Info

RHIO indicates regional health information organization. *RHIO is exchanging administrative and billing data. tRHIO is exchanging clinical data.

*The state government played a major role in creation of RHIO, either through legislation that created the RHIO or through a government agency that convened the stakeholders.

§RHIO has received external funding as of this writing.

RHIO indicates regional health information organization. *RHIO is exchanging administrative and billing data. tRHIO is exchanging clinical data.

*The state government played a major role in creation of RHIO, either through legislation that created the RHIO or through a government agency that convened the stakeholders.

§RHIO has received external funding as of this writing.

We next discuss three of the most well-known RHIOs (two of which are statewide) and use these examples to explore the opportunities and challenges inherent in the NHII effort.

The Indiana Health Information Exchange (IHIE) is arguably the most successful RHIO to date. IHIE was formed in 1996 as the Indianapolis Network for Patient Care when Wishard Memorial Hospital began sharing its data unilaterally with other hospitals to demonstrate the value of health-data exchange. As a result of this leadership, other organizations began sharing their data, and by 2004, the RHIO included five healthcare systems (14 hospitals total), four homeless clinics, and three hospital-affiliated physician group practices. In 2004, the scope of the RHIO expanded to statewide.

The IHIE illustrates the promise that NHII holds for biosurveillance. By 2001, IHIE was reporting notifiable diseases over a single network connection to the Marion County Health Department16 from five clinical laboratories serving nine hospitals (Overhage et al., 2001). The IHIE had already standardized its participating laboratories' data for purposes of clinical data exchange before the biosurveillance project. It therefore reports notifiable diseases to Marion County Department of Health by using current CDC-recommended standards (HL7, LOINC, and SNOMED). As the IHIE expands and standardizes the laboratory data for additional hospitals in Indiana, the data will be available for biosurveillance as a by-product of what is fundamentally a clinical data integration project. At present, the IHIE also reports chief complaint data for biosurveillance over a single connection from all the participating hospitals.

The IHIE also illustrates the challenge of NHII. It took several years for IHIE to create the administrative and technical infrastructure necessary to integrate data from just nine laboratories. IHIE had to obtain sufficient grant funding to develop the data systems and manage the project, and the technical staff had to analyze the laboratory data and develop custom software to translate the data into standard encodings and formats. We note that the required skill set for understanding laboratory information management system data and creating translation capability is not widely available. Finally, the IHIE (as with other RHIOs) still has not achieved a business model that allows it to be self-sufficient without grant support.

The Santa Barbara County Care Data Exchange was founded in 1998 and incorporated in 1999. Its participating organizations planned to start exchanging data only in February 2005 (Anonymous, 2005).This RHIO is noteworthy for being a case study in the cost and effort to develop a RHIO. It has already spent $10 million in grant funding from the California Health Care Foundation to develop the organizational and technical infrastructure necessary for data exchange, and in 2004, it received another $400,000 in funding from the federal government (Colliver, 2005). We note that this cost and effort does not include the cost of data standardization.17 Furthermore, data do not flow from one organization's information system to another, but instead physicians view all the data for a

16 The city of Indianapolis, IN is located in Marion Country.

17 The Santa Barbara Country Care Data Exchange makes use of HL17 Clinical Context Object Workgroup standard. However, this standard is not a data standard, but a standard way of passing patient and user informatin among clinical applications so that viewing a patient's data that resides in one application while using another application is seamless. The data viewed, however, may be (and often are) nonstandard.

patient—regardless of the organization at which the data orig-inated—by using a Web browser.

The Utah Health Information Network (UHIN) was founded in 1993. At present, the participating organizations are hospitals, physicians, and every health plan in Utah except one. These organizations exchange administrative and billing data. By use of an AHRQ grant of $5 million awarded in 2004, it has recently begun the work to exchange clinical data among its member organizations. UHIN also illustrates the difficulty of NHII: in its 12 years of existence, it has accomplished the exchange of only nonclinical, administrative data among many, but not all health plans, hospitals, and physicians in Utah.

8.2.3. Improve Public Health

As the first two NHII goals are achieved, regional healthcare data will become increasingly available for biosurveillance. RHIOs will provide increasing coverage of the relevant organizations in a region. Instead of having to establish point-to-point data exchange with dozens of hospitals, hundreds or thousands of physicians, and numerous laboratories, pharmacies, and diagnostic imaging centers, a biosurveillance organization will establish a single relationship and technical connection to a RHIO. It is perhaps obvious, but worth stating, that ensuring that RHIOs are designed to meet the needs of biosurveillance will increase their societal value and potentially lower costs for all parties involved in the RHIO by expanding the set of organizations that might share in the development and operational costs.

8.2.4. Is the Glass Half Empty or Half Full?

Despite the current momentum of the NHII initiative, we caution that many barriers to progress exist. A recent study by Kaushal et al. (2005) suggests that the 5-year cost to achieve a model National Health Information Network18 exceeds projected spending on IT by the healthcare system.

Even if the U.S. Congress was to authorize the additional $132 billion estimated by Kaushall et al. to create an achievable (as opposed to ideal) model NHII, the number of technicians required for tasks such as vocabulary mapping and system integration is likely to be rate limiting. Governmental public health departments continue to expend resources on alternative solutions such as Web-based disease reporting and direct ELR, which consumes healthcare resources. Healthcare systems have finite resources and devoting them to one project often comes at the cost of not being able to devote them to another project. The CDC has advocated for NHII but has not yet invested in its development or included it in guidelines that shape how state and local departments of health invest federal funds.

Nevertheless, the potential advantages of the NHII model and its current momentum suggest that NHII will transform significantly how the United States conducts biosurveillance in the future.

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