Know your data?

Recently I was reminded of some work we did a number of years ago. It involved a large research database, painstakingly collected over 20 years. The data was defined across a number of specialisations within a single clinical domain and represented in 83 data dictionaries stored in an Excel spreadsheet.

Data was collected based on a series of questionnaires, and we were told that successive data custodians had, true to human nature, made slight tweaks and updates to the questionnaires on multiple occasions. The data collected was actually evolving!

The only way to view the data was to open each of the 83 spreadsheets, painstakingly, one by one.

We were engaged to create archetypes to represent both the legacy data and the data that the research organisation wished to standardise to take forward.

So the activity of converting these data dictionaries - firstly to archetypes for each clinical concept, and then representing each data dictionary as a template - resulting in considerable insight into the quality and scope of the data that hadn't been available previously.

For example, the mind map below is an aggregation of the various ways that questions were asked about the topic of smoking.

Interestingly, what it showed was that no one individual in the organisation had full oversight of the detailed data in all of the data dictionaries.The development of the archetypes effectively provided a cross section of the data focusing on commonality at a clinical concept level and revealed insights into the whole data collection that was a major surprise to the research organisation. It triggered an internal review and major revision of their data.

Some of the issues apparent in this mind map are:

• A number of questions have been asked in slightly different ways, but with slight semantic variation, thus creating the old 'apples' vs 'pears' problem when all we wanted was a basket of apples;
• Often the data is abstracted and recorded in categories, rather than recording the actual, valuable raw data which could be used for multiple purposes, not just he purpose of the rigid categories;
• Some questions have 'munged' two questions together with a single True/False answer, resulting in somewhat ambiguous data; and
• Some questions are based on fixed intervals of time.

No doubt you will see other issues or have more variations of your own you could share in your systems.

And we have repeatedly seen a number of our clients undergo this same process, where archetypes help to reveal issues with enormously valuable data that had previously been obscured by spreadsheets and the like. The creation of archetypes and re-use of archetypes as consistent patterns for clinical content has an enormous positive impact on the quality of data that is subsequently collected.

And while harmonisation and pattern re-use within one organisation or project can be hard enough, standardisation between organisations or regions or national programs or even internationally has further challenges. It may take a while to achieve broader harmonisation but the benefits of interoperability will be palpable when we get there.

In the meantime the archetypes are a great way to trigger the necessary conversations between the clinicians, domain experts, organisations, vendors and other interested parties - getting a handle on our data is a human issue that needs dialogue and collaboration to solve.

Archetypes are a great way to get a handle on our data.

Preventing health data 'black holes'!

It really is not surprising that scientific data is disappearing all the time. But, oh, think of the value of this data - in terms of cost and knowledge. Irreplaceable. The original article from Smithsonian.com is here: The vast majority of raw data from old scientific studies may now be missing.

Some excerpts:

A new survey of 20-year-old studies shows that poor archives and inaccessible authors make 90 percent of raw data impossible to find.

...

When a group of researchers tried to email the authors of 516 biological studies published between 1991 and 2011 and ask for the raw data, they were dismayed to find that more 90 percent of the oldest data (from papers written more than 20 years ago) were inaccessible. In total, even including papers published as recently as 2011, they were only able to track down the data for 23 percent.

...

"Some of the time, for instance, it was saved on three-and-a-half inch floppy disks, so no one could access it, because they no longer had the proper drives," Vines says. Because the basic idea of keeping data is so that it can be used by others in future research, this sort of obsolescence essentially renders the data useless.

...

And preserving data is so important, it's worth remembering, because it's impossible to predict in which directions research will move in the future.

Seems to me that the openEHR approach to data definitions is an excellent candidate for preventing the health data 'black hole' too!

Non-proprietary, open data specifications are a key component for future-proofing irreplaceable clinical and research data.

Archetypes/DCMs MIA in SDOs

Curious to note that there is very little apparent interest in detailed clinical information models (DCMs) of any brand or flavour in the major Standards Development Organisations (SDO's) - they are effectively Missing In Action when compared to the likes of CDA and IHE profiles. The ISO 13972 DCM specification took a long and tortuous time to travel through the ISO TC 215 processes. Engagement with 13972 during its development, and from what I can observe now it is on the verge of publication has been rather sparse.  A further piece of work is now starting in ISO regarding quality criteria for DCMs but it also seems to be struggling to find an audience that understands it, or even cares.

I don't quite understand why the concept of DCMs has not been a big ticket item on the radar of the SDOs for a long time as it is a major missing piece of any standards-based framework. Groups like CIMI are raising awareness, alongside the openEHR work, so momentum is gathering, but for some reason it seems to keep a very understated profile compared to new opportunities like FHIR in HL7.

The work of messages, documents, profiles and terminologies are clearly important for interoperability, but standardisation of clinical content models working closely with terminologies can potentially make the work required to develop messages, documents, and profiles orders of magnitude easier.

Let me test a metaphor on you. Think of each message, document or profile as a sentence and each archetype or DCM as a word, a building block that is one component of each sentence. By focussing on the building a specific sentence, we are working backwards by trying to determine the components, and the outcome is still just that single sentence. However if we start by standardising the words/archetypes, then once they are stable it is relatively simple to construct not only one sentence for a specific purpose, but the potential is a much greater output in which many more additional sentences can be created using a variety of words in different combinations. If we manage the words (archetypes) as core building blocks and get them right, then we allow a multitude of possible sentences (messages/documents/profiles) to proliferate.

The ‘brand’ of archetype/DCM solution does not concern me so much as raising awareness that clinician-led, standardised clinical content is a significant missing and overlooked piece of the international eHealth foundations puzzle.

Standards Development?

https://twitter.com/psujorge/status/438909282499977216

Technical/Wire...Human/Content

In a comment on one of my most recent posts, Lloyd McKenzie, one of the main authors of the new HL7 FHIR standard made a comment which I think is important in the discourse about whether openEHR archetypes could be utilised within FHIR resources. To ensure it does not remain buried in the rather lengthy comments, I've posted my reply here, with my emphasis added.

Hi Lloyd,

This is where we fundamentally differ: You said: "And we don’t care if the data being shared reflects best practice, worst practice or anything in between."

I do. I care a lot.

High quality EHR data content is a key component of interoperability that has NEVER been solved. It is predominantly a human issue, not a technical one - success will only be achieved with heaps of human interaction and collaboration. With the openEHR methodology we are making some inroads into solving it. But even if archetypes are not the final solution, the models that are publicly available are freely available for others to leverage towards 'the ultimate solution'.

