To develop an automated system which examines Poison Control Center data and provides (1) early recognition of events, both man-made and naturally-occurring, which may pose a threat to public health, and (2) real-time notification to Poison Specialists, the on-site experts who evaluate those alerts.
This is a cluster of syndromes created to populate an extreme weather myESSENCE tab. The intent was to increase repeatability of our weather surveillance and have something where a user can use the "Change Region" option to select whatever county, or counties, experienced storm activity. This is still a major work-in progress.
All of this as done in NSSP ESSENCE on Emergency Room data. Fields are specified by each syndrome definition.
Florida has implemented various surveillance methods to augment existing sources of surveillance data and enhance decision making with timely evidence based assessments to guide response efforts post-hurricanes. Historically, data collected from deployed federal assets have been an integral part of this effort. However, a number of factors have made this type of surveillance challenging: logistical is- sues of field work in a post-disaster environment, the resource inten- sive manual data collection process from DMAT sites, and delayed analysis and interpretation of these data to inform decision makers. The ESSENCE-FL system is an automated and secure web-based ap- plication accessed by FDOH epidemiologists and staff at participat- ing hospitals.
Objective
The Florida Department of Health (FDOH), Bureau of Epidemi- ology, partnered with the U.S. Department of Health and Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response (ASPR) to improve surveillance methods in post dis- aster or response events. A new process was implemented for con- ducting surveillance to monitor injury and illness for those presenting for care to ASPR assets such as Disaster Medical Assistance Team (DMAT) sites when they are operational in the state. The purpose of the current work was to field test and document the operational ex- perience of the newly implemented ASPR data module in ESSENCE- FL (syndromic surveillance system) to receive near real-time automated data feeds when ASPR federal assets were deployed in Florida during the 2012 Republican National Convention (RNC).
Automated Electronic Disease Surveillance has become a common tool for most public health practitioners. Users of these systems can analyze and visualize data coming from hospitals, schools, and a variety of sources to determine the health of their communities. The insights that users gain from these systems would be valuable information for emergency managers, law enforcement, and other nonpublic health officials. Disseminating this information, however, can be difficult due to lack of secure tools and guidance policies. This abstract describes the development of tools necessary to support information sharing between public health and partner organizations.
Objective
The objective of this project is to provide a technical mechanism for information to be easily and securely shared between public health ESSENCE users and non-public health partners; specifically, emergency management, law enforcement, and the first responder community. This capability allows public health officials to analyze incoming data and create interpreted information to be shared with others. These interpretations are stored securely and can be viewed by approved users and captured by authorized software systems. This project provides tools that can enhance emergency management situational awareness of public health events. It also allows external partners a mechanism for providing feedback to support public health investigations.
The National Collaborative for Bio-Preparedness (NCB-Prepared) was established in 2010 to create a biosurveillance resource to enhance situational awareness and emergency preparedness. This jointinstitutional effort has drawn on expertise from the University of North Carolina- Chapel Hill, North Carolina State University, and SAS Institute, leveraging North Carolina’s role as a leader in syndromic surveillance, technology development and health data standards. As an unprecedented public/private alliance, they bring the flexibility of the private sector to support the public sector. The project has developed a functioning prototype system for multiple states that will be scaled and made more robust for national adoption.
Objective:
Demonstrate the functionality of the National Collaborative for Bio-Preparedness system.
Accurately gauging the health status of a population during an event of public health significance (e.g. hurricanes, H1N1 2009 pandemic) in support of emergency response and situation awareness efforts can be a challenge for established public health surveillance systems in terms of geographic and population coverage as well as the appropriateness of health indicators. The demand for timely, accurate, and event-specific data can require the rapid development of new data assets to “fill-in” existing information gaps to better characterize the scope, scale, magnitude, and population health impact of a given event within a very narrow time-window. Such new data assets may be concurrently under development and evaluation while being used to support response efforts. Recent examples include the “drop-in” surveillance processes deployed at evacuation centers following Hurricane Katrina1 and the illness and injury surveillance systems established for response workers during the Deepwater Horizon Oil spill response. During the 2009 H1N1 pandemic response, CDC acquired access to data from several national-level health information systems that previously had been un-vetted as public health information sources. These sources provided data extracts from massive administrative or electronic medical records (EMR) based in hospital and primary care settings. It was hoped that such data could supplement existing influenza surveillance systems and aid in the characterization of the pandemic. Few of these new data sources had formal documentation or concise information on the underlying populations and geographies represented.
Objective
To describe data management and analytic processes undertaken to rapidly acquire and use previously unavailable data during a public health emergency response.
Surveillance of influenza in the US, UK and other countries is based primarily on measures of influenza-like illness (ILI), through a combination of syndromic surveillance systems, however, this method may not capture the full spectrum of illness or the total burden of disease. Care seeking behaviour may change due to public beliefs, for example more people in the UK sought care for pH1N1 in the summer of 2009 than the winters of 2009/2010 and 2010/2011, resulting in potential inaccurate estimates from ILI. There may also be underreporting of or delays in reporting ILI in the community, for example in the UK those with mild illness are less likely to see a GP, and visits generally occur two or more days after onset of symptoms. Work absences, if the reason is known, could fill these gaps in detection.
Objective
To address the feasibility and efficiency of a novel syndromic surveillance method, monitoring influenza-like absence (ILA) among hospital staff, to improve national ILI surveillance and inform local hospital preparedness.
During the 2017 Houston floods Lauren Leining worked with the the American Red Cross to visit each disaster victim in a shelter to do bed evaluations, but learned it was a very common thing for people to refuse treatment for a variety of reasons. Many people didn’t want to walk to where the assessments were going on because it was often on one end of a giant convention center. Sometimes they just didn’t feel well enough – for example, they were in pain or their ankle hurt.
The attached query was developed to track medication refill encounters in emergency departments in ESSENCE during evacuations or extended mass gathering events. The query was initially developed for use with the chief complaint, triage note, and discharge diagnosis code (ICD-10 CM).
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.