Presented at Health Informatics New Zealand (HINZ 2017) Conference, 1-3 Nov 2017, Rotorua, New Zealand. Based on my Masters student Peter Wei's research. Authorship: Ping-Cheng Wei, Koray Atalag and Karen Day from the University of Auckland.

1. openEHR Approach to Detailed
Clinical Models (DCM) Development
Lessons Learnt from the International Review of
the Tobacco Smoking Summary Archetype
Ping-Cheng WEI, Koray ATALAG, Karen DAY
The University of Auckland

2. Outline
• Problem Definition
• DCM and openEHR
• Methods
• Findings / Results
• Discussion

3. What’s the Problem?
• Rising burden of diseases: a challenge for many healthcare
systems worldwide
• Healthcare is data rich information poor! Reuse little
• Getting smarter with data requires interoperability
• Getting clinicians to agree on common/minimal dataset
definitions is HARD!
Can we aggregate (tobacco) smoking data at global scale
to address Tobacco Epidemic?
Almost everyone uses own definition!

5. Detailed Clinical Models (DCM)
• Smallest non-divisible clinical concepts + context
Examples: blood pressure, body weight, lab result, BMI
• Information modelling methodology:
– Structural data constraints: List, table, tree
– What data types can be used?
– What values are allowed for these data types?
– How many times a data item can exist?
– Whether a particular data item is mandatory/optional
– Whether a selection is involved from a number of items/values
– Links to clinical terminology (e.g. SNOMED, LOINC)

6. Simple DCM: Body Weight

7. • Open access specs & tooling for representing healthcare
data, enabling interoperability and building EHR
• Supports very elaborate DCM development (=Archetypes)
• Scope is full EHR - not just health information exchange
• Not-for-profit organisation - established in 2001
• Based on 20+ years of international research and practice
• Also an ISO/CEN standard (ISO 13606)
• Big international community
• All DCMs are available from: http://openehr.org/ckm
www.openehr.org

8. The Study
(Peter Wei’s Masters Research)
• Explored the socio-technical aspects of the openEHR
approach to DCM development
• Observed openEHR CKM review through publication
• Participatory observation of reviews
• Semi-structured interviews with reviewers and editors
Approved by the University Of Auckland Human Participants Ethics
Committee on 19/08/2016 for three years. Reference No: 017360

12. CKM Review Content

13. CKM Review
Content

14.  Review 1
Review 2 

16. Findings: Data interoperability and reusability
• There is no ideal “sweet spot” between local and international
interoperability, it varies enormously depending on time and place
• Different countries have different risks, exposures, and nomenclatures,
so it is hard to develop a scale that would make sense for all
• I don’t think there is a huge appetite to drive for international
interoperability, however, it doesn’t mean that it’s not worth it
• Even if you have some kind of logical reasoning at the national level, it
always goes down to the local level, and they always have the
opportunity to give their verdict
• Paradoxically, it may be the vendors that push for international
interoperability

17.  Smoking history, trying to ask appropriate questions that capture peoples’
life-time exposure to cigarettes is important because it tells us the weight
of exposure and thereby the risk of likely adverse health outcomes
 Using really simple questions to capture information that can be used to
guide treatment
 It’s irrelevant to have more detail, because it’s a technical and a
terminological question, and it’s not reasonable to have larger chunks as
no one person can be an expert on everything
 Essentially, we are collecting the same data, but asking different
questions due to the different variations in practices, and over time results
in disparities, which is why it’s so hard to get all those data together
Findings: Accurate capture of patient data

18.  They didn’t understand what I was talking about, so they just went ahead
and said “we will listen to the experts, you are not an expert”
 I was frustrated as I could see that not even eight questions would be
reasonable to ask during a clinical circumstance, it’s just too tiresome to
ask all those questions
 I have presented my model to the editorial team, and they said it’s the
Rolls Royce of input of data, still the archetype needs to be able to
calculate all the content that could be calculated from this model, so the
archetype needs to be more extensive
 That’s the beauty of the system is that it’s there for a community to
comment on
Findings: Challenges of sharing tacit knowledge

19.  The difference in the detail of questions being asked actually reflects
what information is being captured, and for what purpose.
 We try to reflect practices, not necessary direct it.
 There is a tension between modelling patterns, and you need to
decide on pragmatic choices to make the model work in the real
world and make it feasible for clinicians to record the information
they are asking for
Findings: Balancing academic and clinical

20. Interoperability Spectrum
General views of the interviewees:
As interop shifts from local to international data becomes more generalised.
Healthcare providers have less information to work with and to support care
delivery! Therefore, there needs to be a balance between interoperability
and reusability and the clinical practicality of the data collection

21. Synthesis

22. Conclusions
• Crowdsourcing of domain experts broadened the perspectives
of editors, and ensured the DCM to meet a wide range of
expectations from different parts of the healthcare system,
and thus, future-proofed it
• Interoperability and data reuse is a key factor for the success
of health information systems, however, the degree at which
it can be achieved is largely variable!
• In health IT development, there is often a tendency to start
anew; thus, reinvention is the norm rather than exception!

23. Limitations
• Due to time constraints, the study focused only on the
development of one DCM from one open standard
organisation
• The study was only a snapshot! The development of
openEHR DCMs is a continuous process where the DCM can
be resubmitted for review, and further development
• Did not evaluate the performance of the DCM within the
healthcare system, nor received any feedbacks of those
who adopted this DCM

24. Thanks
Koray Atalag MD, PhD, FACHI
k.atalag@auckland.ac.nz
Senior Research Fellow, ABI
Management Board Member, openEHR Foundation
Chief Information Officer, The Clinician