Approaches to Learning openEHR

Hi!

Several years ago some of you in the openEHR community helped us answer questions about learning openEHR. Thank you very much!

For a number of reasons, a proper publication of the results was delayed, sorry about that. On Thursday I’ll present our paper “Approaches to Learning openEHR: a Qualitative Survey, Observations, and Suggestions” at http://www.shi2016.org/program.html Some of you will recognize your own answers :slight_smile:

The full paper is already now openly accessible at http://www.ep.liu.se/ecp/article.asp?issue=122&article=005

I’d also recommend reading at least one of our references if interested in the subject: http://serefarikan.com/2014/10/05/is-openehr-hard/ (Nice text Seref!)

At the same conference I see openEHR is mentioned in at least the following other two papers:

Thanks Erik for giving heads-up – I’ve read your paper with interest, wish you could’ve published earlier :wink:

I’ve also added the three openEHR papers into our Zotero research library – see date sorted view here

Or separately, 1, 2 & 3

Cheers,

-koray

Thanks Erik and Koray,

Kyoto University has open courseware related to clinical modeling by
Prof Dipak Kalra and Prof Stan Huff.
http://ocw.kyoto-u.ac.jp/en/international-conference-en/ehr

Shinji KOBAYASHI

Thanks Shinji,

Now there is a lot more educational material available than when the survey was done.

Regarding video material we also recorded the education "A clinical challenge: To lead or be led by health-IT?" That was held in Linköping Nov 2015.

The youtube playlist can be found at
https://www.youtube.com/playlist?list=PLHFGvRPKSumvhCrMbDrAWi2Kc0MrTHi9M
Background information and slides are found at http://bit.ly/lead-or-be-led-by-IT

Speakers: Silje Ljosland Bakke (Norway), Rong Chen (Sweden), Daniel Karlsson (Sweden), Heather Leslie (Australia), Mikael Nyström (Sweden), Erik Sundvall (Sweden)

Best regards,
Erik Sundvall

P.s. The videos above have semi-crazy (sometimes entertaining) subtitles created by YouTube/Google voice recognition. Feel free to pick one of the videos and use the YouTube interface (if logged in) to submit corrections to the subtitles. Corrected subtitles can then be auto-translated from English to other languages (and then manually polished) in order to provide some more international training material.

P.p.s. As hinted in the paper I still think there is a lot of room for additional interactive pedagogical tools. Especially some combination of learning-enhanced template/archetype-editor functionality tightly integrated with an example EHR-environment. Something suitable to create in some student- or PhD-related-projects perhaps? The new web-based open source archetype/templating tools could be combined with one of the open source web based openEHR systems, and pre-populated with some fictive patient data.

Hi Erik,
Good work & well done. I personally find tutorial style approach as the most efficient way of learning anything, including openEHR. The method works for teaching as well, so I think your P.p.s is a good idea.

All the best
Seref

Great work Erik. Just one small note - the links in the bibliography don’t work properly because they contain %0b in them due to linebreaks. IT people can fix that, but others may not know what is going on. I didn’t check them all, but the Architecture Overview one is broken in this way.

On the substantives, this kind of work is crucial in enabling us to improve the learnability of the specs and method. We often hear comments like ‘xxx document is too complex to understand’ or similar, but without more detailed feedback, it’s hard to know how to fix things.

  • thomas

I have that experience too, it is hard to explain something to someone completely ignorant when you self understand perfectly what is written.

Understandable writing is a profession on its own, and not necessarily to find with health-ICT designers.
I know quite a few GP's and medical specialists, also ones which are important in positions where decisions are made, and they have a busy job, and of course, academically educated. Often they feel resistance of asking what is meant there and there. They give up easy.

OpenEHR is for many, physicians and computer scientists quite out of the box thinking, and if not necessary to understand they often skip that knowledge.

It is the art of storytelling, to make the knowledge sexy or exciting which is missing in the OpenEHR communities.

(Without wanting to discuss FHIR, it is just an example how marketing and storytelling works, personal opinion)
Many people, for example, like FHIR, but not very many know exactly why. They all have the same few arguments, which I would consider as disadvantage, but the marketing machine turned them into advantages, and they all repeat each other, and of course, the name is very very good.
What you hear a lot about as an advantage of FHIR is the possibility to communicate proprietary information, but we don need a standard to communicate proprietary information. The marketing machine turned a weakness into a quality
**FHIR makes HL7 HOT!**

I would be a good idea to brainstorm on how to bring over this knowledge. Ideas about this could help us all.

