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Interoperability

Description

For more than a decade, biosurveillance systems (and more recently BioSense) have been employed in the United States. Efforts to drastically expand these surveillance capacities have been a national priority given concerns about national security. However, there has been little emphasis on value or increasing value to communities or agencies contributing and analyzing data. This qualitative analysis focused on all biosurveillance stakeholders and the opportunity to enhance interoperability and reuse of data and systems.

 

Objective

To understand the perspective of biosurveillance stakeholders and how their participation creates value for them as well as public health departments.

Submitted by elamb on
Description

In November 2002 a NATO summit meeting issued an initiative calling for member states to begin development of an interoperable disease surveillance system that had the ability to give early warning in the event of an attack on armed forces using weapons of mass destruction. In response, the French military have developed the “Projet de Surveillance Spatiale des épidémies au Sein des Forces Armées en Guyane” (2SE FAG), a prototype real-time syndromic surveillance system based on fever case reporting which has been in operation among armed forces personnel in French Guiana since October 2004. Between January and June 2006, French Guiana experienced the largest epidemic of dengue fever in its history. During that year, 2255 confirmed cases and many thousands more suspected cases were recorded among the civilian population. 2SE FAG issued an alert based on a rise in fever cases among armed forces personnel in week 2 of 2006, 5 weeks before a rise was noticed among the civilian population. Limited evaluations of the system have taken place in the past; this study represents a final evaluation of the system before its possible expansion.

 

Objective

The objective of this study was the evaluation of the syndromic surveillance system 2SE FAG which operates among armed forces personnel in French Guiana using the “Framework for Evaluating Public Health Surveillance Systems for Early Detection of Outbreaks,” published by CDC.

Submitted by elamb on
Description

In November of 2011 BioSense 2.0 went live to provide tools for public health departments to process, store, and analyze meaningful use syndromic surveillance data. In February of 2012 ESSENCE was adapted to support meaningful use syndromic surveillance data and was installed on the Amazon GovCloud. Tarrant County Public Health Department agreed to pilot the ESSENCE system and evaluate its performance compared to a local version ESSENCE they currently used. The project determined the technical feasibility of utilizing the Internet cloud to perform detailed public health analysis, necessary changes needed to support meaningful use syndromic surveillance data, and any public health benefits that could be gained from the technology or data.

Objective:

This project represents collaboration among CDC’s BioSense Program, Tarrant County Public Health and the ESSENCE Team at the Johns Hopkins University APL. For over six months the Tarrant County Public Health Department has been sending data through the BioSense 2.0 application to a pilot version of ESSENCE on the Amazon GovCloud. This project has demonstrated the ability for local hospitals to send meaningful use syndromic surveillance data to the Internet cloud and provide public health officials tools to analyze the data both using BioSense 2.0 and ESSENCE. The presentation will describe the tools and techniques used to accomplish this, an evaluation of how the system has performed, and lessons learned for future health departments attempting similar projects.

 

Submitted by Magou on
Description

In 2015, there were 212 million new cases of malaria, and about 429,000 malaria death, worldwide. African countries accounted for almost 90% of global cases of malaria and 92% of malaria deaths. Currently, malaria data are scattered across different countries, laboratories, and organizations in different heterogeneous data formats and repositories. The diversity of access methodologies makes it difficult to retrieve relevant data in a timely manner. Moreover, lack of rich metadata limits the reusability of data and its integration. The current process of discovering, accessing and reusing the data is inefficient and error-prone profoundly hindering surveillance efforts. As our knowledge about malaria and appropriate preventive measures becomes more comprehensive malaria data management systems, data collection standards, and data stewardship are certain to change regularly. Collectively these changes will make it more difficult to perform accurate data analytics or achieve reliable estimates of important metrics, such as infection rates. Consequently, there is a critical need to rapidly re-assess the integrity of data and knowledge infrastructures that experts depend on to support their surveillance tasks.

Objective:

Malaria is one of the top causes of death in Africa and some other regions in the world. Data driven surveillance activities are essential for enabling the timely interventions to alleviate the impact of the disease and eventually eliminate malaria. Improving the interoperability of data sources through the use of shared semantics is a key consideration when designing surveillance systems, which must be robust in the face of dynamic changes to one or more components of a distributed infrastructure. Here we introduce a semantic framework to improve interoperability of malaria surveillance systems (SIEMA).

