Going on a Banksy Hunt...

I spent a total of 19 weeks living away from family in London during 2007. Much of that time was spent by myself, and I ended up walking and exploring - the main task being to locate Banksy pieces. It really started just as something to do to keep me active and to soak up the essence of a different city. Armed with a Banksy Walking Guide that I bought on eBay, I set out on a number of days and walked for miles, finding many stencils around the East End. Some had been buffed; some were hidden behind fences; some just sitting there just like the picture in the book.

Oddly, you could even recognise others who were doing a similar thing and conversations started as you pointed someone to an obscure Banksy that they had missed - a temporary camaraderie in a strange city!

Subsequently, I have also found a few Banksy stencils locally in Melbourne, funnily most are just in the streets around my home and on shop fronts that I walk past each day.

Today I've just posted the last of my Banksy photos to Flickr - Banksy's skeleton car on display behind the Old Truman Brewery back in November 2007 - not sure about it's current status. You can see all my Banksy collection in an online set, Going on a Banksy Hunt if you are so inclined.

It has been an interesting exercise  to seek out and learn a little about Banksy. Clearly there are many more Banksy streetart photos that are chronicled on Flickr and other online sites, and many people that know much more about Banksy than me, but it has been an interesting journey.  So just saying...

Fractal Electronic Health Records?

Clinicians record their findings and conclusions remarkably efficiently on paper, recording the contextual variations succinctly and in a way that other clinicians can understand. Getting computers to do the same thing – to enable clinicians to record simply in the normal circumstances, but be able to cope with the complex and detailed where it is critically needed - is not a trivial task. Ensuring that a user interface reflects a clinician's work flow and captures the evolving requirements in a clinical consultation is extremely complex. Obviously computers are not as flexible as a human brain; they can only record what is pre-ordained in their programming. We clinicians should expect our electronic health record (EHR) applications to do be able to support our recording requirements and work flow however, in reality, there are very few clinical systems that do this well.

Identifying recurring patterns in clinical practice help to ensure our EHRs can record health information effectively. When we look closely, clinical medicine is fractal in nature.

What do we have to record, display, query and exchange in our EHRs? Lots of measurements such as Pulse, Temperature, Blood gases, Apgar Score, Height, and Weight are pretty straightforward. Those screens are a breeze - type in a couple of numbers and hit 'Save'. Evaluations, diagnoses and assessments are also pretty uncomplicated.

However it starts to get much more complicated when we start to explore history-taking and examination findings - where the bulk of the 'art of medicine' takes place.

Let's think of the evolving nature of a typical clinical consultation. It would be so nice if each patient walked into my consulting room with a single, neatly packaged problem for me to solve, but this is not the norm. In fact the majority arrive with the dreaded 'shopping list or, worse still, with multiple problems that are gradually revealed one by one throughout the consultation. So while computers will capture a linear work flow really well, the typical patient consultation is anything but linear.

But each of these problems will likely be recorded in a common pattern - reason for encounter, history of presenting complaint, systematic questioning, examination, differential diagnosis, investigations, diagnosis, management plan and follow-up.

Consider a simple skin examination. The clinician inspects the patient's back and finds an abnormality - a dark, warty lesion. They record its location, dimensions, shape, regularity, surrounding skin etc, and - oh oh - that there is an area within it with increased pigmentation. Then they focus on the hyperpigmented area - recording location, dimensions, shape, surrounding tissue etc. Then they take a photo for future reference and pull out the dermatoscope - recording yet again the location, dimensions, shape, surrounding tissue etc. There are repeating patterns identified here at increasing levels of granularity.

Recently I've been modeling the examination of the hand. Easy, I thought... at first. OK, we’ll use the general clinical principles to record inspection and palpation of the hand as a whole, including specific hand-related items such as presence of Duypuytren’s contracture, wasting of lumbricals plus circulation, sensation (pinprick, temperature, vibration etc), and strength. Then we need to potentially be able to examine in detail:

• per named finger – again inspection and palpation per digit, plus circulation, sensation, movement of each joint on that finger
• per named nerve eg median nerve distribution
• per named tendon
• per named joint – inspection, palpation and movement of each joint
• per named bone - palpation

And if we found something on inspection of the finger such as a nodule, we need to be able to inspect and palpate the nodule. And if there was a pigmented part of the nodule we'd be documenting it in a similar way to the wart on the back - inspect the pigmentation in detail, including an image of it for future reference. These are incredibly complex recording requirements.

