Syndrome Definition

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.

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.

Mining text for real-time syndromic surveillance usually requires a comprehensive knowledge base (KB) which contains detailed information about concepts relevant to the domain, such as disease names, symptoms, drugs, and radiology findings. Two such resources are the Biocaster Ontology [1] and the Extended Syndromic Surveillance Ontology (ESSO) [2]. However, both these resources are difficult to manipulate, customize, reuse and extend without knowledge of ontology development environments (like Protege) and Semantic Web standards (like RDF and OWL). The cKASS software tool provides an easy-to-use, adaptable environment for extending and modifying existing syndrome definitions via a web-based Graphical User Interface, which does not require knowledge of complex, ontology-editing environments or semantic web standards. Further, cKASS allows for - indeed encourages - the sharing of user-defined syndrome definitions, with collaborative features that will enhance the ability of the surveillance community to quickly generate new definitions in response to emerging threats.

Objective

We describe cKASS (clinical Knowledge Authoring & Sharing Service), a system designed to facilitate the authoring and sharing of knowledge resources that can be applied to syndromic surveillance.

Domains go through phases of existence, and the electronic disease surveillance domain is no different. This domain has gone from an experimental phase, where initial prototyping and research tried to define what was possible, to a utility phase where the focus was on determining what tools and data were solving problems for users, to an integration phase where disparate systems that solve individual problems are tied together to solve larger, more complex problems or solve existing problems more efficiently. With the integration phase comes the desire to standardize on many aspects of the problem across these tools, data sets, and organizations. This desire to standardize is based on the assumption that if all parties are using similar language or technology then it will be easier for users and developers to move them from one place to another.

Normally the challenge to the domain is deciding on a vocabulary or technology that allows seamless transitions between all involved. The disease surveillance domain has accomplished this by trying to use some existing standards, such as HL7, and trying to develop some of their own, such as chief complaint-based syndrome definitions. However, the standards that are commonly discussed in this domain are easily misunderstood. These misunderstandings are predominantly a communication and/or educational issue, but they do cause problems in the disease surveillance domain. With the increased use of these standards due to meaningful use initiatives, these problems will continue to grow and be repeated without improved understanding and better communication about standards.

Objective

This talk will point out the inconsistencies and misunderstandings of the word "standard". Specifically, it will discuss HL7, syndrome definitions, analytical algorithms, and disease surveillance systems.

The Extended Syndromic Surveillance Ontology (ESSO) is an open source terminological ontology designed to facilitate the text mining of clinical reports in English [1,2]. At the core of ESSO are 279 clinical concepts (for example, fever, confusion, headache, hallucination, fatigue) grouped into eight syndrome categories (rash, hemorrhagic, botulism, neurological, constitutional, influenza-like-illness, respiratory, and gastrointestinal). In addition to syndrome groupings, each concept is linked to synonyms, variant spellings and UMLS Concept Unique Identifiers. ESSO builds on the Syndromic Surveillance Ontology [3], a resource developed by a working group of eighteen researchers representing ten syndromic surveillance systems in North America. ESSO encodes almost three times as many clinical concepts as the Syndromic Surveillance Ontology, and incorporates eight syndrome categories, in contrast to the Syndromic Surveillance Ontology's four (influenza-like-illness, constitutional, respiratory and gastrointestinal). The new clinical concepts and syndrome groupings in ESSO were developed by a board-certified infectious disease physician (author JD) in conjunction with an informaticist (author MC).

Objective

In order to evaluate and audit these new syndrome definitions, we initiated a survey of syndromic surveillance practitioners. We present the results of an online survey designed to evaluate syndrome definitions encoded in the Extended Syndromic Surveillance Ontology.

Syndromic surveillance systems were designed for early outbreak and bioterrorism event detection. As practical experience shaped development and implementation, these systems became more broadly used for general surveillance and situational awareness, notably influenza-like illness (ILI) monitoring. Beginning in 2006, ISDS engaged partners from state and local health departments to build Distribute, a distributed surveillance network for sharing de-identified aggregate emergency department syndromic surveillance data through existing state and local public health systems. To provide more meaningful cross-jurisdictional comparisons and to allow valid aggregation of syndromic data at the national level, a pilot study was conducted to assess implementation of a common ILI syndrome definition across Distribute.

Objective

Assess the feasibility and utility of adopting a common ILI syndrome across participating jurisdictions in the ISDS Distribute project.