Conversely, I don't particularly care what wire format is used to exchange the data. FHIR is the latest of a number of health data exchange mechanisms that have been developed. Hopefully it will be one that is easier to use, more widely implemented and will contribute significantly to improve health data exchange. But ultimately data exchange is a largely technical issue, needs a technical solution and is relatively easy to solve by comparison.

I'm not trying to solve the same problem you are. I have different focus. But I do think that FHIR (and including HL7 more broadly) working together with the openEHR approach to clinical modelling/EHRs could be a pretty powerful combo, if we choose to.

Heather

We need both - quality EHR content AND an excellent technical exchange format. And EHR platforms, CDRs, registries etc. With common clinical archetypes defining the patterns in all of these uses, data can potentially start to flow... and not be blocked and potentially degraded by the current need for transforms, mappings, etc.

Archetypes: health data bridges

What do we want for our health data - silos of information models for different purposes or ones that bridge multiple use cases? From a series of emails shared on the HL7 Patient Care email list in the past few days...

Grahame Grieve (FHIR, HL7):

"Heather, you need to keep in mind the difference between FHIR and clinical models: it's not our business to say not to exchange data that people do have because some user in an edge case might not understand it. We define an exchange standard, not a clinical UI standard..."

and

"Heather, do not lose sight of the difference between a clinical standard for what care/records should be, and FHIR, which is an IT standard for how care records are."

My response:

"...I am concerned about developing another standard that you state clearly is only designed for exchange and not for what care records should be. If we are not designing to try to harmonise data requirements for health information exchange, how clinical care records are and how clinical care records should be, then we are building siloes of data structures again, that will require mappings and transforms ad infinitum. I’d hate to see us end up with a standard for exchange that can’t be implemented for persistence"...

If we end up with models for exchange, models representing current data in systems (whether or not they represent good clinical practice and models that are regarded as the roadmap for good data, then what have we got? Three sets of data models that perpetuate the nightmare of non-interoperability.

Our openEHR archetypes are attempting to bridge all of these. Use them in whatever context you choose - messages, document exchange, EHR persistence, CDS, secondary use, aggregation and analysis, querying etc. The 'secret sauce' is the use of a second layer of modelling - the template, that allows the correct expression of the archetype appropriate for the context of use.

Mappings and transformations are acceptable where we don't have any choice, especially with legacy data, but they open us up to vulnerabilities from errors, misinterpretation and ambiguity, concerns re data integrity and possible overt data loss. Given the choice, lets work towards creating high quality data that can be re-used in multiple contexts safely.

The Questionnaire Challenge

How should we model questionnaires in our health data? This is something that @ianmcnicoll and I have grappled with for years. We have reached a conclusion in recent times, and our approach, perhaps rather controversially, is not to model them! Yes, you read me right - as a general principle, don't archetype questionnaires.

Now of course there will be some situations where there are standardised and ubiquitous questionnaires and perhaps it will be reasonable to lock these down as fixed data elements and value sets in an archetype, and maybe even govern them within a CKM environment.

But... Consider the number of questionnaires out 'in the wild' at any point in time. Should each of these be archetyped?

Let's think it through. If there are 5000 questionnaires in the world (and clearly there are way more questionnaires than that out in the health ecosystem) then we would need a corresponding whopping 5000 archetypes. And, as we all know, no two questionnaires will be alike even if they have a common parent document - it is always human nature to 'tweak' each one for local use because 'our situation' is unique. It's just the way it is. The consequences are that any data captured using the myriad of archetypes, even though they may be similar, the data will not be interoperable. We will have a huge number of archetypes with a huge variation in content and intent - not a lot of upside from my point of view.

Another alternative could be to define a generic archetype pattern for a questionnaire, and re-use that. In fact we tried this back in 2007 with our work in the NHS - you can see a reasonable example here. The resulting questionnaire pattern is pretty simple and relies on using the templating layer to document the questions, and either templating or use of a terminology subset to record the answers. The equivalent FHIR resource appears similar in principle and intended use. This kind of pattern provides a common framework for a questionnaire but really doesn't give us a lot more interoperability for questionnaire data - the actual questionnaire content will vary enormously and the results can still be chaotic.

So, still somewhat clunky and awkward - not an elegant solution at all.

Then we got to thinking: Do we always need to actually record the questions and their answers in the EHR? This is a critical question. Sometimes the answer is yes, but most often I think we will find that we don't need to record the actual question and (often) check box response. What we really want to record is the outcome, the real health information meaning.

Think about the practical aspects of this...

Clinicians have a systematic questioning process for history taking - we all have a similar pattern but ask subtly different questions - resulting in zillions of permutations and combinations and levels of granularity. Questions could range from: "Have you had any abdominal symptoms?" to "Have you had any nausea, vomiting, reflux, abdominal pain, diarrhoea, constipation etc" to whatever combination is relevant for a given clinician in a given clinical situation. Many will ask the same kind of question slightly differently. Every resulting questionnaire will be slightly different.

And what do they record? They don't record each question and corresponding Yes/No answers in their paper health records. They record the positive responses or the relevant negatives, and/or maybe a quick note that there were no positive responses to systematic questioning about current symptoms, problems, past history, family history etc.

So we need to ask ourselves: Do we need to record the exact question, the potential alternative answers and the actual answer?

If the answer is yes, then it is a very good reason to lock in the questionnaire in an archetype, or at least a template.

If the answer is no, then what is the best way to record the relevant data - the relevant positives and the relevant negatives. For example, with abdominal pain - record the details about their diarrhoea and colicky pain in the right lower abdomen, PLUS that the patient has NEVER had an Appendicectomy.

So I'm suggesting that we need to record the positive presence of something identified in the questionnaire, for example a symptom, diagnosis or previous procedure, and the positive absence of related things. In this case, record the details about the diarrhoea and abdominal pain as the positive presence of symptoms using the Symptom archetype and positive exclusion of a previous Appendicectomy procedure in the Exclusion of Procedure archetype. We don't need to record the actual question and corresponding Yes/No answer.

So our current approach in Ocean is to use the software UI as the means to display the checklist or questionnaire, but only record in the electronic health record any relevant answers - both the positive presence of symptoms, signs, diagnoses, procedures and tests etc, and also the positive exclusion of any of these things - all using standardised archetypes.

Lets face it, it is not often that we ever go back to look at the raw questionnaire data again. So now we tend not to record the raw data (with some exceptions, where it may be required or useful) but use a transform so that a patient's or clinician's positive tick in a box for 'Past History of Epilepsy?' will be converted into a positive statement of 'Epilepsy' within an EHR, using the Diagnosis archetype. Any additional 'other' free text or 'details' or 'date of diagnosis' from the questionnaire can be captured using other relevant data fields for the Diagnosis archetype. The benefit from this approach is that this data can then be potentially re-used into the future as part of a comprehensive Problem List, not just buried as a ticked check box within a questionnaire from years ago, perhaps never to see the light of day ever again.

