive value.ResultsThe sensitivity, specificity and positive predictive value for the “Chief Complaint Only” definition yielded 71.7%, 100%, and 100% respectively. The “Chief Complaint or Triage Note” definition results were 90.9%, 98.8%, and 95.5% for these analyses. Negative predictive value for both definitions was 97.5%.ConclusionsThe sensitivity indicates both definitions are unlikely to give false positives, and the positive predictive value indicates both definitions successfully identify most of the true positives found in the visits. However, the “Chief Complaint Only” definition resulted in a minimally higher specificity and positive predictive value. Therefore, the results indicate that although both definitions have similar specificity and positive predictive value, the “Chief Complaint or Triage Note” definition is more likely than the “Chief Complaint Only” definition to correctly identify ED visits related to falls in icy weather.References1. Beynon C, Wyke S, Jarman I, Robinson M, Mason J, Murphy K, Bellis MA, Perkins C. The cost of emergency hospital admissions for falls on snow and ice in England during winter 2009/10: a cross sectional analysis. Environmental Health 2011;10(60).

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 Enhanced syndromic surveillance during the 9 th Indian Ocean Island Games, 2015

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Pascal Vilain ◽  
Frédéric Pages ◽  
Guy Henrion ◽  
Xavier Combes ◽  
Marc Weber ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Reunion Island ◽  
Mass Gathering ◽  
Secondary Diagnosis ◽  
Syndromic Surveillance System ◽  
Ocean Island ◽  
Réunion Island ◽  
Ed Visits

ObjectiveTo describe how syndromic surveillance was enhanced to detecthealth events during the 9thIndian Ocean Island Games (IOIG) inReunion Island.IntroductionThe 9thIOIG took place in Reunion Island from July 31 to August9, 2015. This sport event gathered approximatively 1 640 athletes,2 000 volunteers and several thousand spectators from seven islands:Comoros, Madagascar, Maldives, Mauritius, Mayotte, Seychelles andReunion.In response to the import risk of infectious diseases from thesecountries where some of them are endemics, the syndromicsurveillance system, which captures 100% of all EmergencyDepartment visits, was enhanced in order to detect any health event.MethodsIn Reunion Island, syndromic surveillance system is based onOSCOUR® network (Organisation de la surveillance coordonnéedes urgences) that collects data from all emergency departments ofthe island. Data are daily transmitted to the French national publichealth agency then are available to the regional office. At the regionallevel, data are integrated into an application that allows the built ofpredefined syndromic groups according to the health risks related tomass gatherings (Table 1, parts 1 to 3) and complemented by specificsyndromic groups (table 1, part 4). Daily analyses with temporal[1] and spatial-temporal [2] algorithms were performed during thesurveillance period of July 27 to August 13, 2015. In addition to thismonitoring, ED physicians were requested to proactively tag Y33(ICD-10) as secondary diagnosis, each ED visits related to IOIG. Linelists were reviewed daily. Each day, an epidemiological report wassend to public health authorities.ResultsFrom July 31 to August 9, 2015, the activity of EDs was inaccordance with that expected. No health events were detected bythe syndromic surveillance system except for the syndrome “alcoholintoxication” for which consecutive signals were observed fromAugust 6 to 9, 2015. This increase occurs commonly at the beginningof each month (due to the social benefits payday) [3] nevertheless thisevent has probably been increased by IOIG (finals for team sportsand games closing ceremony). In total, 8 ED visits were tagged Y33as secondary diagnosis. In over half the cases, visits were related totrauma.ConclusionsThe syndromic surveillance system proved to be useful for thesurveillance of mass gathering events due to its capacity to detecthealth events but also to provide reassurance public health authorities[4]. As described in literature [5], few ED visits were tagged in relationto IOIG. Indeed, the tag of ED visits was implemented two weeksbefore the games, and given the shifts of ED physicians, some of themmay have not been informed. In the future, preparation meetings withphysicians will have to be planned several months before in order toimprove the response rate for mass gathering events.

scholarly journals Customizing ESSENCE Queries for Select Mental Health Sub-indicators

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Achintya N. Dey ◽  
Michael Coletta ◽  
Hong Zhou ◽  
Nelson Adekoya ◽  
Deborah Gould
Keyword(s):  
Public Health ◽  
Mental Health ◽  
Anxiety Disorders ◽  
Syndromic Surveillance ◽  
Depressive Disorders ◽  
National Level ◽  
Chief Complaint ◽  
Co Morbidity ◽  
Icd 10 ◽  
Ed Visits

