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Clinicians, integrators, health IT developers, and researchers face different priorities, forcing trade-offs
to be made that optimize data entry brevity at the cost of computability. ANF represents a collection
of patterns and approaches to provide a predictable normal form to aggregate data sets across multiple
systems. The more normalized a data set is, the simpler it will become to analyze, and errors will be
reduced. In addition to improving analysis, ANF introduces the ability to compare statements with ease
and no loss of semantic integrity.
In August 2019January 2020, ANF was submitted to published at HL7 as an Informative Ballot. You can view a copy of this submission here.
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