The article provides an overviev of the BioSense Program, which is an excellent example of application of informatics to strengthen public health system to effectively monitor and respond better to a public health crisis situation like one being currently faced by India by collating and integrating all data at various levels of the government. Effective surveillance shall enable keeping track of all cases, avoid panic, encourage knowledge sharing and mount coordinated response to public health crisis.

Preparing for a Public Health Crisis

Media news channels, newspapers and internet websites are full of many dire predictions about large-scale loss of life from biological or chemical attacks or a swine flu pandemic.  Computer models estimate that between 2 and 100 million people could die in the event of flu pandemic, depending on the virulence of the virus.  Fears of a major public health crisis are greater now than ever before, and governments throughout the world are trying to improve their capabilities for identifying biochemical attacks or pandemic outbreaks more rapidly.

On May 3, 2006, the United States government issued an Implementation plan for its National Strategy for Pandemic Influenza to improve coordination among federal, state, and local authorities and the private sector for pandemics and other public health emergencies.  The implementation plan calls for improving mechanisms for real-time clinical surveillance in acute care settings such as hospital emergency rooms, intensive care units, and laboratories to provide local, state and federal public health officials with awareness of the pandemics.

Overview

One such initiative is the Bio Sense Real-Time Clinical Connections Program developed by the U.S Federal Centers for Disease control and prevention (CDC).  The BioSense program, initiated in 2004, is an innovative bio-surveillance program designed to increase the nation’s emergency preparedness through the development of a national network for real time disease detection, monitoring, and health situational awareness.   Bio Sense sits atop a hospital’s existing information systems, continually gathering and analyzing their data in real time.  Custom software developed by CDC monitors the facility’s network traffic and captures relevant patient records, diagnoses, prescription information and other demographic data about the cases. BioSense requires Data Sources to transmit data using the Public Health Information Network Messaging System (PHINMS). PHINMS is written in JAVA and is certified to run on platforms that support the Sun Java Run-time Environment (JRE). The Sender (Client) is capable of sending messages as a batch or real time streaming data, receiving acknowledgements to those messages.  The software converts these data to the HL7 data messaging format, which is the standard for the health-care industry, encrypts the data, and transmits them every 15 minutes over the web to the CDC where they are maintained in a large data repository.

The system summarizes and presents analytical results by source, day, and syndrome for each ZIP code, state, and metropolitan area using maps, graphs, and tables.  Registered state and local public health agencies as well as hospitals and health care providers are allowed to access data that pertain to their jurisdiction.  They access BioSense via a web-based application over a secure data network.  Information from BioSense could show early signs of a pandemic or biologic attack and alert local hospitals, health workers, and federal and state agencies to take preventive measures.

The core principles

Communication and Collaboration: To strengthen public health informatics capacity and capability, promote community participation, encourage knowledge sharing, and enhance stakeholder value.

Transparency: To improve system operations, ensure operational excellence and leverage existing state, regional, and community level capabilities and solutions.

Innovation: To advance the research and practice of bio-surveillance and informatics.

The traditional process for public health surveillance is manual and tedious. Hospitals, physicians, and laboratories would mail or fax paper reports to public health agencies, who would then call health care providers for more detailed information.  This slow chain of person-to-person communication is not well-suited to respond to a major public health emergency.

The system helps CDC epidemiologists quickly detect early signs of a flu pandemic or bioterrorist attack and provide public health and government decision makers with the information needed to manage preparedness and response.  Simultaneous access of the data by all levels of public health decreases the time needed to classify health events as serious public health problems; decreases the time to identify causes, risk factors, and appropriate interventions; and decreases the time needed to implement countermeasures and health guidance.

BioSense first became operational in 2004, when it began gathering daily data from U.S Defense Department and Veterans Affairs (VA) Hospitals and Laboratory Corporation of American (LabCorp) orders for medical tests.  (Labcorp operates a large nationwide network of testing locations and service centers and is one of the largest clinical lab service providers in the United States).  Approximately 700 Defense Department and 1,110 VA facilities report data to Biosense.  In late 2005, CDC started to expand the BioSense network to civilian hospitals in major metropolitan areas and anticipates sharing its analysis of local and regional influenza-like illness trends with health care and other public agencies in affected areas.

To help civilian hospitals to BioSense, the CDC enlisted the Consella Group health care information technology consultants.  Consella explains the benefits of participating in a project that will serve their specific interests as well as those of the public at large and will put their data in standardized format.

Currently BioSense supports more than 800 registered users; connects with 770+ hospitals; receives an average of 175,000 near real-time messages per hour; receives data from 1300+ Department of Defense (DoD) and Veterans Affairs (VA) hospitals and healthcare facilities; and, receives laboratory data from LabCorp and RelayHealth Challenges in Interoperability

However, many hospitals have not been anxious to jump on the bandwagon because the transition would be burdensome and time-consuming.  To transmit data to BioSense, each hospital must standardize its patient and other medical data.  Most hospitals use their own coding systems for symptoms, diseases, and medications.  CDS’s contractors would have to work with the hospital to translate its data codes into the standards used by CDC’s software.  According to Barry Rhodes, CDC’s associate director for technology and informatics, “To standardize the data and do all the data validation steps is a huge technological challenge”.

Roadblocks to universal acceptance

Some in the medical community question whether the BioSense network is worth the effort.

However, BioSense contractors, points out that a hospital’s medical staff might not know right away that there’s a serious problem when patients start showing up with symptoms.  CDC scientists using the system will be in a better position to spot a major pandemic or biological or chemical attack over a wider geographic area. Having a bigger picture of what’s happening will help CDC help hospitals, police, and emergency units mobilize a better response.

Although participation in Bio Sense is voluntary physicians and health officials might resent the system because it enables the federal government to encroach on what has traditionally been the domain of local health care providers and organizations.

They note that they and not the CDC have the responsibility for responding to and managing a pandemic.  Additionally, hospitals are reluctant to sign up because of concerns about maintaining privacy and security of patient information. BioSense would let the CDC “listen in” on their treatment of patients on a real-time basis.  The CDC does not use any data that would identify individual patients.

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