Consider the questionnaire as what it really is - just a clinical communication tool, a checklist. It is absolutely not the best means to record, persist and re-use good quality health data. What we really want to record in a consistent way are those critical pieces of health information in a formal archetype so that the data can be utilised for long term health records, decision support, exchange or analysis. Recording the check boxes answers from a questionnaire don't really do that job!

Stop the #healthIT 'religious' wars

I seemed to trigger an interesting discussion over on Grahame Grieve's blog when I posted the following question to him on Twitter. https://twitter.com/omowizard/status/432869451739185152

Grahame responded a la blog, but not really answering the essence of my question.

However, below is a great comment copied directly from the discussion thread, and submitted by Koray Atalag (from openEHR NZ). In it he has succeeded in expanding my twitter-concise thoughts rather eloquently:

"Hi guys,

I’m interested in getting these two awesome formalisms as close as possible. In what way – have no clue at the moment apart from existing mutual understanding and sympathy at a personal level. Well that’s where things start I guess  Ed Hammond once said, as he was visiting us in Auckland last year, convergence in standards is a must, mappings just become complex and hard to maintain. I kind of agree with that. Where I’d like to see openEHR and FHIR is really dead simple – Share what they are the best. Here is how I see things (and apologise if you find too simplistic): 1) Archetypes are THE way to model clinical information – anyone argue with that? 2) FHIR IS the way to exchange health information over the wire; modern, non-document/message oriented, heaps of interest from vendors etc. 3) openEHR’s Model Driven Development methodology can be used to create very flexible and highly maintainable health information systems. So this is a different territory that FHIR covers. Inside systems vs. Outside. A growing number of vendors have adopted this innovative approach but it’d be dumb to expect to have any significant dominance over the next decade or so.

So why not use openEHR’s modelling methodology and existing investment which includes thousands of expert clinicians’ time AND feed into FHIR Resource development – I’d assume Archetypes will still retain lots of granularity and the challenge would be to decide which fall under the 80%. I take it that this proportion thing is not mathematical but a commonsense thingy.

As with anything in life there is not one perfect way of doing health IT; but I feel that FHIR based health information exchange with propriety (and from the looks increasingly monolithic) large back-end HIS and openEHR based health information systems working with rich and changeable clinical data (note some Big Data flavour here will prevail in this rapidly changing environment.

So I’m interested – probably mapping as a starting step but without losing time we need to start working together.

The non-brainer benefits will be: 1) FHIR can leverage good content – I tend to think a number of Published or Under Review type archetypes have been in use in real life for a while and that’s probably what Heather was referring to by clinical validation. A formal clinical validation is a huge undertaking and absolutely unnecessary I guess unless you’re programming the Mars Colonisation Flight health information systems!

2) openEHR can learn from FHIR experience and use it as the means to exchange information (I haven’t yet seen EHR Extracts flying over using modern web technologies). There is an EHR service model and API but I’d say it is not as mature as rest of the specs.

3) Vendors (and the World for that matter) can benefit from 1) mappings; and then 2) better FHIR Resources in terms of more effectively managing the semantic ‘impedance mismatch’ problem. An example is medication – I’d assume an HIS data model for representing medication should have at least the same granularity as the FHIR Resource it ought to fill in (practically only the mandatory items). If any less you’re in trouble – but having a sound model will ease the HIS internal data model matching and help with deciding which part is 80% vs. 20%.

4) Needless to say vendors/national programmes using pure openEHR vs. FHIR + something else will benefit hugely. Even ones using CDA – remember some countries are using (or just starting as in New Zealand) Archetypes as a reference library and then creating payload definitions (e.g. CDA) from these. So having this openEHR – FHIR connection will help transition those CDA based implementations to FHIR. Interesting outcome 

5) I think in the long run vendors can see the bigger picture around dealing with health information inside their systems and perhaps start refactoring or rebuilding parts of it; e.g. clinical data repositories. An HIS with sound data model will likely to produce better FHIR instances and definitely have more capability for using that information for things like advanced decision support etc.

All for now…"

And then the conversation continues, including Thomas Beale from @oceaninfo and Borut Fabjan from @marandlab. I know of many others who have expressed a strong desire for openEHR clinical content and FHIR to be more aligned and collaborative.

FHIR seems here to stay - it is gathering fantastic momentum. The openEHR methodology for developing clinical content is also gathering momentum, including national program adoption in a number of countries and in clinical registries.

Chuck Jaffe (CEO of HL7) emphasised the need for collaboration between standards at last week's Joint Inter-Ministerial Policy Dialogue on eHealth Standardization and Second WHO Forum on eHealth Standardization and Interoperability at the World Health Organisation in Geneva.

So let's do it.

We all live in the real world and need to be more proactive in working together.

It is time to stop the 'religious wars', especially the long-time, tedious 'not invented here' argument between openEHR and HL7 and the ever-ongoing lets 'reinvent the wheel' approach to EHR content that occurs more broadly.

I call on all participants in the eHealth standards world to get the 'best of breed' standards working together.

Archetypes in the Real World

I've spent the past week in Ljubljana, Slovenia. Ian McNicoll (@ianmcnicoll) and I were been training clinicians about archetypes and clinical knowledge governance, ready for the launch of their national CKM. A highlight was a side trip to visit the state-of-the-art Paediatric Intensive Care Unit in Ljubljana. The electronic health record has been running there now for two years, with electronic processes gradually taking over. I was escorted by the clinician in charge of the ICU, Professor Kalan. The purpose of the visit – for him to meet someone who facilitated the archetypes used to run his EHR and for me to see our collective international archetype work implemented and used for real clinical purposes, largely under the expert clinical informatics guidance from Ian.

I was thrilled and a little taken aback, all at once. It is one thing to sit in an office researching clinical models and then to remotely collaborate with our international archetype community. But it is another to see real-time data being collected half a world away from home and knowing that we all had a small part in this, especially to support such critical care for a newborn baby. In the photo, above, you might just be able to spot a humidicrib surrounded by all of the equipment.

The majority of these archetypes were built by the international openEHR community for various projects and now utilised under the CC-BY-SA license by the EHR company to develop their clinical system. There are some local  archetypes in use as well – added for practical and pragmatic purposes - but these are very much in the minority. These same international archetypes are also being used in the EHR repository in the Northern Territory, Australia, and are underpinning their current work on shared antenatal care and hearing health programs. Soon this work is to be extended for renal failure and heart disease. And across more than 20 sites in Australia we have an infection control system that is using both archetypes and some that have been built specifically to support infection control activities and outbreak management. These shared archetypes are also underpinning work in UK, Brazil, Japan and Sweden.

