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Hicks Peter

Description

In 2011, the Centers for Disease Control and Prevention (CDC) released the PHIN Messaging Guide for Syndromic Surveillance v. 1. In the intervening years, new technological advancements including Electronic Health Record capabilities, as well as new epidemiological and Meaningful Use requirements have led to the periodic updating and revision of the Message Guide. These updates occurred through informal and semi-structured solicitation and in response to comments from across public health, governmental, academic, and EHR vendor stakeholders. Following the Message Guide v.2.0 release in 2015, CDC initiated a multi-year endeavor to update the Message Guide in a more systematic manner and released further updates via an Erratum and a technical document developed with the National Institute of Standards and Technology (NIST) to clarify validation policies and certification parameters. This trio of documents were consolidated into the Message Guide v.2.1 release and used to inform the development of the NIST Syndromic Surveillance Test Suite (http://hl7v2-ss-r2-testing.nist.gov/ss-r2/#/home), validate test cases, and develop a new rules-based IG built using NIST's Implementation Guide Authoring and Management Tool (IGAMT). As part of a Cooperative Agreement (CoAg) initiated in 2017, CDC partnered with ISDS to build upon prior activities and renew efforts in engaging the Syndromic Surveillance Community of Practice for comment on the Message Guide. The goal of this CoAg is have the final product become an HL7 Standard for Trial Use following the second phase of formal HL7 balloting in Fall 2018.

Objective: To describe the latest revisions and modifications to the œHL7 2.5.1 Implementation Guide for Syndromic Surveillance (formerly the PHIN Message Guide for Syndromic Surveillance) that were made based on community commentary and resolution of feedback from the HL7 balloting process. In addition, the next steps and future activities as the IG becomes an HL7 Standard for Trial Use will be highlighted.

Submitted by elamb on
Description

In May of 2001, Boston released a strategic transportation plan to improve bicycle access and safety. [1] According to the Boston Transportation Department, ridership has increased 122% between 2007 and 2009. [2] A collaborative public health and public safety task force was initiated in 2010 to foster a safe and healthy bicycling environment.

Objective

To quantify the injury burden and identify possible risk factors using bicycle related injury (BRI) visits at Boston emergency departments (ED).

Submitted by elamb on
Description

Time-of-arrival (TOA) surveillance methodology consists of identifying clusters of patients arriving to a hospital emergency department (ED) with similar complaints within a short temporal interval. TOA monitoring of ED visit data is currently conducted by the Florida Department of Health at the county level for multiple subsyndromes [1]. In 2011, North Carolina's NC DETECT system and CDC's Biosense Program collaborated to enhance and adapt this capability for 10 hospital-based Public Health Epidemiologists (PHEs), an ED-based monitoring group established in 2003, for North Carolina's largest hospital systems. At the present time, PHE hospital systems include coverage for approximately 44% of the statewide general/acute care hospital beds and 32% of all emergency department visits statewide. We present findings from TOA monitoring in one hospital system.

Objective

To describe collaborations between North Carolina Division of Public Health and the Centers for Disease Control and Prevention (CDC) implementing time-of-arrival (TOA) surveillance to monitor for exposure-related visits to emergency departments (ED) in small groups of North Carolina hospitals.

Submitted by elamb on
Description

The CDC's BioSense Program receives near real-time health care utilization data from a number of sources, including Department of Defense (DoD) healthcare facilities from around the globe and non-federal hospital emergency departments (EDs) in the US, to support all-hazards surveillance and situation awareness. Following the tsunami in Japan on March 11, 2011, the BioSense Program modified its surveillance protocols to monitor: 1) injuries and possible radiation-associated health effects in Japan-based DoD facilities and 2) potential adverse health effects associated with the consumption of potassium iodide (KI), a salt used to prevent injury to the thyroid gland in the event of radiation exposure, among persons attending participating EDs in the US. We present the findings from that enhanced surveillance.

Objective

To demonstrate the utility of the BioSense Program for post-disaster response surveillance.

Submitted by elamb on
Description

BioSense is a national program designed to improve the nation’s capabilities for conducting disease detection, monitoring, and real-time situational awareness. Currently, BioSense receives near real-time data from non-federal hospitals, as well as national daily batched data from the Departments of Defense and Veteran’s Affairs facilities.  These data are analyzed, visualized, and made simultaneously available to public health at local, state, and federal levels through the BioSense application.

Objective:

In this paper we present summary information on the non-federal hospitals currently sending data to the BioSense system and describe this distribution by hospital type, method of data delivery as well as patient class and patient health indicator.

