On 28-06-18 10:33, Thomas Beale wrote:
On 27/06/2018 13:00, Bert Verhees wrote:
Dear Seref, I do not agree with this without having explored all the
possibilities. I think it is important not to jump to conclusions and
keep the discussion open.
I have some ideas how to keep it interoperable. I like to discuss
that with an open mindset.
Talking about interoperability.
By the way, how do you create FHIR messages from
OpenEhr-compositions? Or how do you create Openehr-compositions from
FHIR messages?
You have to create a template manually, fitting that item to that
datapoint, isn't it?
that is correct, because FHIR imposes its own model. This is the basic
reason why one should not really use message standards to interoperate
over systems whose data are already transparently structured. However,
some organisations want to pay for these pointless conversions, so
people do them.
Stability and Mapping:
I think FHIR is good, because it is a stable model, and mapping to/from
FHIR can be used for long time, and FHIR is also much used, so mappings
can be used in more occasions. There are also disadvantages, like the
HTTP-REST protocol which it incorporated. Google is now planning a GRPC
protocol for FHIR, and that is promising, because every datatype can
have its own GRPC field predefined, and the performance can really
improve very much, maybe even 100 times as fast. As a rule of thumb one
could say: Never use REST/JSON/HTTP1.1 for stable models, it is throwing
away a lot of performance.
Transparancy:
Data must not only be transparent in a way that people can understand
them, but they must also be transparent in a way that the
software-internals of the sender and receiver can handle them. For that
purpose they need to be mapped from and to these internal processes. If
a GP receives a FHIR message and maps it to his own EHR-tables, then the
data from that message become available in the normal working screens of
the doctor. That is transparency that is needed.
Even within two parties using OpenEhr. You are only automagically
interoperable when two parties use exact the same archetypes, else
you need to puzzle the dataitems.
they only need to use the same data points of those archetypes, or
else any specialised derivative. This isn't hard to achieve; pretty
clearly all systems using openEHR today use the same vital signs
archetypes or derivatives to record vital signs. There is no point
doing otherwise.
I don't know if that is true, but if you say so, I accept that
statement, also because it is restricted to vital signs.
https://en.wikipedia.org/wiki/Vital_signs
The same things you have to do when you need to handle a generated
archetype. But it will not be that hard. Don't expect much complexity
from these generated archetypes.
I've missed some of the earlier discussion, but unless you are dealing
with genuinely novel measurements or orders, you won't have any
'generated archetypes' for most Observations or Instructions or
Actions. You might have some for novel questionnaires or other kinds
of assessment tools (new kind of score etc). But for the vast majority
of cases, I would think the real need is for runtime /matching/ of
data points from /existing/ archetypes to create on-the-fly templates,
something we've known about for 15 years.
I agree, there are not an endless number of data-points-types. They
could also be predefined. We would need sport-coaches, athletes and so
on to help us with that.
I called them before, micro-archetypes, containing only one
datapoint, or a few closely related datapoints.
Let's assume some of these are created, for the reasons mentioned
above; pretty soon you are going to want to curate them properly and
add them to the library. Over time, the number of 'generated
archetypes' will fall to nearly zero, and it will be the matching
process that is the main challenge when encountering data not planned for.
With machine learning algorithms, it must not be hard to interpret them.
Don't understand me wrong, I like OpenEhr, because of the archetyped
system, and the flexibility it offers. It is not by accident that I
discuss it here and not in a HL7 group, although that would bring
more money.
But if flexibility is slowed down by years of review, discussing and
consensus over the whole world for a set of archetypes, then there is
not much flexibility left.
it is slowed down, that's true, and it could be faster. But I don't
see how that reduces flexibility.
The inflexibility is in giving the proceedings out of hands, losing
control, having to deal with changes which are not asked for or wanted.
The data-points would need to be as simple as possible, mostly in
ELEMENT-structure instead of CLUSTER, or only very simple CLUSTERS when
1 data-point is not sufficient. No deep structures, I would advise.
This can work very good for the archetypes which are in CKM, but all
those new devices, all those new datatypes, all this new protocols,
which cannot wait for these review-procedures, because the market
will be jumped far ahead by then.
I agree there is a need to be able to create archetypes much more
quickly based on device specifications. We need to work on that.
Yes, I agree
Bert
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