In our last post on Intelligent Healthcare, we talked a bit about Electronic Healthcare Record systems. EHR/EMR technology is an important piece of the larger set of clinical systems as it represents a patient centric organizational framework. However; EHRs are only part of a larger picture. One area that is particularly promising for the application of Semantic technology to healthcare is process management. When we discuss process management in this context, we’re not talking about traditional process management software solutions. Healthcare process management is in a sense a formalization of (medical) practice approaches that for the most part aren’t automated and in many cases likely never can be fully automated.

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Much if not all of the discussion over the past two years in regards to Healthcare Modernization has revolved around the deployment of Electronic Health Records (EHR) systems. Monies were budgeted to EHR adoption in last year’s Stimulus package and more monies will be allocated towards EHR adoption as a result of the recent Healthcare Reform package. So what does this all mean in regards to Intelligent Healthcare and the application of Semantic technology? First we’ll need to take a closer look at EHRs.

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Over the past twenty years, a number of standards groups have arisen to develop, manage or reconcile Healthcare data or IT-related standards. Much of the focus over the past decade has been dedicated specifically to data exchange standards and identifying standard data elements for various sub-domains of Healthcare practice automation. The primary standards bodies involved in these activities include but are not limited to the following organizations:

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Of all the areas where Semantic Technology may help to transform current practices, no one area may be impacted more than Science.

I’ll distinguish empirical science from the myriad of other sciences by stating that it is characterized more by processes designed to facilitate discovery – the scientific method. The goal of empirical science is to solve problems, it does so through answering a series of questions, often through use of experimentation. Of the IT domains I’ve discussed previously the one that is most involved in pure science is Healthcare, so let’s take a look at that for moment.

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Integration is more than the coding of application or data interfaces. When dealing with complex integration within or across enterprises, there must be sufficient discipline to achieve reproducible results. Furthermore, that discipline must be tailored to the unique requirements of the domain/s in question. Few domains are as complex as Healthcare. Even more important perhaps is that integration cannot be viewed outside of the context of the outcomes within the domains they are meant to serve. Technical success may not translate to process or performance improvement if the relationships between domain goals and enabling technologies aren’t properly understood. Some of the basic concepts associated with our IH include the following:

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