ObjectiveEmergency department (ED) visits related to mental health (MH) disorders have increased since 2006 (1), indicating a potential burden on the healthcare delivery system. Surveillance systems has been developed to identify and understand these changing trends in how EDs are used and to characterize populations seeking care. Many state and local health departments are using syndromic surveillance to monitor MH-related ED visits in near real-time. This presentation describes how queries can be created and customized to identify select MH sub-indicators (for adults) by using chief complaint text terms and diagnoses codes. The MH sub-indicators examined are mood and depressive disorders, schizophrenic disorders, and anxiety disorders. Wider adoption of syndromic surveillance for characterizing MH disorders can support long-term planning for healthcare resources and service delivery.IntroductionSyndromic surveillance systems, although initially developed in response to bioterrorist threats, are increasingly being used at the local, state, and national level to support early identification of infectious disease and other emerging threats to public health. To facilitate detection, one of the goals of CDC’s National Syndromic Surveillance Program (NSSP) is to develop and share new sets of syndrome codes with the syndromic surveillance Community of Practice. Before analysts, epidemiologists, and other practitioners begin customizing queries to meet local needs, especially monitoring ED visits in near-real time during public health emergencies, they need to understand how syndromes are developed.More than 4,000 hospital routinely send data to NSSP’s BioSense Platform, representing about 55 percent of ED visits in the United States (2). The platform’s surveillance component, ESSENCE,* is a web-based application for analyzing and visualizing prediagnostic hospital ED data. ESSENCE’s Chief Complaint Query Validation (CCQV) data source, which is a national-level data source with access to chief complaint (CC) and discharge diagnoses (DD) from reporting sites, was designed for testing new queries.MethodsWe used ESSENCE CCQV to query weekly data for the nine week period from the first quarter of 2018 and looked at three common MH sub-indicators: mood and depressive disorders, schizophrenic disorders, and anxiety disorders. We developed four query types for each MH sub-indicator. Query-1 focused on DD codes; query-2 focused on CC text terms; query-3 focused on a combination of CC, DD, and no exclusion for mental health co-morbidity; and query-4 focused on a combination of CC and DD and excluded mental health co-morbidity. We also examined the summary distribution of CC texts to identify keywords related to MH sub-indicators.For mood and depressive disorders, we queried ICD-9 codes 296, 311; ICD-10 codes F30–F39; CC text terms for words “depressive disorder,” bipolar disorder,” “mood disorder,” “depression,” “manic episodes,” and “psychotic.” For schizophrenic disorders, we queried ICD-9 codes 295; ICD-10 codes F20–F29; CC text terms for words “psychosis,” “psychotic,” “schizo,” “delusional,” “paranoid,” “auditory,” “hallucinations,” and “hearing voices.” For anxiety disorders, we queried ICD-9 codes 300, 306, 307, 308, 309; ICD-10 codes F40–F48; CC text terms for words “anxiety,” “anexiy,” “aniety,” “aniexty,” “ansiety,” “anxety,” “anxity,” “anxiety,” “phobia,” and “panic attack.”ResultsWe identified 2.3 million average weekly ED visits for the 9-week period queried. Table 1 shows average weekly ED visits of select MH sub-indicators from the four query types. Because query 4 focused on specific MH outcomes and excluded MH co-morbidities, the average weekly ED visit for all three sub-indicators was almost half that of query 3, which focused on broader concepts by including MH co-morbidities. Among mood and depressive disorders, query 4 identified on average 23,352 ED visits per week versus 45,504 visits per week for query 3. Similarly, for schizophrenic disorders and anxiety disorders, query 4 identified on average 4,988 and 32,790 visits per week compared with 9,816 and 53,868 visits, respectively, for query 3. Further, more MH-related visits were identified using the DD-coded query (query 1) than CC-based text terms (query 2).ConclusionsAnalysts can benefit from having queries on select sub-indicators readily available and can use these to facilitate routine MH-related monitoring of ED visits, or customize the queries by including local text terms. Consistent with our previous work (3), this analysis demonstrated that MH-related ED visits are more likely to be found in DD codes than in CC alone.* Electronic Surveillance for the Early Notification of Community-based EpidemicsReferences[1] Weiss AJ, Barrett ML, Heslin KC , Stocks C. Trends in Emergency Department Visits Involving Mental and Substance Use Disorders, 2006–2013. HCUP Statistical Brief #216 [Internet]. Rockville (MD): Agency for Healthcare Research and Quality; 2016 Dec [cited 2018 Aug 14]. Available from: http://www.hcup-us.ahrq.gov/reports/statbriefs/sb216-Mental-Substance-Use-Disorder-ED-Visit-Trends.pdf.[2] Gould DW, Walker D, Yoon PW. The Evolution of BioSense: Lessons Learned and Future Directions. Public Health Reports. 2017 Jul/Aug;132(Suppl 1):S7–S11.[3] Dey AN, Gould D, Adekoya N, Hicks P, Ejigu GS, English R, Couse J, Zhou H. Use of Diagnosis Code in Mental Health Syndrome Definition. Online Journal of Public Health Informatics [Internet]. 2018 [cited 2018 Aug 14];10(1). Available from: https://doi.org/10.5210/ojphi.v10i1.8983

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