Next week Ian and I are in Norway to support the Norwegian national archetype effort – training their clinicians and informaticians about archetypes, and especially governance principles at a national level.

There are now 5 CKMs in existence:

• the openEHR international CKM;
• Australia;
• City of Moscow;
• UK clinical community; and the brand new
• Slovenian eHealth program CKM.

The international CKM will continue to gather quality archetypes from all sources and coordinate international review and modelling activities. The intent is for this CKM to be the first port of call for those looking for an archetype.

The national-, organisation- or program-based CKMs will be focussed on supporting local health IT activities and will leverage the international pool of archetypes by a virtual 'read only' reference capability as well as hold specific local archetypes or modifications of the international archetypes that will support local implementation.

Above all the aim is to create high quality, computable, clinical content definitions that have been developed and ratified by the clinicians themselves. In turn this will support collection of good quality data that can be used for a variety of purposes – ranging from the health record itself; through querying and knowledge-based activities such as decision support; aggregation, analysis and research; and secondary use, including population health activities.

I have said it before, but let me say it again…

IT. IS. ALL. ABOUT. THE. DATA.

In the discussions about standards, the standardisation of data is usually missed.

Seeing this little baby in a humidicrib in amongst all of the 'machines that go beep' has invigorated me again.

Let's continue, and even accelerate, our collaboration on the development of archetypes. This will enable us to gather the data we need to provide the kind of healthcare our patients deserve.

Standards vs Standardisation

I read Enrico Coiera's recent blog post Are standards necessary? with interest since it coincided with my posting of Oil & Water: research and standards. It was the use of the word 'standardisation' that caught my attention, as I think of it quite differently in my day-to-day work.

The clinical modelling domain should never be locked down in a formal standards framework. However it still requires a formal approach that provides a stable foundation while still allowing enough flexibility to cater for the dynamic clinical knowledge domain which grows in breadth, depth and complexity every day. This softer type of artefact governance is what I describe as 'standardisation' - a collaborative process, involving strong and transparent governance, that doesn't lock down the published artefacts so that they can't evolve as clinical requirements are recognised.

Within the clinical models environment we have:

• a methodology that is evolving and becoming more robust;
• an intent to create a coherent and integrated set of clinical models with both minimal overlap and minimal gaps
• a process for governance, maintenance and distribution of the models; and
• an evolving methodology towards federation and sharing of models.

Wikipedia refers to 'Standardization' (or 'Standardisation') as "the process of developing and implementing technical standards."

Merriam Webster's view is:

:  to compare with a standard; and

:  to bring into conformity with a standard

Whereas my experience of standardisation is with the clinical models ecosystem as a more organic, 'middle in' or grass-roots collaborative process which fits this other Merriam Webster definition more appropriately:

:  to change (things) so that they are similar and consistent and agree with rules about what is proper and acceptable.

It's all about the semantics.

So maybe I'm wrong. Maybe we are creating a form of standard with each clinical model after all, just with rules that differ to those usually found within a standards development organisation.

Oil & water: research & standards

The world of clinical modelling is exciting, relatively new and most definitely evolving. I have been modelling archetypes for over 8 years, yet each archetype presents a new challenge and often the need to apply my previous experience and clinical knowledge in order to tease out the best way to represent the clinical data. I am still learning from each archetype. And we are still definitely in the very early phases of understanding the requirements for appropriate governance and quality assurance. If I had been able to discern and document the 'recipe', then I would be the author of a best-selling 'archetype cookbook' by now. Unfortunately it is just not that easy. This is not a mature area of knowledge. I think clinical knowledge modellers are predominantly still researchers.

In around 2009 a new work item around Detailed Clinical Models was proposed within ISO. I was nominated as an expert. I tried to contribute. Originally it was targeting publication as an International Standard but this was reduced to an International Specification in mid-development, following ballot feedback from national member bodies. This work has had a somewhat tortuous gestation, but only last week the DCM specification has finally been approved for publication - likely to be available in early 2014. Unfortunately I don't think that it represents a common, much less consensus, view that represents the broad clinical modelling environment. I am neither pleased nor proud of the result.

From my point of view, development of an International Specification (much less the original International Standard) has been a very large step too far, way too fast. It will not be reviewed or revised for a number of years and so, on publication next year, the content will be locked down for a relatively long period of time, whilst the knowledge domain continues to grown and evolve.

Don't misunderstand me - I'm not knocking the standards development process. Where there are well established processes and a chance of consensus amongst parties being achieved we have a great starting point for a standard, and the potential for ongoing engagement and refinement into the future. But...

A standards organisation is NOT the place to conduct research. It is like oil and water - they should be clearly separated. A standards development organisation is a place to consolidate and formalise well established knowledge and/or processes.

Personally, I think it would have been much more valuable first step to investigate and publish a simple ISO Technical Report on the current clinical modelling environment. Who is modelling? What is their approach? What can we learn from each approach that can be shared with others?

Way back in 2011 I started to pull together a list of those we knew to be working in this area, then shared it via Google Docs. I see that others have continued to contribute to this public document. I'm not proposing it as a comparable output, but I would love to see this further developed so the clinical modelling community might enhance and facilitate collaboration and discussion, publish research findings, and propose (and test) approaches for best practice.

The time for formal specifications and standards in the clinical knowledge domain will come.  But that time will be when the modelling community have established a mature domain, and have enough experience to determine what 'best practice' means in our clinical knowledge environment.

Watch out for the publication of prEN/ISO/DTS 13972-2, Health informatics - Detailed clinical models, characteristics and processes. It will be interesting to observe how it is taken up and used by the modelling community. Perhaps I will be proven wrong.

With thanks to Thomas Beale (@wolands_cat) for the original insight into why I found the 13972 process so frustrating - that we are indeed still conducting research!

We need the domain experts!

It certainly helps to be a clinician, although recent work on development of clinical content specifications for a Hearing Health application has taken me further into modelling for the range of audiometry, 226Hz and high frequency tympanometry, audiology speech testing, and hearing screening than I’d ever imagined. Modelling the raw data capture (or downloaded from devices) for these tests is really quite simple, but enabling the complexity of different states, events and protocols that reflect audiological practice has been much more complex than I anticipated. I attempted to model these some years ago, based on my (obviously rather poor) research on the web at the time. Take a look at my meagre effort to build the original archetype for Audiogram Result (as built by a GP who has never performed an audiogram).