Which way we view or prioritize these requirements will depend on the patient context and the expertise of the examiner. For example, recording needs for a hand examination by a General Practitioner will differ from that of a Rheumatologist or an Orthopaedic Surgeon. Consider also the plastic surgeon about to take a patient to surgery to repair a severed finger will absolutely need to be able to record a detailed breadth and depth of not only the hand and the finger but the digital vessels and nerves that will need their expert attention.

Do you get a sense of the fractal nature of medicine? Repeating patterns in the way we record health information:

• revealed as we repeat the work flow of a typical history and examination process; and
• revealed as we record our findings in more and more detail.

Content modeling for EHRs needs to reflect the fractal nature of clinical medicine accurately, both coarse and fine levels of granularity, and ensuring that the data capture is ‘fit for clinical purpose’.

Inspired by @samheard, as usual;-)

The unexpected beauty of a REAL book

Following my visit to the US in October last year, I came home to Australia bearing the latest Kindle very proudly. We are definitely a family that gets excited about gadgets, and this was one of the first international Kindles available - delivered straight to my Raleigh hotel room the day after release on Amazon.com.

I read a couple of books on it before Christmas, but the experience was unfortunately a little underwhelming; the conclusion being that it was slower and much more clunky than the much beloved iPhone. Without realizing it I had gradually been abandoning print for screen.

Then, for Christmas, I received a most beautiful limited edition, hardcover of the latest book by one of my favorite authors.

The cover was beautifully decorated - none of this cheap old slipcover nonsense - and there was one of those semi-transparent pages adjacent to the title page. Have you ever actually owned a book with one of those?

The final, perfect touch - my numbered book was signed by the author.

Now the story was every bit as good as I'd hoped and I lay in bed reading for indulgent hours - a treat I hadn't pursued for some time.

To my surprise I still occasionally find myself reminiscing about that sweet reading experience. Holding that beautifully crafted book in my hands was an unexpectedly sensual experience and it still sends a little shiver down my spine;-)

Web2.0 Clinicians – building clinical knowledge resources

After 5 collaborative review rounds by 18 clinicians and informaticians from 9 countries, today I have published the Clinical Synopsis archetype on the openEHR Clinical Knowledge Manager. The Clinical Knowledge Manager (CKM) is an online community putting the Web2.0 paradigm into practice for EHR development. From the CKM wiki...

"The openEHR Clinical Knowledge Manager is an international, online clinical knowledge resource – www.openEHR.org/knowledge. It has gathered an active Web 2.0 community of interested and motivated individuals focused on furthering an open and international approach to clinical informatics – an application- and message-independent lingua franca for sharing health information between individuals, clinicians and organisations; between applications, and across regional and national borders. All contributions to CKM is on a voluntary basis, and all CKM content is open source and freely available under a Creative Commons licence.

The core openEHR building block/knowledge artefact is known as an archetype. To a clinician an archetype is a computable definition of single, discrete clinical concept; yet to a software engineer it is a computable expression of a domain content model in the form of structured constraint statements, and based on a reference model. Both definitions are describing the same computable knowledge artefact and in practice, clinicians drive the development of the archetype and the engineers implement them in software."

CKM status

At time of writing the registered CKM community numbers 433 individuals from 53 countries, with 184 volunteering to participate in archetype reviews and 50 volunteering to translate archetypes once the content is published. (Current user stats are here). It comprises a range of clinicians, health informaticians, software engineers, terminologists, researchers, students, policy makers, and administrators – and is open to anyone to join and participate. No consumers yet, although the models are designed to be used in PHRs as well. You can self-register by clicking on the link in the top right of the CKM screen.

There are over 250 archetypes currently available - most are still draft; some that are currently within the Team Review process; and a small number that have achieved consensus during Team Review of the clinical content and have been published. Others are in development in various projects and national programs from around the world and many will gradually be submitted into the CKM for international review and publication.

The priorities and focus of the current openEHR CKM archetype reviews are on achieving agreement and consensus on the 10 key archetypes that would support healthcare provision in a typical crisis situation.  Effectively these archetypes would contain clinical content that the openEHR community regard as the most important components of any Emergency Summary – the '10 archetypes that could save a life'!

