Syndrome

In 2017, FL Department of Health (DOH) became one of thirty-two states plus Washington, D.C funded by the Center for Disease Control and Prevention (CDC) under the ESOOS program. One of the objectives of this funding was to increase the timeliness of reporting on non-fatal opioid overdoses through syndromic surveillance utilizing either the emergency department (ED) or Emergency Medical Services (EMS) data systems. Syndromic case validation is an essential requirement under ESOOS for non-fatal opioid-involved overdose (OIOD). FL's ESOOS program conducted OIOD validation and quality monitoring of EMS case definitions, using data from FL's Emergency Medical Services Tracking and Reporting System (EMSTARS). We examined measurement validity with OIOD cases identified from FL's statewide hospital billing database, FL Agency for Health Care Administration (AHCA).

Objective: Assess the validity of Florida (FL) Enhanced State Opioid Overdose Surveillance (ESOOS) non-fatal syndromic case definitions.

In 2016, a half million people were treated in U.S. emergency departments (EDs) as a result of self-harm. 1 Not only is self-harm a major cause of morbidity in the U.S., but it is also one of the best predictors of suicide. Given that approximately 40% of suicide decedents visited an ED in the year prior to their death and that the majority of medically-serious self-harm patients are treated in EDs2, EDs serve as a critical setting in which to monitor rates and trends of suicidal behavior. To date, the majority of ED data for self-harm are generally two to three years old and thereby can only be used to describe historical patterns in suicidal behavior. Thus, in 2018, a syndrome definition for suicide attempts and suicidal ideation (SA/SI) was developed by the International Society for Disease Surveillance (ISDS) Syndrome Definition Committee in conjunction with Centers for Disease Control and Prevention (CDC) staff, allowing researchers to better monitor recent trends in medically treated suicidal behavior using data from the CDC's National Syndromic Surveillance Program (NSSP). These data serve as a valuable resource to help detect deviations from typical patterns of SA/SI and can help drive public health response if atypical activity, such as geospatial or temporal clusters of SA/SI, is observed. Such patterns may be indicative of suicide contagion (i.e., exposure to the suicide or suicidal behavior of a friend or loved one, or through media content, that may put individuals at increased risk of suicidal behavior). Research has demonstrated that suicide contagion is a real phenomenon. 3 13 Reasons Why is a Netflix series focused on social, school, and family-related challenges experienced by a high school sophomore; each episode in the 13-episode series describes a problem faced by the main character, which she indicates contributed to her decision to die by suicide. The series premiered March 31, 2017 and is rated TV-MA by TV Parental Guidelines4 (may be unsuitable for those under age 18 years due to graphic content). Nevertheless, the series has become popular among youth under 18 years of age. Of note, in the final episode, the main character'™s suicide by wrist laceration is graphically depicted. Following the premiere of the series, researchers and psychologists across the U.S. expressed concern that this graphic depiction of suicide could result in a contagion effect, potentially exacerbating suicidal thoughts and behavior among vulnerable youth viewers. To date, the only empirical data demonstrating the potential iatrogenic effects of this graphic portrayal of suicide comes from a study of Google Trends data demonstrating an increase in online suicide queries in the weeks following the show, with most of the queries focusing on suicidal ideation (e.g., how to commit suicide, how to kill yourself).5 However, there has been no study to examine changes in nonfatal self-harm trends following the series debut.

Objective: To describe national-level trends in nonfatal self-harm and suicidal ideation among 10-19 year old youth from January 2016 through December 2017 and examine the impact of popular entertainment on suicidal behavior.

The use of syndromic surveillance systems has evolved over the last decade, and increasingly includes both infectious and non- infectious topic areas. Public health agencies at the national, state, and local levels often need to rapidly develop new syndromic categories, or improve upon existing categories, to enhance their public health surveillance efforts. Documenting this development process can help support increased understanding and user acceptance of syndromic surveillance. This presentation will highlight the visualization process being used by CDC’s National Syndromic Surveillance Program (NSSP) program to develop and refine definitions for syndromes of interest to public health programs.