See the full detail here - http://www.openehr.org/ckm/#showArchetype_1013.1.44_1

And the most recent archetype as designed and verified by practising grassroots Audiologists… I didn’t even get the name of the concept correct!

See the full detail here - http://dcm.nehta.org.au/ckm/#showArchetype_1013.1.1097

Identifying domain experts for the development and then collaboration on verification/validation of each type of archetype/template is absolutely critical for success.

Engaging clinicians: building EHR specifications

There is a methodology that is pragmatically evolving from my experience in openEHR clinical modelling work over the past few years. It has developed in a rather ad hoc way, and totally in response to working directly with clinicians. The simplicity and apparent effectiveness – both for me and the clinicians involved - continues to surprise me each time I use it. The clinical content specifications for specialised health records and care plans that we are building are being developed with a sequence of expert input and clinical verification:

1. Identifying the clinical requirements and business rules in conjunction with a selected initial domain expert group;
2. Broader abstract verification of the notion of ‘maximal data set’ for ‘universal use case’ during formal archetype review cycles;
3. Contextual validation during template review by ‘on-the-ground’ clinicians; and finally, although to a lesser degree,
4. Validation during mapping and migration of legacy data.

With each project I am refining this process. Starting off a project with face-to-face meetings has been a ‘no brainer’ – after all, it takes a while for everyone to understand the get the idea of what we are doing. However after initial workshops, pretty much everything else can be done via web conference, online collaboration via CKM and email.

I find the initial workshops are usually greatly satisfying. Within hours we can be creating two outputs – a mind map that reflects the clinicians evolving conversation about their requirements and, in parallel, an equally agile template of clinical content specifications that can be verified by the clinicians in real time.

The mind map is displayed on a shared screen or via a data projector and acts as a living document, evolving as we talk through the clinical requirements, and identify the complexities, dependencies and relationships of all the components. The final mind map may be surprisingly different to how it started, and at the end of the conversation, the clinicians can verify that what they’ve said if accurately reflected in the mind map. It is an open source tool, so we can also share this around after the workshop for further comments.

Most recently I have begun building a template on the fly during the workshop, using any existing archetypes that are available, and identifying gaps or the need for new archetypes on the mind map as we go. In this way we are actually building the content specification in front of the clinicians as well. They get an understanding of how the abstract discussion will actually shape the resulting EHR content and they can verify it as we gradually pull it together. The domain experts are immediately equipped to answer the question: “Does this specification match what you have been telling me you do in practice?”

This methodology seems to bring the clinicians along with us on the clinical modelling journey, and most are able to understand at least some of the implications of some of our requirements discussions and, in particular, the ‘shape’ of the data that we can collect. It is a process seems to suit the thinking process of many clinicians and the overwhelmingly consistent feedback from recent workshops is that they have all actually enjoyed the experience and want to know what are the next steps for them to be involved. So that’s certainly a winner.

And the funders/jurisdictions are anecdotally confirming for me that they are finding that this approach is supporting higher quality specifications in a much shorter time frame.

For example, at a project kickoff workshop for a new project recently, in two days we:

• developed a series of mind maps capturing a consensus view of the clinical requirements and business processes;
• identified all the archetypes required for the entire project, including those that existed and were ‘fit for use’, those that needed some extension to meet requirements and new archetypes that needed to be created;
• identified sources of information or mind mapped the requirements for each new archetype identified; and
• built 3 templates comprising all of the existing archetypes available from a number of sources – the NEHTA CKM http://dcm.nehta.org.au/ckm/, the openEHR international CKM http://www.openehr.org/ckm/ and local drafts that I had on my own computer. For a number of the new archetypes we also collectively identified source information that would inform or be the basis for the archetype development.

All of this described above took 8 medical practitioners clinicians away from their everyday practice for only 1-2 days, each according to their availability. Yet it provided the foundation for development of a new clinical application.

Then I go home. Next steps are to refine the mind map, modify/update/specialise any archetypes for which we have identified new requirements and build the new ones. And in parallel start the collaborative process through a CKM project to ensure that existing and modified archetypes are ‘fit for (our project’s) purpose’, and to upload and initiate reviews on the new draft archetypes.

All work to progress these archetypes to maturity (ie aiming for clinical consensus) and then validate the templates as ready for handover to the implementers can be done online, asynchronously and at a time convenient to the clinicians work/life balance!

I live over 2000 kilometres away from these clinicians. Yet the combination of web conference and CKM enables us to operate as an ongoing collaborative team. It seems to be working well at the moment... No doubt I'll continue to learn how to do it better.

The Archetype Journey...

I'm surprised to realise I've been building archetypes for over 7 years. It honestly doesn't feel that long. It still feels like we are in the relatively early days of understanding how to model clinical archetypes, to validate them and to govern them. I am learning more with each archetype I build. They are definitely getting better and the process more refined. But we aren't there yet. We have a ways to go! Let me try to share some idea of the challenges and complexities I see…

We can build all kinds of archetypes for different purposes.

There are the ones we just want to use for our own project or purpose, to be used in splendid isolation. Yes, anyone can build an archetype for any reason. Easy as. No design constraints, no collaboration, just whatever you want to model and as large or complex as you like.

But if you want to build them so that they will be re-used and shared, then a whole different approach is required. Each archetype needs to fit with the others around it, to complement but not duplicate or overlap; to be of the same granularity; to be consistent with the way similar concepts are modelled; to have the same principles regarding the level of detail modelled; the same approach to defining scope; and of course the same approach to defining a clinical concept versus a data element or group of data elements… The list goes on.

Some archetypes are straightforward to design and build, for example all the very prescriptive and well recognised scales like the Braden Scale or Glasgow Coma Scale. These are the 'no brainers' of clinical modelling.

Some are harder and more abstract, such as those underpinning a clinical decision support system of orders and activities to ensure that care plans are carried out, clinical outcomes achieved and patients don't 'fall through the cracks' from transitions of care.

Then there are the repositories of archetypes that are intended to work as single, cohesive pool of models – each archetype for a single clinical concept that all sits closely aligned to the next one, but minimising any duplication or overlap.

That is a massive coordination task, and one that I underestimated hugely when we embarked on the development of the openEHR Clinical Knowledge Manager, and especially more recently, the really active development and coordination required to manage the model development, collaboration and management process within the Australian CKM – where the national eHealth program and jurisdictions are working within the same domain of models, developing new ones for specific purposes and re-using common, shared models for different use cases and clinical contexts.

