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Tyson James

The U.S. Department of Homeland Security National Incident Management System (NIMS) establishes a common framework and common terminology that allows diverse incident management and support organizations to work together across a wide variety of functions and hazard scenarios1. Using common terminology helps avoid confusion and enhances interoperability, particularly in fast-moving public health (PH) emergency responses. In addition, common terminology allows diverse incident management and support organizations to work together across a wide variety of functions and scenarios1. LOINC is one of a suite of designated standards for the electronic exchange of public health and clinical information. Implementation of LOINC facilitates improvement of semantic interoperability, including unified terminology2. More than 68,100 registered users from 172 countries use LOINC to move interoperable data seamlessly between systems3. The CDC Division of Emergency Operations (DEO) leads development of standardized PH emergency preparedness and response terminology to improve effective and interoperable communications between national and international partners. Realizing the scale of LOINC support and implementation across the global public health arena, CDC DEO collaborates with LOINC to further enhance and harmonize the current PH emergency response terminology and to attain critical PH emergency management and preparedness and response requirements.

Objective: The purpose of this project is to demonstrate the progress in development of a standardized public health (PH) emergency preparedness and response data ontology (terminology) through collaboration between the Centers for Disease Control and Prevention (CDC), Division of Emergency Operations (DEO), and the Logical Observation Identifiers Names and Codes (LOINC) system.

Submitted by elamb on

Effective prevention, detection, and rapid response to PH emergencies rely on sufficient and timely delivered information. PH EOC data flows are based on critical information requirements, addressing needs of EOC staff for timely delivered analytical products that provide situational awareness, event-specific data, event investigation tools, resource management etc1. The ability of PH EOC systems to automatically and accurately interpret meaning of the exchanged data depends on a level of semantic data interoperability and utilization of a common information exchange reference model (CIERF) that conforms to established data standards. PH EOC data interoperability requires mutual development and close collaboration with partners to develop a PH EPR CIERF, common terminology and standardized vocabulary.

Objective:

The purpose of this project is to demonstrate progress in developing functional data models and semantic definitions (content standards) for data elements and value sets comprising information categories supporting PH Emergency Preparedness and Response. (EPR) The objective is to explain the concepts and methods used to define core PH Emergency Management and Preparedness and Response functions, Information Exchange Requirements (IERs), data elements, and value sets to create a PH Emergency Operations Center (EOC) Minimum Data Set Specification. The primary focus of this presentation is to describe the value of semantic data interoperability and provide operational examples of the value and return-on-investment gained through building semantically interoperable data exchange through content standardization.

Submitted by elamb on

Social media messages are often short, informal, and ungrammatical. They frequently involve text, images, audio, or video, which makes the identification of useful information difficult. This complexity reduces the efficacy of standard information extraction techniques1. However, recent advances in NLP, especially methods tailored to social media2, have shown promise in improving real-time PH surveillance and emergency response3. Surveillance data derived from semantic analysis combined with traditional surveillance processes has potential to improve event detection and characterization. The CDC Office of Public Health Preparedness and Response (OPHPR), Division of Emergency Operations (DEO) and the Georgia Tech Research Institute have collaborated on the advancement of PH SA through development of new approaches in using semantic analysis for social media.

Objective

The objective of this analysis is to leverage recent advances in natural language processing (NLP) to develop new methods and system capabilities for processing social media (Twitter messages) for situational awareness (SA), syndromic surveillance (SS), and event-based surveillance (EBS). Specifically, we evaluated the use of human-in-the-loop semantic analysis to assist public health (PH) SA stakeholders in SS and EBS using massive amounts of publicly available social media data.

Submitted by Magou on

The purpose of this project is to demonstrate progress in developing a scientific and practical approach for public health (PH) emergency preparedness and response informatics (EPRI) that supports the National Health Security Strategy and Global Health Security Agenda (GHSA) objectives. PH emergency operations centers (EOC) contribute to health security objectives because they operationalize response, recovery and mitigation activities during national and international PH events. The primary focus of this presentation is to describe the results of an analysis of CDC’s EOC, and other EOCs, in building their EPRI capabilities. 

Submitted by uysz on
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