Not surprisingly progress has been steady but a little slower than anticipated. Remember, all participants volunteer, including the editors and this is a relatively new activity. As such we are continually learning and refining the CKM tool and our processes. Most importantly, we are seeking to align the identified critical archetypes with the work that is being done in isolation by many standards groups and national bodies. Under review at the moment are probably the two hardest on which to achieve consensus – Adverse Reactions and the Problem/Diagnosis family. Medication orders is about to commence the review process.

Interestingly, the Adverse Reaction review is currently paused because following it's first review round, where it became clear that Adverse Reaction needs to be considered as part of a larger picture related to the modeling of all safety-related concepts. At present I am endeavoring to tease out the differences and overlap in theory and practice related to Adverse Events; Adverse Reactions; Adverse Drug Reactions; Warnings; Alerts; and Risk plus Adverse Event reporting to statutory authorities – it's complex and I can't see where this has been done previously. In practice, most current EHRs try to mimic the way we record these concepts in paper records, but this is not easy. How we should replicate that critical 'ALLERGIC TO PENICILLIN' scrawled in red felt pen across the front of a paper record, so no-one misses it? To take our EHRs into the future we need a cohesive suite of concept definitions that will support data capture, viewing, querying and inferencing to support clinical decision support. So watch this space, and please let me know if you'd like to join in!

Modeling an entire EHR – is it achievable?

Many will consider that creating and agreeing all the clinical content for an EHR is an impossible task. However let's consider a couple of key things about openEHR:

1. The openEHR archetype is created as 'a maximal data set for a universal use case'. So in other words, everything we can think of about a single clinical concept for use in every possible clinical scenario. In the past we have struggled and fought about the inclusions in minimum data sets, however with a maximum data set everyone's priorities can be included. The innovation of openEHR is in achieving consensus on the data specifications through use of the maximum data set but allowing for clinical diversity and relevance by constraining the maximum data set down to a useful one for each clinical scenario through use of templates. I like to think of this as a little bit of 'magic – a bit like having your cake and eating it too!
2. While there are 350,000+ SNOMED terms, we do not anticipate 350,000 archetypes. In fact 10-20 will comprise most emergency or discharge summaries and as few as 50-100 archetypes could cover most of a typical primary care EHR. Most people are surprised that we need so few archetypes, and the key reason is that each archetype is about a concept, not an archetype per symptom or diagnosis. In fact there is a single symptom archetype and a single diagnosis archetype that will likely cover more than 90% of symptoms and diagnoses, by using a terminology such as SNOMED CT to identify the actual symptom or diagnosis itself. The power of structured content definitions (the archetypes) plus a terminology is a very powerful semantic combination.
3. We have started with the hardest archetypes – those in which nearly every stakeholder and jurisdiction will have an opinion. Once these key 10 archetypes are published, we anticipate that the momentum will increase.

Tim O'Reilly spoke of the Web2.0 being a 'harnessing the collective intelligence' and while in it's early days still, CKM is starting to do just that – to bring together experts from many profession domains, areas of expertise and geographical regions with a common goal. Grassroots clinicians are contributing alongside the technical experts – all contributions are gratefully received and are incorporated into the final published content models.

Please regard this as an open invitation to all to become involved. Self-register, and if you want to become involved in archetype review then 'adopt' the archetype/s of your choice!

All Blood Pressures are not created equal! (Part II)

Following on from the previous post... If we want to compare and review blood pressure (BP) over time from all sources and clinical situations, then they need to be recorded in a consistent manner. We also need a common structure to facilitate accurate data exchange without manipulation.

Most systems have a proprietary database comprising a home-grown data structure – so if there are 'n' thousands of clinical vendors in existence, there are probably way more than 'n' thousands of technical approaches to specifying the clinical documentation and process that are so familiar to you. HealthVault is one that publishes its data specifications publicly but most private companies are not so open.

There are also a number of approaches that are proposing use of common data structures to support health information sharing. You can see some of my thoughts on this in previous posts – and in my opinion this is definitely the way to go if you want/need to do smart and active things with health data. Some examples are HL7 templates and openEHR archetypes.

Let's take a look at some publicly available representations of Blood Pressure...

On the right is the Microsoft HealthVault Blood Pressure specification (click image to enlarge):

It's largely in 'techspeak', although if you examine the specification itself you will find only three clinical elements:

• Systolic
• Diastolic and...
• Pulse!