Submitted by elamb on
Description

Oregon Public Health Division (OPHD), in collaboration with The Johns Hopkins University Applied Physics Laboratory, implemented Oregon ESSENCE in 2011. ESSENCE is an automated, electronic syndromic surveillance system that captures emergency department data from hospitals across Oregon. While each hospital system sends HL7 2.5.1-formatted messages, each uses a uniquely configured interface to capture, extract, and send data. Consequently, ESSENCE receives messages that vary greatly in content and structure. Emergency department data are ingested using the Rhapsody Integration Engine 6.2.1 (Orion Health, Auckland, NZ), which standardizes messages before entering ESSENCE. Mechanisms in the ingestion route (error-handling filters) identify messages that do not completely match accepted standards for submission. A sub-set of these previously-identified messages with errors are corrected within the route as they emerge. Existence of errors does not preclude a message’s insertion into ESSENCE. However, the quality and quantity of errors determine the quality of the data that ESSENCE uses. Unchecked, error accumulation also can cause strain to the integration engine. Despite ad-hoc processes to address errors, backlogs accrue. With no meta-data to assess the importance and source of backlogged errors, the ESSENCE team had no guide with which to mitigate errors. The ESSENCE team needed a way to determine which errors could be fixed by updating the Rhapsody Integration Engine and which required consultation with partner health systems and their data vendors. To formally address these issues, the ESSENCE team developed an error-capture module within Rhapsody to identify and quantify all errors identified in syndromic messages and to use as a guide to prioritize fixing new errors.

Objective:

To streamline emergency department data processing in Oregon ESSENCE (Oregon’s statewide syndromic surveillance) by systematically and efficiently addressing data quality issues among submitting hospital systems.

Submitted by elamb on
Description

Public health is at a precipice of increasing demand for the consumption and analysis of large amounts of disparate data, the centralization of local and state IT offices, and the compartmentalization of programmatic technology solutions. Public health informatics needs differ across programmatic areas, but may have commonalities across jurisdictions. Initial development of the PHCP was launched with the goal of providing a shared infrastructure for state and local jurisdictions enabling the development of interoperable systems and distributed analytical methods with common sources of data. The PHCP is being designed to leverage recent successes with cloud-based technology in public health.

Success of the PHCP is dependent on the involvement of state and local public health jurisdictions in the transparent development and future direction of the platform. Equally critical to success is the selection of appropriate technology, consideration of various governance structures, and full understanding of the legal implications of a shared platform model.

Objective

To update the public health practice community on the continuing development of the Public Health Community Platform (PHCP).

Submitted by teresa.hamby@d… on
Description

The PHCP is a community-led initiative to provide shared infrastructure, services, and applications to the public health community as solutions for complex public health informatics problems. The project has progressed by establishing a governance structure led by an executive committee representative of the public health practice community. The executive committee has established the strategic path for the continued development of the PHCP and prioritized eCR as the initial use case for implementation.

Objective

To inform the community on the progress of electronic case reporting (eCR) utilizing the shared infrastructure and applications of the Public Health Community Platform (PHCP).

Submitted by rmathes on
Description

In the current state of the health care system there is uneven access to primary care, and too many people struggling to navigate the system are receiving care in the hospital for issues that would be better dealt with in the community, and then are being readmitted to the hospital only days after leaving. To address these issues and improve efficient continuity of care, the Health Links program provides a new model of care at the clinical level in Ontario. In this model all of the patient’s health service providers in the community, including primary care, hospital, and community care, work together to create a coordinated care plan for the patient. The initial focus of Health Links is on highcost users. Health Links, and primary care as a whole, require comprehensive data analysis to effectively support patients and providers. SHIIP is a portal-based technology solution that enhances individual patient care while providing real-time feedback and summarized data to help plan care. The primary objective of SHIIP is to develop an Integrated Portal with core functionalities that will facilitate the sharing of information and enable person-centred care coordination. SHIIP aims to assists the success of Health Links by providing consistent maintenance and sharing of patient records, timely communication and collaboration between a patient’s multiple health care providers, and removing physical barriers through the virtualization of care processes. SHIIP is designed to identify and assist in the delivery of care for complex/high needs patients, and will facilitate reporting, performance monitoring and quality improvement efforts. Some of the anticipated benefits of SHIIP include: enhanced patient experience, reduced workflow duplication, improved access to information at point of care, more efficient clinical documentation, and improved health outcomes. Ultimately, SHIIP helps to improve access and quality of healthcare, and consequently health equity, especially for complex/high-needs patients.

Objective

To describe how the South Eastern Integrated Information Portal (SHIIP) will support the Health Links program with the delivery of care for patients, by facilitating reporting, performance monitoring and quality improvement efforts. The portal-based technology that SHIIP uses to integrate all of a patient’s clinical care information into summarized data and to provide real-time feedback will also be explained.

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

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