Clinical data collected by the healthcare system are a rich source of data for biosurveillance. They include the data needed for earlier detection of cases and outbreaks and for more rapid characterization of outbreaks. Clinical data in the United States at present, however, are not highly available for biosurveillance (other than that practiced by hospital infection control). The barriers include the use of paper records, multiple departmental information systems, and nonstandard data formats. In countries with national health systems such as the United Kingdom, these barriers are less daunting.
The types of data that are available in electronic form in the United States are weighted toward data collected for administrative purposes such as patient registration and billing (and market penetration is high for such systems). Some administrative systems—registration, scheduling, and billing—have data that are of value for biosurveillance and developers of new strategies for early detection of outbreaks are using these data. The use of computers to record clinical information has lagged administrative use, and market penetration is variable depending on the type of system. Clinical information systems are widely deployed in clinical laboratories and radiology departments, and are less used in pathology departments and as POC systems. Specific data that are highly available, although difficult to access, include laboratory and radiology results.
Key gaps are symptom and sign data, which are often recorded by using English, not computer encoding. The market penetration of IT into small private practices is less than in large practices; even when small practices use IT, the sheet numbers of such practices make integration of their data into a biosurveillance network an expensive and time-consuming project.
A bright note is that the clinical computing industry has been working on the problem of interfacing and data integration for several decades, so there is a large body of work already completed toward solutions that can be applied directly to the problem of integrating clinical data into biosurveillance.
A biosurveillance organization such as a state health department that wishes to create real-time data exchange with a hospital should develop both a short-term and a long-term strategic plan. In the short term, it should work with each hospital organization to determine whether the appropriate technical approach to data exchange should focus on building an interface to an existing HL7-message router, an interface to an existing data warehouse, or a POC system (or systems). We discussed principles to guide such decisions.
In the long-term, the health department should factor two megatrends into its planning. The first is that POC systems will become commonplace in both the outpatient and inpatient settings. Unless these systems are biosurveillance-enabled, meaning that their manufacturers engineer these systems to be able to interoperate with biosurveillance organizations, additional work will have to be done to create such interfaces. The second is the NHII movement, which, if supported by governmental public health, may lead to the required biosurveillance enabling of clinical information systems on an accelerated time frame.
The protestant minister, when asked for his secret for giving a good sermon, responded "first I tell them what I'm gonna tell them, then I tell them, then I tell them what I told them.'' POC systems with decision support are the future of biosurveillance. HL7-message routers represent unique resources for the present. POC systems enable collection of symptom and sign data in coded format. Their decision support capabilities can support real-time bidirectional interactions among frontline clinicians and biosurveillance organizations. They can support computer-based case detection and case reporting. The RHIO component of the NHII movement is also important, if it is supported, to the future of biosurveillance. POC systems with decision support and RHIOs are important to the future of biosurveillance.
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