Ouch... Pulse is usually independent of BP measurement for most clinicians, even if it may commonly be measured simultaneously. This model cannot currently capture event the basice clinical requirements identified in the previous post - not even recording that a large cuff was used for an obese patient, to indicate whether the measurement is accurate and able to be interpreted confidently. This model is really not rich enough to cater with our clinical recording requirements for Blood Pressure.

At right is a HL7 model for Blood Pressure (click image to enlarge):

Umm... maybe a little difficult to understand. It's hard to see the scope of the content, and almost impossible for clinicians to have input into, which is a significant issue in terms of achieving accessible and high quality data definitions.

Finally, openEHR has a number of ways of representing the data model for Blood Pressure. It is a maximal data set intending to capture all information about Blood Pressure measurements for all the clinical and research situations described previously, and more.

On the right is the simplest representation of the openEHR blood pressure archetype – displaying the content in a non-technical way so that all clinicians can focus and comment on the  clinical content itself.

At right is another way that the same BP archetype is displayed to clinicians and informaticians - specifically used when seeking detailed comments about the clinical content on a per element basis during collaborative online archetype reviews. While it may help to have an understanding of data types eg Text or Quantity or Date, no deep understanding of openEHR is required of participants.

In the interests of full disclosure, I have been intimately involved in the development of the openEHR Blood Pressure archetype which has been developed and agreed with a lot of clinical input, and places a lot of emphasis on being approachable by clinicians and incorporating their feedback.  The representations you see here are not perfect, but grassroots clinicians are participating actively in online reviews of archetypes.  The blood pressure archetype was published after consensus was reached on the content by 30 clinicians, informaticians and engineers from 13 countries.

There is no doubt that at first glance the archetype may appear too rich. One of the key differentiators in openEHR is the capability to take this maximum data set and activate/display only the parts that are relevant to the clinical scenario requirements eg for primary care or a paediatric patient. This detailed discussion is out of the scope of this post, and will be left until a later date.

The focus of the health IT domain has largely been technical. Involvement of clinicians has often been token or as a secondary process.  It is critical for successful development of EHR systems that clinicians are able to be actively involved in development and quality control of the clinical content that underpins these systems - clinicians need to request involvement. At the same time, the health IT domain needs to 'un-technify' eHealth - clinicians need support to participate, so that more than just a few elite informaticians can view these data structures and contribute to their development and quality review.

In these two posts we have explored a little about the scope of clinical models and their representation. Yet again, this is still only the tip of the iceberg re health data. The list goes on, including the use of terminology and the non-trivial technical requirements that are required to underpin these clinical models so that we have know exactly what this data means - far more complex than can be supplied by a simple XML model. Now that really starts to open a can of worms... for later!

All Blood Pressures are not created equal! (Part I)

Clinicians, have you ever had a look at the data structures underpinning your EHR - the models of clinical content? If you don't understand the principles of what your data structure is then your EHR may not do, or ever be able to do, all the things you need it to do to record your clinical notes. You need a sense of what is 'under the bonnet' and what its capabilities are. Take Blood Pressure as an example. It is probably the most easily understood clinical concept to both clinicians and patients. We clinicians tend to think of it as a very simple measurement to record on paper, and we expect our EHR applications to do it in a similar way.

So let's brainstorm about what we need to record blood pressure. The typical primary care provider such as a General Practitioner or Nurse will record the Systolic and Diastolic pressures, plus maybe a blood pressure cuff size if it is different to the 'normal' cuff, and position of the patient if recording a postural drop. This is straightforward, 'bread and butter' stuff for clinicians.

So the base data requirements are:

• Systolic – a quantity that is a pressure, measured in millimeters of mercury (mmHg)
• Diastolic – ditto
• Cuff size – most will measure using a 'normal' adult cuff, recording a size only if they use a larger or smaller cuff.
• Position – most patients in primary care will be sitting; most in hospital will be reclining

While this may cater for the large majority of our BP measurements, there are other less common situations where it is critical that BP be recorded appropriately and in context. So we need a data specification that also caters for the following situations where BP is measured, such as:

• The cardiologist or exercise physiologist may need additional data about the level of exertion for use in stress testing or research. A BP measured at rest needs to be interpreted differently to that recorded after jogging for 10 minutes.
• Recording a series of BP readings over a 24 hour period to determine the 24 hour average, plus knowing the patient's concurrent sleep status – this is now regarded as key diagnostic criteria for diagnosis of hypertension in Europe.
• Measuring data from home BP machines – many of these actually record the Mean Arterial Pressure and use an algorithm to determine the Systolic/Diastolic readings displayed.
• Automatic BP measuring every 5 minutes during surgery or an admission to Intensive Care by 'the machine that goes beep'.
• Paramedics taking a measurement of a trapped patient at the scene of an car accident.