Objective: To describe the use of uni-grams, bi-grams, and tri-grams relationships in the development of syndromic categories.

In Massachusetts, syndromic surveillance (SyS) data have been used to monitor injection drug use and acute opioid overdoses within EDs. Currently, Massachusetts Department of Public Health (MDPH) SyS captures over 90% of ED visits statewide. These real-time data contain rich free-text and coded clinical and demographic information used to categorize visits for population level public health surveillance. Other surveillance data have shown elevated rates of opioid overdose related ED visits, Emergency Medical Service incidents, and fatalities in Massachusetts from 2014-20171,2,3. Injection of illicitly consumed opioids is associated with an increased risk of infectious diseases, including HIV infection. An investigation of an HIV outbreak among persons reporting IDU identified homelessness as a social determinant for increased risk for HIV infection.

Objective: We sought to measure the burden of emergency department (ED) visits associated with injection drug use (IDU), HIV infection, and homelessness; and the intersection of homelessness with IDU and HIV infection in Massachusetts via syndromic surveillance data.

State and local jurisdictions have been exploring the use of SyS data to monitor suspected drug overdose outbreaks in their communities. With the increasing awareness and use of SyS systems, staff from the Centers for Disease Control and Prevention (CDC) worked to develop several queries that jurisdictions could use to better capture suspected drug overdose visits. In 2017, CDC released their first two queries on heroin overdose and opioid overdose, followed in 2018 by stimulant and all drug overdose queries. Over time, and with the assistance from the SyS community and the CDC-funded Enhanced State Opioid Overdose Surveillance (ESOOS) state health departments, CDC has revised the queries to address suggestions from jurisdictions. However, it'™s not clear how often and in what way the syndrome definitions are updated over time. This is particularly true as new drugs emerge and the names of those drugs are integrated into syndrome definitions (e.g., recent Spice and œK2 synthetic cannabinoid outbreaks).

Objective: To discuss the process for developing and revising suspected drug overdose queries in syndromic surveillance (SyS) systems.

An expanded ambulatory health record, the Comprehensive Ambulatory Patient Encounter Record (CAPER) will provide multiple types of data for use in DoD ESSENCE. A new type of data not previously available is the Reason for Visit (ROV), a free-text field analogous to the Chief Complaint (CC). Intake personnel ask patients why they have come to the clinic and record their responses. Traditionally, the text should reflect the patient's actual statement. In reality the staff often "translates" the statement and adds jargon. Text parsing maps key words or phrases to specific syndromes. Challenges exist given the vagaries of the English language and local idiomatic usage. Still, CC analysis by text parsing has been successful in civilian settings [1]. However, it was necessary to modify the parsing to reflect the characteristics of CAPER data and of the covered population. For example, consider the Shock/Coma syndrome. Loss of consciousness is relatively common in military settings due to prolonged standing, exertion in hot weather with dehydration, etc., whereas the main concern is shock/coma due to infectious causes. To reduce false positive mappings the parser now excludes terms such as syncope, fainting, electric shock, road march, parade formation, immunization, blood draw, diabetes, hypoglycemic, etc.

Objective

Rather than rely on diagnostic codes as the core data source for alert detection, this project sought to develop a Chief Complaint (CC) text parser to use in the U.S. Department of Defense (DoD) version of the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE), thereby providing an alternate evidence source. A secondary objective was to compare the diagnostic and CC data sources for complementarity.

Particularly in resource-poor settings, syndromic surveillance has been proposed as a feasible solution to the challenges in meeting the new disease surveillance requirements included in the World Health Organization's International Health Regulations (2005).

Objective

The aim of this study is to demonstrate how syndromic surveillance systems are working in low-resource settings while identifying the key best practices and considerations.