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ISDS, in collaboration with and with the support of CDC, recently released a new version of the PHIN Messaging Guide for Syndromic Surveillance. This Guide expands on previous versions and includes specifications for transmitting hospital inpatient electronic health record (EHR) information for syndromic surveillance. The webinar will focus on leading participants through the new Guide, explaining the various sections and changes, and showing public health practitioners and vendors how the Guide may be useful in practice. 

Presenter

Description

Investigation of cases, clusters, and outbreaks of infectious disease is a complex process requiring substantial support from protocols, distributed and cooperative work, and information systems. We set out to identify public health information needs, the types of data required to meet these needs, and the potential alignment with visualizations of this data.

Objective

The goal of this work is to identify specific work practices in disease investigation that would be supported by data visualization, such as identifying exposure, contact, and spatiotemporal clustering.

Submitted by teresa.hamby@d… on
Description

Population health relies on tracking patients through a continuum of care with data from disparate sources. An assumption is made that all records of a patient from all the sources are connected. As was realized during the process of operationalizing algorithms for population health, not all patient records are connected. Disconnected records negatively impact results: from individual patient care management through population health’s predictive analytics. An enterprise master patient index (EMPI) system can be employed to connect a patient’s records across disparate systems, but it requires comprehensive tuning to maximize the number of connected records. This presentation describes how one large healthcare integrated delivery network tuned their EMPI system to maximize the number of connected patient records across all sources.

Submitted by teresa.hamby@d… on
Description

Each year several thousands contract the seasonal flu, and it is estimated that these viruses are responsible for the deaths of over six thousand individuals [1]. Further, when a new strain is detected (e.g. 2009), the result can be substantially more dramatic [2]. Because of the potential threats flu viruses pose, the United States, like many developed countries, has a very well established flu surveillance system consisting of 10 components collecting laboratory data, mortality data, hospitalization data and sentinel outpatient care data [3]. Currently, this surveillance system is estimated to lag behind the actual seasonal outbreak by one to two weeks. As new data streams come online, it is important to understand what added benefit they bring to the flu surveillance system complex. For data streams to be effective, they should provide data in a more timely fashion or provide additional data that current surveillance systems cannot provide. Two types of multiplexed diagnostic tools designed to test syndromically relevant pathogens and wirelessly upload data for rapid integration and interpretation were evaluated to see how they fit into the influenza surveillance scheme in California.

Objective

Evaluate utility of point of need diagnostic tests in relationship to current standard influenza detection methods.

Submitted by Magou on
Description

Speed, reliability, and uniformity of data collection enable syndromic surveillance (SyS) systems to provide public health authorities (PHAs) with timely information about community health threats and trends. Increasingly, healthcare information technology (HIT) is being used to accelerate and automate data collection for more real-time surveillance, reducing irregularity in how SyS data are packaged and sent by healthcare providers. Continuing to focus on patient and population health outcomes, the on-going US federal program that certifies HIT to promote interoperability has mandated broader use of an updated standard for communication of SyS data. Under the Edition 2015 federal rule tied to Medicare and Medicaid reimbursement, hospitals, in addition to emergency departments and urgent care centers, are now required to provide SyS data to PHAs using HL7 2.5.1 messages that are in conformance with Release 2.0 of the CDC’s Public Health Information Network (PHIN) guide for SyS. To facilitate the intended application of this updated standard, a new version of conformance testing tools is being published, which will enable HIT developers to increase their probability of meeting the requirements outlined in the standard and lead to enhanced product interoperability and reliability.

Objective

Describe how the 2015 Edition of the National Institute of Standards and Technology’s (NIST) Syndromic Surveillance Messaging Validation Suite continues to support federal efforts to increase healthcare information technology interoperability for timelier public health surveillance in the US; and show how this tool is used to validate messages.

Submitted by aising on
Description

Public health in Ontario, Canada has no standardized system for carrying out syndromic surveillance. Previous research had demonstrated wide variation in the implementation of syndromic surveillance.

Objective:

To describe results of a prospective study to assess the impact of using a standard process by which public health units (PHUs) investigate syndromic surveillance alerts for respiratory illness.