Other questions might be clinically significant in some circumstances include:

• What Korotkoff sound was used?
• What about the implications for paediatric measurement?
• Where was the measurement taken? Which limb? Finger vs upper arm?
• How was it taken – auscultation; palpation, machine; or invasive?
• What about pregnant women who need to have their BP measured with lateral tilt to get a true reading – do we need to record that detail?

It may be very important to have this information recorded in some situations.

Maybe blood pressure is maybe not so simple, after all.

Clinicians understand clinical nuances well, recording the contextual variations appropriately in paper records – in fact it is so ingrained that it is almost done on autopilot. The problem arises in trying to get computers to do the same thing – to record simply in the usual circumstances but be able to cope with the complex and detailed where it is critically needed.

So, we need to have some understanding about the capabilities of our EHR systems.  Most systems only cater for little beyond the basic four requirements. Yet most of these additional requirements that we have identified are useful or necessary at other times to ensure unambiguous BP recording.

The mind map at left captures the basic versus the 'ideal' requirements. The 'ideal list may seem excessive to some. Yet if our EHR system could cater for this, then we could record all nuances of BP accurately and share them unambiguously if they share the same underlying structure - primary care to secondary care; PHR to EHR to research; patient to clinicians. So then, the 'art of the EHR' is to present the right amount of information and the right context to the clinician to let them record what they need - not too much for the common simple BP reading, but more when necessary.

Here we have started to explore the tip of the iceberg – the content scope of one common clinical measurement. The essential message here is that we clinicians need to have some understanding of what is 'under the bonnet' of our EHR systems. What may be adequate for the commonest situation is not necessarily enough for recording the complexities of clinical care.

Part II starts to explore clinician engagement in content models...

EHRs: the means, not the end

I remember hearing a story about a software demonstration for practice management and billing - a classic where the practice principal proudly stood up and gave testimony about the merits of his new system, including the news that he had to hire extra staff in order to run it, above those who had run the practice beforehand.  Apparently the audience's collective jaws 'hit the floor'.  This is not good eHealth.  Health IT should not add overheads, but make things smarter, quicker, more efficient, and more valuable - or it's probably not worth doing. There is something weird that appears to happen around computers and all things 'e' - sometimes we just seem to lose our analytical skills, or perspective, when sitting in front of a computer. Computers are just tools to support us in our practice of healthcare.

In KevinMD's excellent guest blog in August 2009, "How a wealth of information takes attention away from the patient", Abraham Verghese discusses the tension experienced - look at the data or the patient? With more information available at our fingertips and with only a limited amount of time per patient, how do we prioritize our focus for the best outcomes?  It's not easy as you might first think. We can be torn between the need or desire for (possibly) higher quality, detailed data, rather than the conducting a thorough patient history and exam - after all, time is limited.

When I was in medical school it was always drummed into me that you couldn't compromise a thorough medical history; that a history was possibly way and above more important than even the examination and the secret to good medical practice.  I have always considered that this is a good principle to work by.

If using an electronic health record (EHR) compromises those high standards, then it is time for a re-think.  An EHR should enhance, not hinder.  If it gets in the way of you talking or touching the patient, or causes you to spend more time or effort WITHOUT providing value back then there is something wrong. Note that the value may be direct and immediate (e.g. more efficient; data available at point of care) or indirect and delayed (e.g. better quality data; ability to do query/research, support recalls etc). The benefits should be obvious. Difficulties are usually multifactorial - the clinician; the application; the inability to touch type; or other factors - but they are an important trigger for stopping and investigating the current work processes so that the problems and barriers can be identified and tackled.