I always tell about the flexibility of OpenEHR. There is a healthcare innovation, which is not supported by the information structure of a classic EPD system. In OpenEHR, you write some archetypes, some templates and gui's and you are in business with the new innovation.

There are some more stories to tell, someone should make a comic of them, or a Prezi (http://www.prezi.com). That would be better then those boring Powerpoint presentations.

Quite some way to go.

The most boring example about how to explain OpenEHR is bloodpressure.

Every EHR can store bloodpressure. So, this example does not trigger people to want to know more about it. They have difficulties not to yawn to obviously.

But imagine a new therapy for curing child-cancer, a therapy which needs new information-structures to be used. OpenEHR supports any new cure almost out of the box, anyway, without support of the EHR-manufacturer. That makes the heart beating, that makes emotions getting the adrenaline running.

Hello Erik and everyone

This was a great read indeed. I missed the original call for participation to this but several responses to the questions of the survey reminded me events from my own experience too.

Just a thought: The survey seems targeted more towards training rather than education. That is, it assumes a fair amount of knowledge and practical experience already for someone to respond to the questions about "How do you expose newcomers to the structure of openEHR". But before that, they need to understand what it is that they are actually doing (and going to be doing by adopting openEHR).

My experience in taking people with a background mainly in relational databases and working with them all the way to data modeling with openEHR is that they still need a step backwards. They need to realise that what they have been doing is a subset of a bigger picture that is shared by many different DBMSs and then start talking about these specific LEGO bricks and the things you can (and cannot) build with them. Starting with "Dual model", "Archetype", "Template", "DV_VALUE", ..., generates questions that are really more about the basics and peripheral issues rather than the subject itself (the structure of openEHR and the value it bears).

There is a lot to be covered until we can have a discussion about openEHR itself (it is also a rewarding experience) and people need a space where they can try and more importantly fail. The (by now) available implementations are ideal for this.

All the best
Athanasios Anastasiou
Lecturer in Health Data Science | Darlithydd mewn Gwyddoniaeth Data Iechyd

Probably Blood Pressure is a good example for more technical oriented
people, but as you say clinicians would need better examples or they
will become bored.
This is obvious, but if you adapt your examples to the clinical
specialty of the people you are talking it's easy to get them
interested. Luckily there are already tons of validated complex
openEHR archetypes that you can show clinicians knowing that it will
get they attention.

another simple thing that few people consider is the arithmetic of clinical models. The way I have roughly calculated it in the past is as follows:

  • openEHR.org has about 500 archetypes, at an average of about 12 substantive data points per archetype (ADL WB works this out) = ~6,000 data points
  • Intermountain has 6,500 CEMs which are fine-grained and roughly an average of 1 data point, most on lab and not overlapping with openEHR; let’s say 6,000 non-overlapping data points (in fact the real average has to be somewhat over 1 because there are some panel archetypes, but I don’t have detailed stats)

So we can say that there are about 12,000 substantive data points in the two largest clinical models added together today. (Of course, there are other CKMs, and we could count archetypes on a per-project basis as well, but to stay simple…)

If we guess that this covers about 33% of medicine, with another 2/3 to go then the ultimate target (not including genomics) is around 36,000. I’ve done this calculation a few different ways and arrived at 40,000, and 50,000. But it’s the same ballpark each time.

So the question is then: by what method could we expect 36,000 clinical data points to be formally modelled? The short answer is that the current openEHR method, with all the faults it may have, is in fact working to some reasonable extent, and can be seen to be scalable. Better coordination, support from national programmes, SDOs, etc of course would help. On the other hand, I see no other large clinical model libraries, nor technical approaches that could create such a thing.

Of course some people will say: we don’t need to model that many, we only need to model for message and document (and now web) interchange. My response is: we are no longer in the business of building messages between black boxes, but of enabling semantic content to flow between components, both ‘inside’ systems and ‘between’ them. So it is certain that someone will be interested in a coherent framework for doing this kind of modelling, it just might not be the de jure SDOs.

Above I only talk about archetypes for data. But there will be workflow archetypes in the future; we also need to include the effort for terminology, guidelines, secondary use models and other semantic artefacts. Overall, the amount of effort to build libraries of clinical semantic models is very substantial indeed, and to make it scalable, can clearly only be done by some virtual community / crowd-sourcing approach, and with very good quality formalisms, tools and governance. See this post for a more comprehensive estimate.

In my view, architectures and standards that don’t assume this reality are probably not going to solve the needs of e-health for the future.

  • thomas

I try to figure out what your reply has to do with the text you quote.

Maybe you try to formulate a sales-argument? Because that is what I am looking for and I was writing about.

