“Smart data, smarter healthcare”

Last week Hugh Leslie & I spent time in Shanghai and Huangzhou at the invitation of Professor Xudong Lu and Professor Huilong Duan. It was a privilege to be invited and particpate in the very first openEHR meetings to be held in China.

It follows on from a surprise discovery of Professor Lu’s work presented at the Medinfo conference in Brazil last year, and Prof Lu attending our openEHR training in Kyoto in Janauary.

Hugh & I presented at two events:

  • a seminar of invited guests and VIPs for the first openEHR meeting to be held in China on April 18 in Shanghai – an introduction to openEHR (Heather) and an overview of openEHR activity in Australia (Hugh); followed by
  • an introduction to openEHR – at the China mHealth & Medical Software conference, Shanghai on April 19

Watch my introduction to openEHR, ‘Smart data, smarter healthcare’ presentation, available via slideshare:

Adverse reaction risk: the provenance

This week I documented the provenance of our Adverse Reaction Risk archetype – it has been a long & memorable journey from the first iteration in 2006 through to its publication in the international openEHR CKM last November 2015.

In the beginning was Sam Heard‘s original archetype – created way back in 2006 when Ocean Informatics had a .biz email address and before any collaboration – just the initial thoughts of one individual.

original

This was uploaded to the International openEHR CKM in July 2008.

beginning

In 2008 this archetype had its first collaborative review. The results of this were collated and as Editor I revised this archetype significantly to include the review feedback PLUS input from a number of publications available from NHS England, FDA and TGA  drug reporting requirements and the ICH-E2B publications. This was uploaded at the end of August 2009.

In late 2010, Australia’s National eHealth Transition Authority (NEHTA) forked the archetype and brought it into the NEHTA CKM environment and ran a series of 5 archetype reviews during the period through to June 2011. The resulting archetype formed the basis for the adverse reaction data elements in the initial PCEHR CDA documents which are currently being transmitted from Australian primary care clinical systems into the PCEHR (now rebadged as ‘My Health Record‘).

NEHTA starts.jpg

In 2012, there was another review round carried out in the international CKM.

The results from that 2012 review, the outcomes from the June 2011 NEHTA archetype and publications from HL7’s FHIR resource and RMIMs were amalgamated by Ian McNicoll in June 2014 to form a new archetype – initial called ‘Adverse Reaction (AllergyIntolerance)‘ and later, the ‘Adverse Reaction (FHIR/openEHR)’ archetype – with the intent of conducting a series of joint FHIR & openEHR community review of the combined model and at the end of the process generating a FHIR resource AND an openEHR archetype with matching, clinically verified content.hl7.jpg

In August 2014 the first joint openEHR/FHIR review was carried out, with myself (@omowizard, AU, openEHR), Ian McNicoll (@ianmcnicoll, UK, openEHR), Graham Grieve (@GrahameGrieve, AU, FHIR) & Russ Leftwich (@DocOnFHIR, USA, HL7 Patient Care/FHIR) as editors. Nasjonal IKT forked the archetype into the Norwegian CKM at the conclusion of that process.

norway

There was a subsequent joint review between openEHR & FHIR that followed, only rather than the few weeks I had anticipated, we had to wait until the FHIR community completed a full FHIR ballot. This blew out the review period to 7 months for our work.

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This really highlights the need to separate the ballot/review process for clinical artefacts like FHIR resources and archetypes from balloting process of complete technical standard or specification within a typical standards organisation. If we use this same glacially slow process for the governance of clinical artefacts then it will take decades to achieve high quality shared clinical models.

And one HL7 participant contacted me and said it would be impossible for them to respond to the archetype review in less than 6 months. <facepalm here>. Just for perspective, our typical review round is open for 2 weeks and it takes anywhere from 10 minutes to 30 minutes for most participants to record their contribution.

But we waited… and fed the FHIR ballot comments back into the next archetype iteration. There were not that many! And then we sent it out for the next review – and this time the Norwegian CKM community participated as well. The Norwegian CKM team (led by Silje Ljosland Bakke, @siljelb, & John Tore Valand, @Jtvaland) translated the archetype into Norwegian &  ran a slightly shorter review period, contributing the collective feedback into the international review.