Anecdotally, it has surprised me to see some clinicians assume that data displayed on a computer screen has more authority than it warrants, because it is electronic format. They change the way they practice. However, just as in a paper record, because 'nil known' is noted on a computer screen next to 'Known allergies' does not necessarily mean that they don't have any - you still have to ask as the answer may have changed since last asked.  Whether a previous clinician has written in pen or electronically, there is no difference to how we should practise.

Are we compromising our practice? The good old doctor-patient interaction vs. the EHR?

An EHR should not change the way a clinician engages with the patient.

So, it's not rocket science, but don't EHR for EHR's sake. After all, let's face it; an EHR is only useful if it supports quality health care. It is a means to an end, the journey, but not THE end.

Yes, you might arrange the office differently and there might be more opportunity for collaboration once the patient can see their record - that's all good. But if use of an EHR compromises the doctor-patient communication, the recording of data, the use of time in a consultation, or making the history-taking and examination a priority, then the issue needs identification and quick resolution.

Don't lose those first principles that you learned in medical school - they are the foundation of the doctor-patient interaction. The EHR should just be a supportive framework to enable you to do a better job.  If it doesn't, stop and re-think as the EHR should enhance, not hinder.

But you all know that already - this is just a reminder for when we lose a little focus in the excitement...

Street Art and Doors

I have loved taking photos for many years. It has just been a hobby, something to distract from the routine. But it has made me stop and view the world around me from a slightly different angle. I love the textures and small details, and it is only with a camera in hand that I slow down and look up! In early 2007 I participated in a National Gallery of Victoria guided walk around my home city of Melbourne, down into the subways and past dumpsters into stinking alleys. I saw the street art around me of which I had previously been ignorant. So now as I walk around my local inner city streets I deliberately take detours down alleys and dead ends to seek out the art works – the ‘pieces, the paste-ups, the stencils that sometimes tell a story and other times are just appealing to look at; the walls and alleys that are ‘curated’ and collaborative artworks that are appearing all over my local streets. And I've found it is a great reason to get out and explore a new city or find new aspects of an old one.

Don’t misunderstand me, to those who tag my house periodically... pox on you! That’s just plain vandalism and it costs me a sweet fortune to get it cleaned off. But to those who pursue their craft with the right permissions, I think I envy you a little – your art enables me to feel a little anarchic and a little rebellious, but vicariously and without the heights!

Other objects I like are doors & gates. As eyes are like windows on the soul, doors are the 'windows' (oops, sorry) of the city... they tell you a little something about those who live there. Well, it’s a nice thought, and I have a few photos of doors. Well, it's also a bit of an obsession really. No-one else gets it! You will also likely see some textured and abstract photos.

Anyway, as an exercise to nurture my soul a little, I decided to post a photo on Flickr each day this year - my #365photo challenge to myself. Will I succeed or not? No idea, but so far, so good - up to D13! My intention is to focus on finding some new street art and posting it, but the pressure of finding new stuff everyday is probably unsustainable, so will mix with a few photos that I have gathered over the last few years, mainly from time spent trawling East London in 2007 looking for the elusive artwork of Banksy, plus a few doors from my travels.

So, the Flickr photostream itself will hopefully evolve throughout the year and today I have added a few photos from it to this blog (in the right column) - each day they should change as I add another to my #365photo challenge.

Enjoy, or not – as you please. It just is.

Standardized, data-driven eHealth

What is an EHR? Most currently working within eHealth circles will have a ready answer, and the classic response will be something like "an EHR is a software application that is used by clinicians for provision of patient care". But think about it for a second...

What do we want from an electronic health record? It's not actually the application or the user interface or the workflow, but a record of health information in an electronic format.

And so what of the health information itself? What is it? What do we want? What should we want?

Let's work with these definitions: Data are the computable facts; while health information is the data after it is processed, organized, structured or presented in a given context so as to make it useful.

We definitely want health information that...

• Is available at the right time and the right place to the right person.
• Is accurate, detailed and of high quality.

I don't think there is much disagreement on these two points. How about these next suggestions?

We should also want health information that...

