Machine Learning , some thoughts

Seref Arikan serefarikan at kurumsalteknoloji.com
Wed Jun 27 09:20:04 EDT 2018


Dear Bert,

Always happy to keep a discussion open and I appreciate your input. I'm
sure achieving the kind of agility without introducing the problems I
mentioned would be of interest to many people, so by all means feel free to
make suggestions.

The market is a commercial dynamic. It is true that it keeps jumping
around, but not necessarily far ahead, at least in terms of providing the
solutions to the health IT problems we've been trying to solve.

I for one will be keeping an eye on your suggestions re how to do what
you're suggesting

Kind regards
Seref



On Wed, Jun 27, 2018 at 1:00 PM, Bert Verhees <bert.verhees at rosa.nl> 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?
> 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.
>
> 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 called them before, micro-archetypes, containing only one datapoint, or
> a few closely related datapoints.
> 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.
> 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.
>
> Best regards
> Bert
>
>
> On 27-06-18 11:50, Seref Arikan wrote:
>
> Hi Bert,
>
> Let me try to keep it brief: you seem to suggest breaking the openEHR
> methodology. If you allow downstream actors (clinical systems, guided by
> their users) create archetypes without going through the methodology, i.e.
> creating, discussing, reviewing archetypes, you'll end up with computable
> health with no interoperability.
>
> This will in turn break machine learning because you cannot learn anything
> valuable from datasets which are created based on data, which are based on
> models, which are based on clinicians going siri on their systems.
>
> As a side note, this whole domain will make much faster progress when
> someone starts teaching clinicians (when they're at medical school) that
> informatics, just like washing hands before an operation, is partly their
> responsibility and they cannot get much out of their systems until they
> start taking charge of some aspects of it, instead of waiting for vendors
> to present them their incorrect/biased view of clinical care.
>
> Our fundamental problems need humans doing what needs to be done, we're
> still nowhere near the capability to get rid of having to do what openEHR
> methodology allows us to do, from and AI perspective.
>
> All the best.
> Seref (who could not keep it brief...)
>
>
>
>
> On Tue, Jun 26, 2018 at 11:31 PM, Bert Verhees <bert.verhees at rosa.nl>
> wrote:
>
>> One short addition, why this discussion, the original point:
>>
>> What about machine learning?
>> Machine learning becomes possible when many daily health related data are
>> available. A machine can, f.e. detect deviations.
>>
>> Why generated archetypes?
>> Every day there are new devices, new ideas about health, we cannot wait
>> for CKM to follow day to day inventions, and some of them only used by
>> minorities. The EHR must be able to create archetypes when needed.
>>
>> Op wo 27 jun. 2018 00:18 schreef Bert Verhees <bert.verhees at rosa.nl>:
>>
>>> Thanks for supporting reactions.
>>>
>>> It is really typical in western medical science that it is very problem
>>> oriented. All EHRs, even unconventional one, even the new thinking, it is
>>> very problem oriented.
>>>
>>> All data are gathered around a problem and in relevance of a problem.
>>> All datastructures are pointing to a problem. Without problem there is no
>>> datarecording.
>>>
>>> It is historically grown like that. Medical data collecting is only done
>>> by clinicians, and only when a patient has a problem, the data around the
>>> problem, the diagnosis, and the treatment, that is important. Data which do
>>> not have a known relevance are not recorded.
>>>
>>> And when the patient has a new problem, the only information available
>>> are the problems in history. Information about lifestyle is unknown. One
>>> can ask the patient, but some patients have a selective memory.
>>>
>>> But in sports this is different. Medical datarecording also happens when
>>> there is no problem, but as daily routine. But now, many people today, also
>>> no-sport people, I wrote before today, measure data many times. Apple
>>> patented a blood pressure device in Applewatch. It is cheap, easy to do.
>>>
>>> It will not take long and people have their own EHR at Google, Amazon,
>>> Microsoft, Walmart or Apple, to record their daily medical data. They maybe
>>> will be able to demand that GP's store their findings in that EHR, so a
>>> more holistic view about the patient will become available, and maybe
>>> insurance companies will reward access to that holistic view.
>>>
>>> We must prepare for that, the face of healthcare will change. Until now
>>> it was problem-care, which we called in Orwellian tradition Newspeak:
>>> healthcare. But it will change to really healthcare. It is something
>>> completely different, and it happens fast.
>>>
>>> I learn also from this, while writing I learn. But I have said it all.
>>> Now it would be nice to discuss how to implement healthcare instead of
>>> problemcare.
>>>
>>> Bert
>>>
>>> Op di 26 jun. 2018 22:18 schreef Karsten Hilbert <
>>> Karsten.Hilbert at gmx.net>:
>>>
>>>> > But the person should be seen as more then a medical complaint, but
>>>> as a
>>>> > complex of conditions and lifestyle.
>>>> > We need generic archetypes which can store machine generated datasets
>>>> to
>>>> > store information about the whole person, instead of only the medical
>>>> > condition which is subject of conversation.
>>>> >
>>>> > I believe I am the only person in this list who thinks like that. But
>>>> > that does not matter.
>>>>
>>>> Actually, any worthwhile GP thinks like that (except we don't say
>>>> things like "datasets" or "generic archetype").
>>>>
>>>> I rather doubt you are alone in this. Even on-list.
>>>>
>>>> Karsten
>>>>
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>>>
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