Over the past twenty years or so, 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:
·
American National Standards Institute, Healthcare
Information Technology Standards Panel (ANSI
HITSP)
Believe it or not, this is not an exhaustive list and there
are literally hundreds of formally published Healthcare IT related standards to
contend with. In many cases, the function of Healthcare Inter-operability has
become a “standards integration” or reconciliation activity.
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| Principles of Healthcare Inter-operability within "Intelligent Healthcare" |
Healthcare Inter-operability is largely today a review of
data exchange considerations. The reason for this is simple; passing data is or
should be far less complex than designing application capabilities in unison
across the multitude of systems and organizations that employ some form of
Healthcare automation. This is the essence of ‘loosely coupled’ integration,
the notion that the source systems are largely abstracted from the design
conventions of any other source system and can send or receive data externally
as long as those data sources can be mapped to some part of the source system
schema. The prevailing theory of how those data exchanges should be managed is
that specific formatting standards ought to be used to more or less regulate
the message structures. This standardization approach began before the advent
of XML, through Electronic Data Interchange (EDI) approaches and others but has
since accelerated. EDI while successful depended upon relatively simple data
exchanges and complete agreement across industry segment participants in order
to enjoy the full benefit of the resulting standard message formats. This
approach works to a degree, but does not often support complex requirements.
The good thing about specialized IT standards is that they
can help to coordinate best practices amongst hundreds or thousands of
organizations working in the same industry domain. The bad thing about specialized
IT standards is that they don’t always keep pace with technological change and
they may not support extremely complex environments well. Healthcare represents
perhaps the most complicated single practice community of its size in the
world. While there are many areas within which standardization can be easily
achieved in Healthcare, data management is not one of them. Not only that,
though, there is a serious argument to be made that extreme data
standardization (or specialization) in Healthcare might actually prove to be
counter-productive and could degrade the overall quality of care.
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