Archetype collaboration building an eHealth infostructure
For the past decade, a growing and vibrant community of international eHealth experts with representation from 86 countries has been successfully collaborating to create an independent knowledge base of computable clinical specifications, ready to use and share in eHealth projects and health records.
Each clinical knowledge specification is based upon ISO 13606 and is freely accessible to anyone for download. Participation in the development of these computable specifications is also open to anyone with an interest in eHealth and with a willingness to share their knowledge amongst the community.
The resulting specifications, known as archetypes, are effectively independent of any single vendor implementation or messaging formalism.
This national and international collaboration aims to break down silos of health data. Development and use of archetypes is gathering momentum in Australia and by overseas national eHealth programs as the value of this work and the substantial benefits are being realised.
The efforts from this community can be found in the international openEHR Clinical Knowledge Manager (CKM) and, locally in Australia, in the NEHTA CKM.
The size of the scope of clinical content required to build electronic health records is usually severely underestimated – the sheer breadth and depth surprises most venturing into this area, further compounded by the need to incorporate a dynamic and evolving clinical knowledge base.
Traditionally, the health IT domain has built information models for specific purposes, such as a document or message, and focused on data exchange between systems or form-based specifications. In contrast, each CKM is a library of clinical knowledge specifications, known as archetypes, which are re-usable across multiple documents, messages, healthcare contexts, domains and professions, developed collaboratively and shared between different CKM communities.
Each agreed and published archetype establishes the data elements, their constraints and semantics to accurately express clinical content in a computable form. Clinical archetypes can then be used to collect consistent information that clinicians need as part of day-to-day patient care, for exchange with other clinicians and between clinical systems. Archetypes are also used to underpin complex decision support, research and analysis.
If we want to leverage ‘big data’ then we need to be sure that the ‘little data’ is accurate and safe for purpose. This is a paradigm shift in eHealth.
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. These approaches do have limitations.
Minimum data sets were originally designed for reporting purposes and while they have been useful, they are inadequate as a sustainable approach to management or exchange of more granular data or complex clinical scenarios.
Patients vary, so that no single discharge summary or consultation note will suit all. Clinicians vary, so that no single approach will fit all professions, generalist and specialists. Clinical contexts vary – that old saying, ‘right information for the right patient at the right time’, also needs ‘the right context’ added to the mix. In reality, the ‘one size fits all’ approach to health data standards is an absolute myth – it is more like ‘one size fits none’.
The CKM communities have experienced considerable traction in developing agreed and clinically verified archetypes to express clinical concepts using a maximal data set and universal use case approach. In this way, the archetypes can ‘fit all’.
Each archetype contains all of the data elements that describe a single clinical concept across the full range of possible use cases, including personal health records, primary care, hospital care, secondary use of data, population health and research.
For example, the archetype for blood pressure contains 20 data elements and there is the ability to extend it using other archetypes that describe level of exertion as the blood pressure was taken with the patient running on a treadmill or the exact device used for measurement.
It will also enable explicit differentiation of a systolic measurement taken as part of a vital signs examination from the average systolic measurement recorded during 24-hour Holter monitor monitoring. Only the data elements that are relevant for the clinician’s purpose and clinical context need to be shown in a clinical system.
In the case of blood pressure, commonly three data elements might be displayed on the clinical system’s screen – systolic and diastolic measurements and the position of the patient – but any and all of the other data elements can be displayed in other clinical contexts when relevant.
Clinicians have long recognised that the traditional business approach does not translate well into the business of clinical practice processes. We absolutely need to transition away from technicians and vendors dictating what clinicians have in their EHRs, information managers using their traditional paradigms and software engineers designing the data structures that represent the clinical data and workflow in every EHR.
With the best of intentions from both sides there is still a massive semantic chasm between the two professions as demonstrated by the many systems that don’t meet clinical users’ needs. The adoption of the openEHR approach resolves these issues.
The openEHR approach now in use is the result of years of research, investigation of existing clinical systems, engagement with grass roots clinicians, domain experts, vendors and standards organisations around the world. As an example, in the past three months the international community has achieved consensus on an archetype representing adverse reaction risk.
This archetype has had an extensive journey of evolution over the past 10 years. The published archetype is the result of input from international eHealth programs, HL7 FHIR and patient care communities, international standards, and an extensive collaboration process across three CKM instances in Australia, Norway and the international community.
During 13 CKM review rounds, steered by editors from Australia,the UK and the US, we had 92 participants from 16 countries, 221 total reviews and zero face-to-face meetings. This has not been a trivial body of work, as adverse reaction is a core concept in any clinical system, but in practice every system has implemented it slightly differently.
This archetype is now an open specification representing a massive collaborative effort. It may not be perfect, but it is freely available and downloadable for use in any system. If new requirements are identified, then there are governance processes available to revise and republish, but for now we have effectively drawn a line in the sand, and made this archetype available as a starting point for others to use, share or refine.
There is a powerful logic in actively separating the development of clinical content from the implementation or messaging formalism or screen design for data capture or display. It is only by actively separating these processes that we can develop, agree and verify the clinical content specifications once and share and reuse across multiple eHealth domains.
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.
Archetypes, as specifications for clinical knowledge in an open, non-proprietary format are a disruptive innovation. One does not have to be a rocket scientist to recognise that if Australia can leverage the 400+ archetypes that already exist in the international CKM, already incorporating a huge breadth of clinician knowledge and expertise, we can kick start some intelligent and cohesive clinical system development.
All those who share the same archetypes will be able to share that same data. This effectively creates an ecosystem of coherent and interoperable clinical data which has the potential to be interoperable or aggregated and this ecosystem is able to engage with ongoing further developments.
Once created and verified as fit for use by participating clinicians, health informaticians, vendors, administrators and other data users, a library of archetypes can persist as a infostructure resource for years, and maybe even decades. Governance processes ensure that the archetypes are maintained and can evolve within a robust versioning and publishing framework. Archetype-enabled implementations will then contain the same, standardised clinical data patterns.
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 represent a pragmatic and sustainable approach to interoperability: between professions; between implementations; beyond our current technologies.
Evelyn Hovenga, Heather Leslie and Heather Grain are all part of the Global eHealth Collaborative (GeHCo), which has been established to build communities of health informatics experts to bridge eHealth silos by establishing communities, building capability and making a practical difference.
GeHCO will be launched in Sydney on April 6 at the CBD campus of the University of NSW, followed by a seminar and a workshop on April 7. The Melbourne launch will be held at the Melbourne Business School on April 13 and 14. See the GeHCO website for more information.