The archetype ecosystems are hard, numbers of archetypes that need to work together intimately and precisely to enable the accurate and safe modelling of clinical data. Physical examination is the perfect example that has been weighing on my mind now for some time. I've dabbled with small parts of this over the years, as specific projects needed to model a small part of the physical exam here and there. My initial focus was on modelling generic patterns for inspection, palpation, auscultation and percussion – four well identified pillars of the art of clinical examination. If you take a look at the Inspection archetype clinicians will recognise the kind of pattern that we were taught in First Year of our Medical or Nursing degrees. And I built huge mind maps to try to anticipate how the basic generic pattern could be specialised or adapted for use in all aspects of recording the inspection component of clinical examination.Over time, I have convinced myself that this would not work, and so the ongoing dilemma was how to approach it to create a standardised, yet extraordinarily flexible solution.

Consider the dilemma of modelling physical examination. How can we capture the fractal nature of physical examination? How can we represent the art of every clinician's practice in standardised archetypes? We need models that can be standardised, yet we also need to be able to respond to the massive variability in the requirements and approach of each and every clinician. Each profession will record the same concept in different levels of detail, and often in a slightly different context. Each specialty will record different combinations of details. Specialists need all the detail; generalists only want to record the bare basics, unless they find something significant in which case they want to drill down to the n^th degree. And don't forget the ability to just quickly note 'NAD' as you fly past to the next part of the examination; for rheumatologists to record a homunculus; for the requirement for addition of photos or annotated diagrams! Ha – modelling physical examination IS NOT SIMPLE!

I think I might have finally broken the back of the physical examination modelling dilemma just this week. Seven years after starting this journey, with all this modelling experience behind me! The one sure thing I have learned – a realisation of how much we don't know. Don't let anyone tell you it is easy or we know enough. IMO we aren't ready to publish standards or even specifications about this work, yet. But we are making good, sound, robust progress. We can start to document our experience and sound principles.

This new domain of clinical knowledge management is complex; nobody should be saying we have it sorted...

Archetype Re-use

Last Thursday & Friday @hughleslie and I presented a two day training course on openEHR clinical modelling. Introductory training typically starts with a day to provide an overview – the "what, why, how" about openEHR, a demo of the clinical modelling methodology and tooling, followed by setting the context about where and how it is being used around the world. Day Two is usually aimed at putting away the theoretical powerpoints and getting everyone involved - hands on modelling. At the end of Day One I asked the trainees to select something they will need to model in coming months and set it as our challenge for the next day. We talked about the possibility health or discharge summaries – that's pretty easy as we largely have the quite mature content for these and other continuity of care documents. What they actually sent through was an Antineoplastic Drug Administration Checklist, a Chemotherapy Ambulatory Care Nursing Intervention and Antineoplastic Drug Patient Assessment Tool! Sounded rather daunting! Although all very relevant to this group and the content they will have to create for the new oncology EHR they are building.

Perusing the Drug Checklist ifrst - it was easily apparent it going to need template comprising mostly ACTION archetypes but it meant starting with some fairly advanced modelling which wasn't the intent as an initial learning exercise.. The Patient Assessment Tool, primarily a checklist, had its own tricky issues about what to persist sensibly in an EHR. So we decided to leave these two for Day Three or Four or..!

So our practical modelling task was to represent the Chemotherapy Ambulatory Care Nursing Intervention form. The form had been sourced from another hospital as an example of an existing form and the initial part of the analysis involved working out the intent of the form .

What I've found over years is that we as human beings are very forgiving when it comes to filling out forms – no matter how bad they are, clinical staff still endeavour to fill them out as best they can, and usually do a pretty amazing job. How successful this is from a data point of view, is a matter for further debate and investigation, I guess. There is no doubt we have to do a better job when we try to represent these forms in electronic format.

We also discussed that this modelling and design process was an opportunity to streamline and refine workflow and records rather than perpetuating outmoded or inappropriate or plain wrong ways of doing things.

So, an outline of the openEHR modelling methodology as we used it:

1. Mind map the domain – identify the scope and level of detail required for modelling (in this case, representing just one paper form)
2. Identify:
   1. existing archetypes ready for re-use;
   2. existing archetypes requiring modification or specialisation; and
   3. new archetypes needing development
3. Specialise existing archetypes – in this case COMPOSITION.encounter to COMPOSITION.encounter-chemo with the addition of the Protocol/Cycle/Day of Cycle to the context
4. Modify existing archetypes – in this case we identified a new requirement for a SLOT to contain CTCAE archetypes (identical to the SLOT added to the EVALUATION.problem_diagnosis archetype for the same purpose). Now in a formal operational sense, we should specialise (and thus validly extend) the archetype for our local use, and submit a request to the governing body for our additional requirements to be added to the governed archetype as a backwards compatible revision.
5. Build new archetypes – in this case, an OBSERVATION for recording the state of the inserted intravenous access device. Don't take too much notice of the content – we didn't nail this content as correct by any means, but it was enough for use as an exercise to understand how to transfer our collective mind map thoughts directly to the Archetype Editor.
6. Build the template.

So by the end of the second day, the trainee modellers had worked through a real-life use-case including extended discussions about how to approach and analyse the data, and with their own hands were using the clinical modelling tooling to modify the existing, and create new, archetypes to suit their specific clinical purpose.

What surprised me, even after all this time and experience, was that even in a relatively 'new' domain, we already had the bulk of the archetypes defined and available in the NEHTA CKM. It just underlines the fact that standardised and clinically verified core clinical content can be re-used effectively time and time again in multiple clinical contexts.The only area in our modelling that was missing, in terms of content, was how to represent the nurses assessment of the IV device before administering chemo and that was not oncology specific but will be a universal nursing activity in any specialty or domain.

So what were we able to re-use from the NEHTA CKM?

• COMPOSITION.encounter
• EVALUATION.adverse_reaction – one instance per adverse reaction included in a adverse reaction list
• EVALUATION.clinical_synopsis
• EVALUATION.problem_diagnosis – one instance per diagnosis included in a problem list
• INSTRUCTION.request-referral – one instance per referral requested
• ACTION.health_education
• ACTION.procedure – with two instances for different purposes

…and now that we have a use-case we could consider requesting adding the following from the openEHR CKM to the NEHTA instance:

• OBSERVATION.story
• CLUSTER.symptom – with multiple instances for each symptom identified

And the major benefit from this methodology is that each archetype is freely available for use and re-use from a tightly governed library of models. This openEHR approach has been designed to specifically counter the traditional EHR development of locked-in, proprietary vendor data. An example of this problem is well explained in a timely and recent blog - The Stockholm Syndrome and EMRs! It is well worth a read. Increasingly, although not so obvious in the US, there is an increasing momentum and shift towards approaches that avoid health data lock-in and instead enable health information to be preserved, exchanged, aggregated, integrated and analysed in an open and non-proprietary format - this is liquid data; data that can flow.

