Hi,
I know that this is probably something very inappropriate but I happened
to need such a solution. An example:
CLUSTER [AAAA]
CLUSTER [BBBB] Some type of finding (a lesion: ulcers)
ELEMENT [CCCC] A Feature of the finding (i.e. bleeding)
v: some value
ELEMENT [DDDD] Another Feature of the finding (area)
v: some value
ELEMENT [DDDD] Another type of finding (a lesion: atrophy)
v: some value OR null_flavor
My problem is I want to be able to state whether CLUSTER[BBBB] is
observed (True) or not (False) when both features (ELEMENTs CCCC and
DDDD) are not present (NULL). I am perfectly able to state it when the
data structure is an ELEMENT.
Problem arises when none of the features (attributes) of CLUSTER [BBBB]
is observed and that two things can happen:
1) None of the features could really not be assessed, but there is
definitely an ulcer (presence=TRUE)
2) The lesion in CLUSTER [BBBB] is not visualized at all
(Presence=FALSE). But then we need to know why (classical flavors of null)?
Of course a straightforward solution is putting under each CLUSTER with
child nodes, a new ELEMENT describing its "presence" with Boolean type
and with null_flavor.
However if it will not break very badly current semantics and other
strategies, the advantages of such approach might be:
1) Reducing size, manageability and understandability of (big) archetypes
2) During querying of leaf-nodes in a huge repository, the search
algorithm can first check parent nodes' presence and then further go
down to leaf-nodes. If a whole branch is not valid/null from the top,
then there is no need to look for lower levels and the performance might
be enhanced.
I might be making a horrible proposal here technically or even there
exists another solution already, but this is what I need.
Best regards,
Koray Atala, M.D.
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