RE: An argument for bridging information models and ontologies at the syntactic level

Alan,
 
Thanks for the detailed feedback. Some responses are included below.


	My main contention is that the things that we put in medical records
represent statements "ascribing" (or "not ascribing") characteristics and
relationships to patients - i.e.
	we are saying that the patient "_has_ a white count = 10,000" or that
the patient "_has_ Diabetes".  (For diabetes we may also say that the patient
"_does_not_have_ diabetes)

	We may be basing this information on information about a sample, an
artifact (e.g. a Radiology study), a direct observation, or a diagnostic
inference.  
	[VK]  I agree with the requirement of separating observation from
diagnosis.
	 
	 In each case there is a degree of inference - indicated by the fact
that most information has to be "approved" before it gets into the record.
	[VK] Shouldn't it be the case, that there is no inference in the context
of an observation. Would think that an observation is basically the result of
recording our perceptions about the patient?
	I understand that at a philosophical level, e.g., what happens when your
perception directs you to a reading at a finer granularity the least count of
the measurement device or how do we decide 0 degrees and 100 degrees centigrade?
	observations and assessments can be inter-twined with each other. But I
think its possible to presume that in a pragmatic sense, an observation doesn't
require inference.
	 
	However, there is indeed a chain of inferences involving some
combination of assessments, impressions, findings and diagnoses. Wonder how
these various types of inferences play out? 

	i) concerns the chain of evidence, long or short, and our systems
sometimes conflate the measurement and the statement of belief based on that
measurement (the "ascription").  However, when we go to reason about it the
reasoning is very different.  If we infer that the patient has an elevated
potassium we do something; if we think the sample has been haemolized we do
something else.  But no person "has" a haemolised K+" although they may have the
source from which "a haemolised sample" was taken on which a measurement of K+
was performed.
	[VK] Agreed. This is why there is a need to clearly differentiate
between an observation, an assessment and a diagnosis.... 

	II) concerns what statements can convey information.  Since our
background information model (sometimes oddly called an "ontology") says that
all people at all times have a white count, there is no point is saying "The
patient has a white count" (although there is a point in saying: "the patient
has had a white count performed"). 
	[VK] Agreed. The latter is an example of a process outcome and may be
useful while measuring compliance to a recommended clinical process or
guideline. 
	 
	By contrast, "Diabetes" and "Cardiac Murmur" are both things that only
some people have only some of the time.  Simply to say that a patient _has_ them
conveys information because we don't know it already and does differentiate them
from other patients, or the same patient at different times or as observed by
different observers. 
	[VK] Agree with the above, just that I would not characterize the above
as observations but may be as diagnoses which have been obtained as a result of
some inferences. Maybe a better way of making the statement above is: "the
patient has the state of diabetes".
	So, analogous to the previous case, it would not give us extra
information when we say that "a patient has state". 

	We tend to use the label "Situation" for the entity that reprsents a
patient at a time as observed by an observer (who records their information) and
"includes" as the property, so that, the appropriate level for transforming
between ontologies, codes, and information models must take this into account.
	[VK] Would propose that we different "Situation" from "Action", i.e.,
the act of observation of a patient situation is different from the situation.
	       Would using the label "State" be a an appropriate interpretation?
For e.g., patient state at a time as observed by an observer? 

	Note that "having diabetes" is different from "diabetes".  There is
different information to be conveyed about "diabetes" and about "having
diabetes" (or more precisely, ("situations having diabetes" - or in our usual
notation Situation THAT includes Diabetes).
	[VK] Agreed. Wonder if an alternative formulation - State THAT includes
Diabetes is appropriate? 

	This approach deliberately makes it possible get the equivalences
between a finding

	"'_has_ WBC>=10,000" and what SNOMED has trditionally called an
"observable "'_has_ WBC' >= 10000'" as a test and value (range).
	
	And alows us to say of the same WBC that it is considered to be
'elevated".
	[VK] But an observation of has_WBC > 10,000  and level_WBC = 'elevated"
are two different things, as the latter involves an assessment. 

	The evidence chain for the statement that the WBC is elevated goes back
to the statement about the WBC being above 10,000 which in turn goes back to the
lab test etc.
	[VK] Agreed. 

	B) There is different information to be conveyed about the entity that
is being tested for - e.g. WBC - and the method of testing. Therefore it makes
sense for there to be separate entities for them at some level in our modelling.
(You can order a test, you can't order somebody to have a WBC). 
	[VK] I think Snomed has done a good job here by modeling observables
whereas LOINC models the method of testing. So yes we need to differentiate
between the observable and the finding for which I think Snomed has a reasonable
model?
	 
	  In the same way, the test result is clearly different from the
statement that it is valid for the patient.  
	[VK] I understand it all depends on how much a physician trusts the lab
which delivers the result.
	 
	Thanks,
	 
	---Vipul


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