The Times, They Are a-Changin’...

Channelling Bob Dylan? Not quite! But it is interesting to see some emerging HL7 and openEHR activity, at least in this little part of the world – Australia and New Zealand :) Maybe this is a model for the rest of the world - at least food for thought!

For too many long years there appears to have been a palpable barrier between the HL7 and openEHR communities. Some individuals have managed to bridge it, but there has definitely been a reluctance to engage at organisational level. It stems from before my time; I suspect vocal personalities with strong, diverging opinions were at the root. To some, it is a little like a religious argument – where "only my way is the right way"!

Be that as it may - the barrier appears to be softening and became evident to me for the first time back in January last year as I attended the HL7 meeting in Sydney. A full day openEHR workshop was presented by a diverse group of Australian companies plus NEHTA experts; Bob Dolin in attendance, amongst others. Keith Boone tweeted his initial impression of the openEHR approach after I demonstrated our tooling and then blogged about it. My thoughts were captured in my Adventures of a clinician in HL7 post.

Fast forward to 2012…

You may have seen some announcements from New Zealand. Firstly, publication in April of the Health Information Exchange Architecture Building Blocks where they specified "2.3.2 The data definitions of the Content Model shall be formulated as openEHR archetypes" within the "10040.2 HIE Content Model, a framework for the creation of a common set of logical data definitions" document.

And secondly: HL7 New Zealand and the openEHR Foundation signed a Statement of Collaboration - also announced April 2012. Now there's a headline that might have been a surprise to many – HL7 NZ & openEHR clearly intending to work closely together!

Only last Thursday Hugh Leslie & I participated in a seminar, "Bringing the Electronic Health Record to Life," organised by HL7 NZ, Health Informatics New Zealand (HINZ) and the University of Auckland. Prof Ed Hammond, 'the father of HL7', keynoted the meeting: "EHR - The Killer App". In the afternoon mini-tutorials, David Hay presented on FHIR, and Hugh, I and Koray Atalag presented a little about our openEHR work, including clinical knowledge governance and clinician engagement. Koray (a HL7 NZ member and openEHR localisation program coordinator) announced within the meeting that HL7 NZ is the likely organisation to auspice a NZ chapter of openEHR. Now that definitely has to start to change the openEHR/HL7 dynamic somewhat, even if HL7 NZ is a relatively small international affiliate :). The HL7 NZ leadership, to their absolute credit, are certainly not being constrained by any traditional 'turf wars'.

The following day, last Friday, Hugh and I presented a full day workshop on openEHR, again sponsored by HL7 NZ, HINZ and the University of Auckland. As I understand it, this was the first opportunity for the openEHR approach to be socialised with the broader healthIT community in NZ; about 25 in attendance including members of the HL7 NZ Board, vendors, and regional and HealthIT Board reps. The focus was on how openEHR could support the creation of a range of technical artefacts to meet NZ's requirements for CDA messaging (and beyond), generated from a cohesive and governed pool of clinical content models.

Interestingly we had a surprise attendee for the workshop – Ed Hammond joined us for the whole day. I won't presume to guess what Ed has taken away from the day, although he did offer up a comment to the group about the value of exploring use of archetype content directly within CDA.

Post workshop one of the attendees tweeted:

"At #HINZ #openEHR talks last 2 days. openEHR is a fantastic foundation for practical action. Left knowing steps I will take. How cools that!"

And of course, there is an HL7 AU meeting in Sydney early next week entitled "FHIR?  CIMI? openEHR? What's the Future of eHealth & mHealth Standards?" The agenda:

• Keynote: Ed Hammond (again) – "FHIR, CIMI and openEHR - What's the Future for eHealth Standards?". [It will be very interesting to hear his opinion after last week's openEHR exposure.]
• Grahame Grieve: "FHIR – What is it? Why has it suddenly become so popular?"
• Hugh Leslie: "Recent developments in openEHR and CDA", and
• I'll be reporting on the CIMI project.

It would be an interesting day to be a fly on the wall! 2 HL7-ers and 2 openEHR-ers addressing an HL7 meeting - all exploring alternatives to the current approaches!

So, keep your eye on the space where HL7 intersects with openEHR – might be some interesting developments.

_______________________

Within the openEHR community, and definitely within Ocean Informatics where I work, we are certainly finding that significant interest is being certainly generated from many sources about the process of using standardised and governed openEHR clinical content as a means to generate range of technical artefacts, including CDA. The New Zealand national interest and activity is evident, as outlined above. And in addition:

• In Australia, NEHTA has piloted the use of clinician-reviewed archetypes from the NEHTA Clinical Knowledge Manager as the start point for generating a number of the PCEHR technical specifications. This work is ongoing and being extended.
• CIMI, the initiative that grew out of HL7 but is now independent, is seeking to develop an internationally agreed approach to clinical modelling and generation of multiple technical outputs. It has already agreed to utilise openEHR ADL 1.5 as its modelling formalism and is using the openEHR Reference Model as the starting point for developing a CIMI Reference Model. We watch this progress with interest.
• And Brazil's national program has recently reconfirmed its intention to commence using openEHR.

Whether the final solution is openEHR or CIMI or even something else, I think that the advent of standardised clinical models as the common starting point for generation of a range of technical outputs is upon us. Ignore it at your peril. And specifically, I would suggest that HL7 International should be considering very seriously how to embrace this new approach.

Sticking with the quasi-gospel theme, maybe it is now a bit more like Curtis Mayfield's "People Get Ready":

People get ready There's a train a-coming You don't need no baggage Just a-get on board

Let's leave our baggage behind, get on the 'train' together to collaborate and create something that transcends any health IT domain turf war! Don't get left behind...

CIMI... one of many crossroads

Grahame Grieve posted CIMI at the Crossroads recently. I can't disagree with a lot of the content, but maybe I'm a bit more of an optimist as I draw some slightly different conclusions. Grahame is totally right about what it has achieved so far:

• a significant membership roll that has never been achieved before
• a significant agreement of an initial approach to clinical models - a primary formalism of ADL 1.5/AOM with a commitment to support transformation to isosemantic UML models in a spirit of inclusivity and harmonisation.

And as he points out, the notion that the modelling methodology was chosen independently of the Reference Model is somewhat disconcerting.

"...the decision to choose ADL/AOM as the methodology, while deferring the choice of reference model. While I understood the political reality of this decision, choosing an existing methodology (ADL/AOM) but not the openEHR reference model committed CIMI to building at least a new tooling chain, a new community, and possibly a new reference model.