• Is a lifetime health record - cradle to grave. Health information that can be accumulated over time, aggregated from many sources to inform better care for ourselves, our patients and loved ones.
• Can be created in one place or by one provider and shared with others so that the meaning of the data is preserved and accurate.
• Can be dynamically and actively used - consisting of structured, atomized data that we can re-use and combine in different ways to improve our health and wellness. Documents or PDF's of our health information are useful as part of a passive record, but they are effectively a dead end - we can't do anything useful with big blobs of text except read them.
• Is not locked in to a proprietary vendor database; data should be in an open, non-proprietary format.
• Is a continuum of our health information across all aspects of healthcare and related activities, not fragmented silos of data artificially segmented for personal, clinical or secondary use purposes.
• Can be accessed via an EHR, EMR or PHR, SEHR or ICEHR - pick an acronym, any acronym!
• Can be accessed independent of any specific organizations, providers and geographical locations.
• Has had minimal transformation or manipulation. Keep in mind the Chinese Whispers effect! There is significant risk that important data can be lost or lose integrity with each data migration to a new software application or transformation between disparate systems.

It is a commercial reality that we continue to develop EHR applications in the traditional manner, building the greatest and 'best of breed' clinical software applications, with each EHR vendor doing it in their own proprietary way, as 'rugged individuals'! The resulting software usually has a rich functionality and a great user interface. It is likely that it does a fine job locally in the clinic, hospital or network on which it is installed. But what about regionally, nationally, internationally? Is it still working well if we take the big picture view? Sure, our EHR applications are full of data, but the data is isolated, fragmented, and limited in its use.

There is no doubt that all over the world, the health IT community are finding it unexpectedly hard to exchange health information between different applications - the effort and resources that are being poured into policy, research and pilots for health information exchange is enormous. Progress is glacially slow. If we want to exchange PDFs and documents, then we are doing well, but if we want our software to be able to do more than display text, to do clever things with our health information, then our data requirements are much more complex. If we want that data to be able to be shared, used in multiple applications then the current approach requiring data transformations and messaging paradigms won't be sustainable

Interestingly, the further we go down these paths many are realizing the need to change our emphasis away from the EHR application and towards the data. Back in November 2009, Clay Shirky wrote:

"This ability to separate data from transport and applications from data is the essential pre-condition for innovation — a group that has a valuable new idea for presentation of data for clinical use should not also be forced to think about the data encoding or the way the data are transported. Groups working on new data encodings should not be tied to a pre-existing suite of potential applications, nor should they have to change anything in the transport layer to send the new data out, and so on."

The bolded text, above, reflects my emphasis on an important statement. Confirming this approach, as recently as this week, Kibbe & Klepper also called for separation of the data from the applications and from the transport layer.

Change the focus to standardized, data-driven eHealth

So, innovation requires a new approach to data; a changing emphasis from application- or message-driven to data-driven eHealth. If we also insist on an open and standardized approach to health data specifications then we will be able to realize many additional advantages:

• A strong foundation of shareable and re-usable computable clinical content definitions on which to build coordinated and cohesive applications, messages, clinical decision support programs, and research activities. If we use common, standardized data definitions then the tasks of eHealth become orders of magnitude easier. Content definitions are created and agreed as the content is already specified and the processes become more generic
• An unambiguous and detailed understanding of what each piece of data means so we can do 'stuff' with it - a tight semantic 'handle'.
• A powerful enabler for managing the complex requirements involved in health data capture, integration, aggregation, inferencing and sharing.
• A continuum of our health information, independent of vendor, provider or organization - the real potential for lifelong health records, for the first time.

There is no doubt that this approach is orthogonal to the status quo and it will be challenging to many for logistical, financial and political reasons, but can we really afford to ignore this?

According to the European Commission's seminal 2009 report entitled "Semantic Interoperability for Better Health and Safer Healthcare: Research and Deployment Roadmap For Europe" (PDF, p16), standardizing the capture, representation and communication of clinical data requires three components to represent meaning: a generic reference model for representing clinical data, agreed clinical data structure definitions and clinical terminology systems. Potential standardized data definitions proposed are openEHR archetypes, ISO/EN 13606 Part 2 (which are simpler archetype structures), HL7 templates, generic templates and data sets.  Standardization of data is not 'pie in the sky' but an approach that has had significant research and implementation experience, particularly in Europe.

So, to consumers, clinicians, organizations, researchers and governments, the call should not only be "Gimme my damn data!" but give me standardized data that is application- and message-independent. Then we can actually start to use and re-use our data, not only as a detailed record of current and past health conditions, events and activities, but dynamically and pro-actively to inform and promote our future health and well-being.