Data Sharing

Developing effective data-driven algorithms and visualizations for disease surveillance hinges on the ability to provide application developers with realistic data. However, the sensitivity of the data creates a barrier to its distribution. We have created a tool that assists data providers with de-identifying their data in preparation for sharing. The functions in the tool help data providers comply with the HIPAA 'Safe Harbor' de-identification standard by removing or obscuring information such as names, geographic locations, and identifying numbers.

Objective

To develop a robust, flexible, and easy-to-use data de-identification tool that makes it easier for data providers to create data sets that are sharable with external collaborators.

Inter-jurisdictional data sharing can enhance disease surveillance capabilities for local, state, regional and national public health situational awareness and response. BioSense 2.0, a cloud-based computing platform for syndromic surveillance, provides participating local, state and federal health jurisdictions with the ability to share aggregated data; a functionality that is easily activated by selecting an administrative checkbox within the BioSense application. Checking the data-sharing box, however, is a considerable decision that comes with benefits and consequences. On May 20-21, 2013, nine city, county, and state public health department jurisdictions (mainly from the mid-western region of the U.S.) met to explore data sharing for Heat Related Illness (HRI) surveillance using BioSense 2.0. During the workshop, all participants agreed to share data (using the BioSense 2.0 front-end application) in real-time to investigate HRI trends in regional populations during May-August 2012, evaluated HRI case-definitions, and documented benefits and barriers to inter-jurisdictional data sharing. The workshop was convened by ISDS, in collaboration with the Association of State and Territorial Health Officials (ASTHO), with the support of the U.S. Centers for Disease Control and Prevention. Staff from BioSense programmatic and technical teams were also present for the workshop.

Objective

Build upon the findings of a Regional Data Sharing workshop with the larger surveillance community to more clearly describe the benefits, barriers, and needs for data sharing on the BioSense 2.0 platform.

CDC is building a public health information grid to enable controlled distribution of data, services and applications for researchers, Federal authorities, local and state health departments nationwide, enabling efficient controlled sharing of data and analytical tools. Federated aggregate analysis of distributed data sources may detect clusters that might be invisible to smaller, isolated systems. Success of the public health grid is contingent upon the number of participating agencies and the quantity, quality, and utility of data and applications available for sharing. Grid protocols allow data owners to control data access, but requires a model to control the level of identifiability of depending upon the user’s permissions. Here, we describe a work currently in progress involving the design and implementation of an ambulatory syndromic surveillance data stream generator for the public health grid. The project is intended to broadly disseminate aggregate syndrome counts for general use by the public health community, to develop a model for sharing varying levels of identifiable data on cases depending upon the user, and to facilitate ongoing development of the grid.

Objective

To implement a syndromic surveillance system on CDC’s public health information grid, capable of securely distributing syndromic data streams ranging from aggregate case counts to individual case details, to appropriate personnel.

When the Chicago Bears met the Indianapolis Colts for Super Bowl XLI in Miami in January, 2007, fans from multiple regions visited South Florida for the game. In the past, public health departments have instituted heightened local surveillance during mass gatherings due to concerns about increased risk of disease outbreaks. For the first time, in 2007, health departments in all three Super Bowl-related regions already practiced daily disease surveillance using biosurveillance information systems (separate installations of the ESSENCE system, developed at JHUAPL). The situation provided an opportunity to explore ways in which separate surveillance systems could be coordinated for effective, short-term, multijurisdictional surveillance.

Objective

This paper describes an inter-jurisdictional surveillance data sharing effort carried out by public health departments in Miami, Chicago, and Indianapolis in conjunction with Super Bowl XLI.

The practice of real-time disease surveillance, sometimes called syndromic surveillance, is widespread at local, state, and national levels. Diseases ignore legal boundaries, so situations frequently arise where it is important to share surveillance information between public health jurisdictions. There are currently two fundamental ways for systems to share public health data and information related to disease outbreaks: sharing data, or sharing information. Data refers to patient level and aggregate counts of patients, and can be difficult to share legally because of privacy issues. Information refers to summaries, opinions or conclusions about data. There are few if any legal barriers to sharing information, and by definition it includes interpretation of data by knowledgeable local personnel which is vital during outbreak investigation. Currently most shared information is unstructured text, and this format makes it difficult for computers to use the information in any meaningful way. The only thing a system can do with this unstructured information is allow users to read each message.

Objectives

Alternate methods are needed to facilitate communication between jurisdictions during potential disease outbreaks. One alternative is to share structured information. Defined at the appropriate level, information sharing can avoid traditional data sharing barriers while capturing valuable local knowledge. The key is to identify the types of surveillance information that are neither so highly interpreted as to lose their value nor so loosely interpreted as to face traditional data sharing barriers. The objective of this work is to identify the level at which surveillance information sharing can be both feasible and beneficial, and to create a vocabulary standard that supports the exchange of structured information between diverse surveillance systems. 

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.

In the fall of 2006, the Ohio Department of Health (ODH) and the Indiana State Department of Health (ISDH) proactively began general discussions regarding surveillance issues of mutual interest. Both states, having operational syndromic surveillance systems, thought value could be added to one another’s program by sharing data across their common border. Ohio receives emergency department chief complaint data from 130 of its hospitals; Indiana from 76 hospitals. The ODH uses the EpiCenter System managed by Health Monitoring Systems, while the ISDH Public Health Emergency Service System uses Electronic Surveillance System for the Early Notification of Communitybased Epidemics. Each state desired to view the new shared data through its own system. A formal memorandum of understanding was developed and signed by both states to support syndromic data sharing. Data began flowing between the two states in April, 2008.

Objective

The ODH and the ISDH enhanced their individual syndromic surveillance efforts through cross-border sharing of emergency department chief complaint data.

The Public Health Information Network (PHIN) Messaging Service (PHINMS) is a PHIN-certified messaging system, initiated and supported by the Centers for Disease Control & Prevention. PHINMS is widely used by many hospitals in the state(s) to send their Electronic Lab Reports. The PHINMS architecture allows for multiple data streams and routing configurations. However, many states are still using the legacy File Transport Protocol for their syndromic data transfer. There are many benefits in utilizing PHINMS that will be outlined in this presentation. PHINMS contains two components: sender and receiver. A PHINMS entity (either a hospital or DOH) can act as both/either a sender and/or a receiver. This makes two-way communication possible via the same PHINMS connection.

OBJECTIVE

This presentation describes the secure and reliable data transfer methodology of syndromic data between hospitals and public health agencies using the PHINMS. Included is an overview of PHINMS and several programs South Carolina has developed including Auto Send, Data Extract, Email Notification, and Self-Issued Security Certificates. These programs are configurable for different hospitals and run automatically. The system can be easily adopted and customized by other states.

The purpose of this study is to depict a local county health departmentís analysis and dissemination algorithm of surveillance system (SS) aberration (alarm) to designated stakeholders within the community.