Analysis Normal Form (ANF) is a logical model intended to represent a normalized view of aggregate
clinical statements recorded during treatment for analysis, research, clinical decision support, and other
purposes. ANF can be used to represent any clinical statement irrespective of how the information was captured at its source (i.e. information systems or medical devices). ANF can be used in conjunction
with other models intended to ensure that clinical information is structured and complete at the
time of entry (e.g. CIMI models, ISO/TS 13972 Detailed Clinical Models) or exchanged among systems
(e.g. HL7 CDA templates, HL7 V2 message profiles, FHIR profiles).
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 2019, ANF was submitted to HL7 for an Informative Ballot. Results will be announced in October 2019. You can view a copy of this submission here.
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