Submitted by elamb on
Description

Concern over oral health-related ED visits stems from the increasing number of unemployed and uninsured, the cost burden of these visits, and the unavailability of indicated dental care in EDs [1]. Of particular interest to NC state public health planners are Medicaid-covered visits. Syndromic data in biosurveillance systems offer a means to quantify these visits overall and by county and age group.

Objective

The objective was to use syndromic surveillance data from the North Carolina Disease Event Tracking and Epidemiologic Collection Tool NCDETECT and from BioSense to quantify the burden on North Carolina (NC) emergency departments of oral health-related visits more appropriate for care in a dental office (ED). Calculations were sought in terms of the Medicaid-covered visit rate relative to the Medicaid-eligible population by age group and by county.

Submitted by uysz on
Description

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.

Submitted by hparton on
Description

Syndromic surveillance seeks to systematically leverage health-related data in near "real-time" to understand the health of communities at the local, state, and federal level. The product of this process provides statistical insight on disease trends and healthcare utilization behaviors at the community level which can be used to support essential surveillance functions in governmental public health authorities (PHAs). Syndromic surveillance is particularly useful in supporting public health situational awareness, emergency response management, and outbreak recognition and characterization. Patient encounter data from healthcare settings are a critical inputs for syndromic surveillance; such clinical data provided by hospitals and urgent care centers to PHAs are authorized applicable local and state laws. The capture, transformation, and messaging of these data in a standardized and systematic manner is critical to this entire enterprise. In August 2015, a collaborative effort was initiated between the CDC, ISDS, the Syndromic Surveillance Community, ONC and NIST to update the national electronic messaging standard which enables disparate healthcare systems to capture, structure, and transmit administrative and clinical data for public health surveillance and response. The PHIN Messaging Guide for Syndromic Surveillance -Release 2.0 (2015) provided an HL7 messaging and content reference standard for national, syndromic surveillance electronic health record technology certification as well as a basis for local and state syndromic surveillance messaging implementation guides. This standard was further amended with the release of the PHIN Messaging Guide for Syndromic Surveillance - Release 2.0, Erratum (2015) and the HL7 Version 2.5.1 PHIN Messaging Guide for Syndromic Surveillance- Release 2.0, NIST Clarifications and Validation Guidelines, Version 1.5 (2016). ISDS is now engaged in a process, supported by a CDC Cooperative Agreement, to formally revise the existing guide and generate an HL7 V 2.5.1 Implementation Guide (IG) for Syndromic Surveillance v2.5 for HL7 balloting in 2018. This roundtable will provide a forum to present and discuss the HL7 Balloting process and the outstanding activities in which the Syndromic Surveillance community must participate during the coming months for this activity to be successful.

Objective:

To provide a forum to engage key stakeholders to discuss the process for updating and revising the Implementation Guide (IG) for Syndromic Surveillance (formerly the PHIN Message Guide for Syndromic Surveillance) and underscore the critically of community and stakeholder involvement as the Implementation Guide is vetted through the formal Health Level Seven (Hl7) balloting process in 2018.

Submitted by elamb on
Description

In 2011, the CDC released the PHIN Implementation Guide (IG) for Syndromic Surveillance v.1 under the Public Health Information Network. In the intervening years, new technological advancements, EHR capabilities as well as epidemiological and Meaningful Use requirements have led to the periodic update and revision of the IG through informal and semi-structured solicitation and collection of comments from across public health, governmental, academic, and EHR vendor stakeholders. Following the IG v.2.0 release in 2015, CDC initiated a multi-year endeavor to update the IG in a more systematic manner and released further updates via an Erratum and a technical document developed with NIST to clarify validation policies and testing parameters. These documents were consolidated into the Message Guide v.2.1 release and used to inform the development of the NIST Syndromic Surveillance Test Suite (http://hl7v2-ss-r2-testing.nist.gov/ss-r2/#/home), Validation Test Cases, and develop a new rules-based IG built using NIST’s Implementation Guide Authoring and Management Tool (IGAMT). As part of a Cooperative Agreement initiated in 2017, CDC and ISDS built upon prior activities and renew efforts in engaging the Syndromic Surveillance Community of Practice for comment on the IG with the goal of having the final product to become an "HL7 V 2.5.1 Implementation Guide for Syndromic Surveillance Standard for Trial Use" following a formal HL7 balloting process in 2018.

Objective:

To describe the process to update the Implementation Guide (IG) for Syndromic Surveillance via community and stakeholder engagement and highlight significant modifications as the IG is vetted through the formal HL7 balloting process.

Submitted by elamb on