The cost of this is high; so high that the opportunity created by the foundation of CIMI may likely founder if we see another attempt to reinvent the health IT wheel, yet again.

There are many opinions, and everyone at the CIMI table has their own bias, history, experience. Organisational and personal investment in each existing solutions are high. No one wants to throw away their efforts and 'start again'; everyone wants their work to be the successful and sustained.

The CIMI community do need to make an objective decision if it is to move forward. It may not be result which wins a popularity contest. It is very likely that some members will walks away and keep working as they always have; maybe intending to return when a more mature solution is on offer.

In his paragraph on the pros and cons of openEHR, Grahame very eloquently states:

This is the first choice: pick the least worst established clinical modelling paradigm.

:)

"Least worst" - Thanks Grahame! You could turn that around: the 'best' available so far, where there is no perfect solution!

But it's not a bad principle - to take the least worst and make it better!

The chair of the openEHR board, Sam Heard proposed the following to the openEHR community back in October 2011:

“If the CIMI group chooses to use ADL as the formalism then the openEHR community is prepared to explore the Foundation governance arrangements with the CIMI group and align the two efforts using the structures that are mutually agreed.

Changes to ADL and the openEHR Reference Model may be part of the process to meet the collective needs, and alignment of the shared RM and a reviewed RM for ISO 13606 would also be a major goal. ADL 1.5 would be submitted to ISO as part of this alignment.”

Seems sensible to me - start with a robust candidate and modify/enhance it to meet the collective needs. The latest version of the openEHR RM is clearly one candidate. It has evolved significantly from the 2005 version which forms the basis of ISO 13606. Given that ISO 13606 (parts 1-5) is due for revision this year, perhaps we have a great opportunity for harmonisation. The openEHR community is already starting to develop a proposal for the revision, but a greater achievement would be to align all of these efforts into a new 13606/openEHR/CIMI specification.

This is a difficult task that we are trying to solve. We know that because it has not been solved before.

This is definitely not the first crossroad that CIMI has encountered - don't underestimate the effort that has brought the group to this point - and it will definitely not be the last. What will determine success is keeping the end goal front and centre in CIMI's decision-making; cutting ruthlessly through the political and personal agendas; putting pragmatism ahead of perfection; and a willingness to compromise in order to move forward.

It may not be possible. It could be a hell of a ride. I still think it has the potential make a hell of a difference.

The ultimate PHR?

I've been interested in the notion of a Personal Health Record for a long time. I was involved in the development of HotHealth, which launched at the end of 2000, a not-so-auspicious year, given the dot com crash! By the time HotHealth was completed , all the potential competitors identified in the pre-market environmental scan were defunct. It certainly wasn't easy to get any traction for HotHealth take-up and yet only recently it has been retired. For a couple of years it was successfully used at the Royal Children's Hospital, cut down and re-branded as BetterDiabetes to support teenagers self-manage their diabetes and communicate with their clinicians, but it wasn't sustained.

This is not an uncommon story for PHRs. It is somewhat comforting to see that the course of those such HealthVault and GoogleHealth have also not been smooth and fabulously successful :-)

Why is the PHR so hard?

In recent years I participated in the development of the ISO Technical Report 14292:2012: Personal health records -- Definition, scope and context. In this my major contribution seemed to be introducing the idea of a health information continuum.

However in the past year or so, my notion of an ideal PHR has moved on a little further again. It has arisen on the premise of a health record platform in which standardised health information persists independently of any one software application and can be accessed by any compliant applications, whether consumer- or clinician-focused. And the record of health information can be contributed to by any number of compliant systems - whether a clinical system, a PHR or smartphone app. The focus is on the data, the health record itself; not the applications. You will have seen a number of my previous posts, including here & here!

So, in this kind of new health data utopia, imagine if all my weights were automatically uploaded to my Weight app on my smartphone wirelessly each morning. Over time I could graph this and track my BMI etc. Useful stuff, and this can be done now - but only into dead-end silos of data within a given app.

And what if a new fandangled weight management application came along that I liked better - perhaps it provided more support to help me lose weight. And I want to lose weight. So I add the new app to my smartphone and, hey presto, it can immediately access all my previous weights - all because the data structure in both apps is identical. Thus the data can be unambiguously understood and computed upon within the second app without any data manipulation. Pretty cool. No more data silos; no more data loss. Simply delete the first app from the system, and elect to keep the data within my smartphone health record.

And as I add apps that suit my lifestyle, health needs, and fitness goals etc, I'm gradually accumulating important health information that is probably not available anywhere else. And consider that only I actually know what medicines I'm taking, including over the counter and herbals. The notion of a current medication list is really not in the remit of any clinician, but the motivated consumer! And so if I add an app to start to manage my medications or immunisations this data could be also used across in yet another compliant chronic disease support app for my diabetes or asthma or...

I can gradually build up a record of health information that is useful to me to manage my health, and that is also potentially useful to share with my healthcare providers.

Do you see the difference to current PHR systems?

I can choose apps that are 'best of breed' and applicable to my need or interest.

I'm not locked in to any one app, a mega app that contains stuff I don't want and will never use, with all the overheads and lack of flexibility.

I can 'plug & play' apps into my health record, able to change my mind if I find features, a user interface or workflow that I like better.

And yet the data remains ready for future use and potentially for sharing with my healthcare providers, if and when I choose. How cool is that?

Keep in mind that if those data structures were the same as being used by my clinician systems, then there is also potential for me to receive data from my clinicians and incorporate it into my PHR; similarly there is also potential for me to send data to my clinician and give them the choice of incorporating this into their systems - maybe my blood glucose records directly obtained from my glucometer, my weight measurements, etc. Maybe, one day, even MY current medicine list!

In this proposed flexible data environment we are avoiding the 'one size fits all', behemoth approach, which doesn't seem to have worked well in many situations, both clinical systems or personal health records. Best of all the data is preserved in the non-proprietary, shared format - the beginnings of a universal health record or, at least, a health record platform fully supporting data exchange.

What do you think?

"We have the capability!"

We have had the technology for a purpose-built openEHR-compliant 'plug & play' platform for some time; standalone applications have been built, but just recently it appears that the practical reality of an multi-application platform is also about to happen. "We have the technology. We have the capability..." Stay tuned.

...Reminds me of my 1970's hero, Steve Austin, the Six Million Dollar Man. With apologies to Steve:

"We have the technology. We have the capability to make the world's first universal health platform. openEHR will be that platform. Better than ever before. Robust health data...application independent...semantically interoperable!"

[youtube http://www.youtube.com/watch?v=K7zNY0I5JNI&w=480&h=360]