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Terminology

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.

Referenced File
Submitted by elamb on

As part of the US Department of Defense strategy to counter biological threats, the Defense Threat Reduction Agency’s Cooperative Biological Engagement Program is enhancing the capabilities of countries in the former Soviet Union (FSU) to detect, diagnose, and report endemic and epidemic, man-made or natural cases of especially dangerous pathogens. During these engagements, it was noted that Western-trained and Soviet-trained epidemiologists have difficulty, beyond that of simple translation, in exchanging ideas.

The Soviet public health system and epidemiology developed independently of that of other nations. Whereas epidemiology in the West is thought of in terms of disease determinants in populations and relies on statistics to make inferences, classical Soviet epidemiology is founded on a more ecological view with the main focus on infectious diseases’ spread theory. Consequently many fundamental Soviet terms and concepts lack simple correlates in English and other languages outside the Soviet sphere; the same is true when attempting to translate from English to Russian and other languages of the FSU. Systematic review of the differences in FSU and Western epidemiologic concepts and terminology is therefore needed for strengthening understanding and collaboration in disease surveillance, pandemic preparedness, response to biological terrorism, etc.

 

Objective

The purpose of this project was to develop an English-Russian Epidemiology Dictionary, which is needed for improved international collaboration in public health surveillance.

Submitted by hparton on

In 2013, the Utah Department of Health (UDOH) began working with hospital and reference laboratories to implement electronic laboratory reporting (ELR) of reportable communicable disease data. Laboratories utilize HL7 message structure and standard terminologies such as LOINC and SNOMED to send data to UDOH. These messages must be evaluated for validity, translated, and entered into Utah’s communicable disease surveillance system (UT-NEDSS), where they can be accessed by local and state investigators and epidemiologists. Despite the development and use of standardized terminologies, reporters may use different, outdated versions of these terminologies, may not use the appropriate codes, or may send local, home-grown terminologies. These variations cause problems when trying to interpret test results and automate data processing. UDOH has developed a two-step translation process that allows us to first standardize and clean incoming messages, and then translate them for consumption by UT-NEDSS. These processes allow us to efficiently manage several different terminologies and helps to standardize incoming data, maintain data quality, and streamline the data entry process.

Objective:

The objective of this abstract is to illustrate how the Utah Department of Health processes a high volume of electronic data. We do this by translating what reporters send within an HL7 message into "epidemiologist" language for consumption into our disease surveillance system.

Submitted by elamb on
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