We did this simultaneous review across the FHIR, international and Norwegian communities twice – once in July 2015 and another in November 2015. One of these reviews resulted in the renaming of the archeytpe  concept to ‘Adverse reaction risk’.

double

At the end of the November 2015 review round, the editors found that there was a consensus reached amongst the participants. In the international CKM we removed the FHIR-specific components and published the content of the ‘Adverse reaction risk’ archetype. The publication status of original archetype was simultaneously changed in the CKM  to rejected – this rejected archetype remains in the international CKM as part of the provenance/audit trail for the published archetype.

publish

The Norwegian CKM has now taken that international archetype and published it within their CKM and under their own governance. The archetypes are semantically aligned.

The FHIR resource has evolved in keeping with the archetype changes. To be completed honest I’m not sure if the final, published openEHR archetype has been reflected back into the latest FHIR resource, but there is no doubt that there certainly the great majority of the two artefacts are aligned due to the joint review process.

derive

The archetype that has finally been published started with the brain dump of a single clinical informatician. At this point in its journey this archetype alone has been shaped by:

  • 13 review rounds
  • 221 review contributions
  • 92 unique individuals
  • 16 countries (top 3 being AU, NO & US)

This has been a very significant block of international work. Getting any kind of consensus on such a clinically significant artefact across different jurisdictions, standards organisations and diverse requirements has not been easy. But we have experienced a great generosity of spirit from all who contributed their time, expertise and enthusiasm to capture an open specification for a single piece of clinical knowledge that can be re-used by others, and potentially improved even more over time.

This is what the published Adverse reaction risk archetype looks like today:

latest.jpg

The detail and thought behind each data element and example is significant. Yet we know it is not perfect, nor ‘finished’.

No doubt we will identify new requirements or need to modify it. This journey will then start its next phase…

If you have identified additional requirements… If you disagree with the model…  then register and contribute to the community effort now by registering on the international CKM and make a change request or start a discussion thread.

 

 

Bridging the interop chasms

The dilemma for implementers is: how to standardise clinical content yet use it in different clinical scenarios? How to lock down clinical content yet express variation in clinician requirements. How to create clinical content standards when every day the scope, depth and detail of the content is dynamically evolving? And then if we somehow manage to specify the content enough to successfully implement our own system, how to make that solution interoperable with others?

Everyone is running around (often in circles) trying to find the holy grail of health IT, the ‘one ring to bind them all’ of standards and, more recently, the ‘Uber of healthcare’. The sheer number of approaches reflects that there is no clear single approach at this point, no clear winning strategy.

My proposal: if we want to achieve any degree of semantic interoperability in our clinical systems we need to standardise the clinical content, keeping it open and independent of any single implementation or messaging formalism.

I noticed that John Halamka, CIO at Harvard & Beth Israel Deaconess Medical Center, was quoted in a rather unappetising Forbes article yesterday – worth reading for the interesting content but please leave the title and analogy at the door. His quote:

“FHIR is the “HTML” of healthcare. It’s based on clinical modeling by experts but does not require implementer’s to understand those details. Historically healthcare standard were easy for designers and hard for implementor’s. FHIR has focused on ease of implementation.” 

Totally agree: FHIR is the newest technology on the block and indeed many are considering it the HTML of healthcare. It has created a massive buzz of excitement around the world. But remember that HTML itself is a content free zone. Without addition of content, HTML is essentially just a technical paradigm. Similarly, without high quality clinical content, FHIR runs the risk of just being a marvellous new technical approach, elegantly solving our current implementer nightmares. We need more…

I have blogged previously about my experience participating in a FHIR clinical connectathon this time last year: The challenge for FHIR: meeting real world clinician requirements. My opinion about FHIR is neutral. I am not a software engineer. However as a clinician it was not offering enough to meet my recording needs a year ago. Little of my world has been FHIRified since. No doubt the FHIR team have a strategy for that, it will evolve, sometime.

My potentially controversial position is that it does not necessarily follow logically that the clever minds who devised FHIR are best placed to develop the clinical content that will ensure FHIR’s success. The great majority of FHIR models created to date are related to the US domain and within a rather limited scope that are largely focused on supporting existing messaging requirements and simple document exchange.

This is not a FHIR-specific problem – it is ubiquitous across the healthIT ecosystem. We need to transition away from the traditional business approach where the technicians/vendors dictate what clinicians would have in their EHR, and the data structure is determined by software engineers who have to investigate, interpret and then attempt to represent the world and work of the clinician in every EHR. With the best of intentions from both sides there is still a massive semantic chasm between the two professions.