Submitted by rmathes on
Description

The CMS EHR Incentive Programs include a measure for meaningful use of EHR systems for submitting syndromic surveillance messages to public health. The Stage 2 measure defines the standard for transmission to be HL7 v2.5.1 Admit/Discharge/Transfer messages according to the PHIN Messaging Guide for Syndromic Surveillance and Conformance Clarification for EHR Certification of Electronic Syndromic Surveillance, Addendum to PHIN Messaging Guide for Syndrome Surveillance. The National Institute of Standards and Technology (NIST) provides an online testing tool for validating messages. While some jurisdictions use the Biosense platform for receiving, managing, and analyzing syndromic surveillance data, there is no consistent tool that is available to jurisdictions to assess the quality and conformance of data submissions both at the time of on-boarding a new reporting facility and on an ongoing basis during production operations.

The New York City Citywide Immunization Registry (CIR), the immunization information system for NYC that has been operational since 1997, has as part of its software suite an Open Source, webbased data quality assurance (QA) tool used by its research scientists to qualify new sites for reporting data electronically via HL7 v2 messages, and for monitoring the ongoing quality of data submissions over time. A validation process evaluates incoming messages against the rules established by an implementation guide (IG) and stores the result of the evaluation in a CIR database table that is accessible by the QA Tool which displays the data to an administrative user. This project served as a proof-of-concept for implementing a similar process for syndromic surveillance.

Objective

To leverage an existing open source quality assurance software tool created for the immunization domain and modify it to serve as a quality assurance tool for syndromic surveillance messages.

Submitted by teresa.hamby@d… on
Description

Details about the ONC 2015 Edition certification criteria for Syndromic Surveillance and the related NIST Test Suite were explained previously. We now provide an overview and key information regarding updates to the Test Suite and how it is designed to be used.

Objective

The NIST Syndromic Surveillance Test Suite for 2015 Edition ONC certification testing was published in February 2016. Key information related to the purpose, development, and use of this conformance test tool is provided via snapshots on a poster.

Submitted by teresa.hamby@d… on
Description

Most countries do not report national notifiable disease data in a machine-readable format. Data are often in the form of a file that contains text, tables and graphs summarizing weekly or monthly disease counts. This presents a problem when information is needed for more data intensive approaches to epidemiology, biosurveillance and public health as exemplified by the Biosurveillance Ecosystem (BSVE). While most nations do likely store their data in a machine-readable format, the governments are often hesitant to share data openly for a variety of reasons that include technical, political, economic, and motivational issues. For example, an attempt by LANL to obtain a weekly version of openly available monthly data, reported by the Australian government, resulted in an onerous bureaucratic reply. The obstacles to obtaining data included: paperwork to request data from each of the Australian states and territories, a long delay to obtain data (up to 3 months) and extensive limitations on the data’s use that prohibit collaboration and sharing. This type of experience when attempting to contact public health departments or ministries of health for data is not uncommon. A survey conducted by LANL of notifiable disease data reporting in 52 countries identified only 10 as being machine-readable and 42 being reported in pdf files on a regular basis. Within the 42 nations that report in pdf files, 32 report in a structured, tabular format and 10 in a non-structured way. As a result, LANL has developed a tool-Epi Archive (formerly known as EPIC)-to automatically and continuously collect global notifiable disease data and make it readily accesible.

Objective

LANL has built a software program that automatically collects global notifiable disease data—particularly data stored in files—and makes it available and shareable within the Biosurveillance Ecosystem (BSVE) as a new data source. This will improve the prediction and early warning of disease events and other applications.

Submitted by teresa.hamby@d… on
Description

The NBS is an integrated disease surveillance system deployed in 22 public health jurisdictions to support receipt, investigation, analysis and reporting, and data exchange for state reportable conditions. The NBS is governed by the Centers for Disease Control and Prevention (CDC) and state, local, and territorial users that make up the NBS Community. In the early 2000’s, electronic laboratory results reporting (ELR) was implemented in an effort to improve timeliness and completeness of disease reporting. As standards-based electronic health records (EHRs) are adopted and more surveillance data become available, modern surveillance systems must consume information in an automated way and provide more functionality to automate key surveillance processes. 

Objective

The NEDSS Base System (NBS), an integrated disease surveillance system, implemented extensible functionality to support electronic data exchange for multiple use cases and public health workflow management of incoming messages and documents. 

Submitted by Magou on