Maybe I misunderstand the advantage of OpenEHR, and is what I think that is an advantage, in your opinion is a another way to a disaster.
Because you cannot just create an archetype for every something new that comes up.

I have done some thinking about this.

I wrote before on this list about a large hospital which developed its own information system, which grew to 7000 tables in 20 years, because all the time new therapies, new innovations, not only medical, but also organizational come up, how many people in a room, new insurance-requirements, new diseases, many things change in a large organization, many changes are not for medical purpose, but can have medical effect, and the software must support it all.

A friend worked in a telephone company, and they had their customer-information in a blown up database of 1200 tables, and he had to bring it back to, let's say, 100 tables. After a year, he was able to remove a third of it, and also repaired the according code, and then he was happy to find another job.

This is how software in a large organization, can explode to something which is very expensive to maintain, and in the end no-one really can understand what is going on in all details. Documentation often is unreadable 15 years after writing, and it often presumes knowledge of other details, which again brings you to many pages of the similar misunderstanding.

It are spaghetti databases, mostly surrounded by spaghetti code. Like a large building which grows without control. There are parts which you cannot go, some parts you can only go when you are very careful, there maybe machinery, some of it is running but no one knows in all details for which purpose.

I think OpenEHR can under circumstances avoid this spaghetti, because in the kernel, it remains simple, but it does not avoid chaos out of the box.
Archetypes can also become information-labyrinths. This will surely happen when the number grows to ten-thousands in 20 years. They have the advantage of having implicit documentation and context. There are no Codd myriads of tables, where dependencies of normalizations can spread to unexpected parts, but there are only archetyped object instances.

But still, there can be chaos, which archetype were we using for that situation in 2003, there may be five of them, depending on who used it and some other factors? There is the chaos, you don't know in which paths information is, so it may also be an exploded information system, with lots of information no one can find.

So, what I understand is, it is to define those 50.000 data points, and give them a unique path. Then when there is, for example a drug description, it will always be on the same path, and you don't need to know the purpose of a specific archetype when you want to list all drugs a patient has got in his lifetime, or if he had had a specific lab-test and what the result was.

But if this is the point, we have, indeed, the problem of semantical scalability. Good word for that.
50.000 data-points is not that much. We (not me, I am only the piano-player) need to give up the standards-war and work together on this.
And in the meantime, the advantage of using OpenEHR is limited? There is still the advantage of implicit documentation and context, which is a lot, and it is open for migration when the datapoints are standardized, which can be a phased process.

Maybe this is all very common knowledge in health-informatics. I should find a sponsor which pays for my trips to HIMSS, etc. :wink:

Thanks for reading
Bert

separating semantic models from technical infrastructure - explained a bit more here.

The most boring example about how to explain OpenEHR is bloodpressure.

> Every EHR can store bloodpressure. So, this example does not trigger
> people to want to know more about it. They have difficulties not to
> yawn to obviously.

Actually, I think blood pressure is a good example for explaining OpenEHR to the general public because it seems so boring.
If you explain to a UI designer you need to measure blood pressure, they think they need a timestamp, the systolic and diastolic pressure.
And that is precisely what most apps do.

But, if you want to have a meaningful blood pressure reading (meaningful for the physician) you probably have to follow some standard (like the Dutch NHG standard) and then storing a blood pressure is not that simple anymore.

And for that you have OpenEHR: archetypes modeled by domain experts which communicate to the other developers what kind of data should be stored according to the domain experts.

But imagine a new therapy for curing child-cancer, a therapy which needs
new information-structures to be used. OpenEHR supports any new cure
almost out of the box, anyway, without support of the EHR-manufacturer.

Depending on the intended audience, I think you should be careful with such statements because it sounds like everyone can create a new archetype and then they are done with it.

If you have an archetype then all you have is a way to store the data. You still need the EHR manufacturer to implement the UI or other services surrounding the data.

If you compare it to normal databases it is like saying "to support this fancy new disease, all you have to do is add a new SQL table"

Ralph.

Yes, it is true, but there is one mitigating factor that speaks for archetypes, that is that SQL tables tend to search for dependencies in already existing tables and data sets need to be hard-coded around the nets of tables that are needed to support them, but archetypes-systems carry context within the targetted data-set, so the result will have less proliferation of dependencies.

I wrote this in my previous reply, which must have been send about at the same time as yours.

One problem is not solved when using archetypes.
How to avoid a chaos of archetypes within an organization but more, between organizations and the number of archetypes will grow to many thousands.

There must be a list of data-point-definitions in a higher (semantical) order. That is what I read yesterday in Thomas linked blog.
http://wolandscat.net/2014/12/15/semantic-scalability-the-core-challenge-in-e-health/