What most technical modellers haven’t yet grappled with is the huge scope of clinical content – the sheer breadth and depth is astounding and as new knowledge is discovered it is also dynamic and evolving, which only compounds an almost impossible task. Most clinical recording in systems to date is relatively simple – usually focused on the ‘one size fits all’ minimal data set approach to enable some information to be shared broadly. It certainly has had some limited success but how long will it be before we realise that we need to standardise more than the minimum data sets.

Minimum data sets are woefully inadequate when we need to represent the detail that clinicians record as part of day-to-day patient care, for patient-specific data exchange with other clinicians, to drive complex decision support, for data querying, aggregation, analysis. Patients vary, so that no one approach will suit all – the needs for a surgical patient, a neonate, a pregnant woman vary hugely. Clinicians vary, so that no one approach will suit all – generalist vs specialist; medical and nursing notes may focus on the same things but from a completely different point of view. Clinical contexts vary, so no one approach will suit all. Many aspects of clinical recording needs recurring, fractal patterns. There are homunculi, questionnaires, normal statements, graphs, video, audio. The ‘one size fits all’ approach to health data standards is an absolute myth – in fact, the truth is actually that one size fits none.

Take the timing of medications as an example. Just this one seemingly simple data element raises a huge number of challenges for EHRs. I challenge you to show me one system in the world that enables prescribing today at the following level of detail:

This is the level of detail that clinicians need today in their clinical work. Yet most clinical systems only cater for the ability to prescribe to the level of complexity where someone can take one tablet, three times a day, after meals. Even if you try to prescribe a skin cream, many systems are unable to do anything but represent it in the most rudimentary way.

Below is the mind map of the current Medication Order archetype:

medication

You can see and download the corresponding archetype that is currently undergoing review here. This clinical content specification is the result of years of research, investigation of existing clinical systems, engagement with vendors and standards organisations and direct clinical informatician experience. The amount of work involved in specifying this common clinical order should not be underestimated, nor should it need to be undertaken ever again if we can get appropriate levels of agreement through international domain expert review! (Please register in CKM and adopt the archetype to participate in the international review.) It is massive. It is hugely complex.

Via a similar process, we have just achieved a consensus view on our Adverse Reaction Risk archetype: 12 review rounds completed; 91 participants from 16 countries; 182 total reviews; 0 face-to-face meetings! A core concept in any clinical system, with every system implementing it slightly differently. Now we have a line drawn in the sand, a starting point for being able to share adverse reaction data that has been designed and verified by clinicians, yet immediately computable. This work was done in collaboration with the FHIR/HL7 patient care community – note the joint copyright!

Archetypes bridge the semantic chasm between clinicians and software engineers.

Using archetypes as the means to represent clinical knowledge in an open, non-proprietary way is major breakthrough in our quest to “help kill the “golden goose” of proprietary EHR data”, as the Forbes article phrases it.

One does not have to be a rocket scientist to recognise that if we leverage the 400+ existing archetypes already in the international CKM, which already incorporates a huge breadth of clinician knowledge and expertise, we can kickstart any serious development of implementable resources for any technical paradigm willing to join in.

There is a powerful logic in actively separating out development of clinical content from the implementation formalism. In that way we can develop, agree and verify the clinical content specifications once. The resulting archetypes become the free, open standard representing the clinician’s knowledge in an implementation agnostic way. Subsequently technical transformations will be able to deliver the content to the implementer in any formalism that they choose. No longer just one archetype for openEHR implementation alone, but leverage the content to develop FHIR, CIMI, CDA, v2, UML resources… Now there is a vision!

Archetypes bridge the semantic chasm between implementation formalisms.

IMO this is probably the greatest benefit : the archetyped clinical content is created once, verified as fit for use by our clinicians, and remains as a governed infostructure resource for the next years, decades and beyond. Governance processes ensure that the archetypes are maintained and can evolve within a robust versioning framework. Different implementations will have the same, standardised clinical content.

One solid truth that we can rely on in the world of technology is that FHIR, HL7v2, HL7v3, CIMI, UML, AML, openEHR and other implementation formalisms will likely be overtaken at some time in the future. As sure as death and taxes. We really don’t want to start the process of building content for the each and every new technical invention that comes along.

Archetypes bridge the chasms created by the volatile fads and fashions in IT: our resulting ehealth INFOstructure will be a non-proprietary representation of clinical knowledge that can withstand and outlast the inevitable waves of technology as they come and go. 

Archetypes are a pragmatic and sustainable approach to interoperability: between professions; between implementations; beyond our current technologies!