Clinical Knowledge Governance in a Web2.0 world

Establishing and maintaining the quality of clinical knowledge is clearly the domain of the expert clinicians themselves. This is a broadly accepted principle for management and governance of the traditional clinical knowledge artefacts. However this assumption needs re-evaluation when we need to establish quality, safety and ‘fitness for purpose’ of computable clinical knowledge artefacts that populate Electronic Health Record (EHR) systems. Clinical knowledge has traditionally been created and shared through formal publication and peer-review processes that have been adjudicated by committees of clinical experts. Those expert committees have been appointed through a credentialing process and have had jurisdiction and oversight over the entire publishable content – ‘the buck stops here’. Before the rise of the internet, face-to-face meetings have been where most of the committee work has been done, and the process has most often been slow and expensive but delivered good quality publications. The opportunity cost to each participating clinician has been high with recurring interruptions to their clinical activities. Revision of those publications at a later date repeats this process, taking considerable time, money and resources.

Certainly in recent times, there have been more electronic tools to support these processes – email, teleconferences and videoconferences have improved the logistics of the process, but essentially the process remains unchanged.

Given the increasing traction of electronic health records, there is a parallel movement to develop and share computable clinical content definitions that can be created, published and implemented by: multiple clinical disciplines; generalists and specialists; primary, secondary and tertiary care organisations; population health planning; clinical researchers; and knowledge-enabled systems such as clinical decision support applications. They need to be language independent and translatable, in order to transport health information across national boundaries.

These kind of computable clinical models need the input from many experts, clinicians and others, to ensure that they are not only clinically appropriate but support safe data usage in our EHRs. These models are increasingly being created with ambitious goals – to create once and then re-use many times. In this case, the scope of the models needs to include requirements of the full breadth of clinical professions and specialties. Clinicians remain key to their development and publication, but they also require input from:

  • Other domain experts – non-clinicians who will want or need to use these same models for non-clinical purposes such as secondary data use;
  • Informaticians – who understand how these models will be the basis for recording health information, exchange between systems, reporting, data aggregation and how knowledge-based activities.
  • Terminologists – to ensure that the models will integrate with appropriate terminology value sets;
  • Technicians – who will advise on the technical impacts of these models in systems; and
  • Translators – who will ensure that the clinical information is faithfully transformed from one language to another.

Examples of these computable clinical content models are many and varied. There are open source and proprietary models of many different flavours and philosophies – archetypes, templates, detailed clinical models etc. In recent years there are increasing attempts to broaden the input to the creation of these models and even to start to standardise them – regionally, nationally and even internationally. In this new paradigm, the traditional approaches to clinical content development, management and governance are no longer sufficient.

When the full breadth, depth, and dynamic nature of clinical knowledge is considered, it is not feasible to be able to appoint an overarching committee or board who would be capable of providing final ‘sign off’ about the clinical ‘correctness’ for any one model. Each clinical knowledge model will require input from varying groups of expert clinicians, terminologists, informaticians and technicians, depending on the clinical knowledge artefact under review. We need to find innovative approaches to online and asynchronous collaboration of a wide range of individuals from diverse backgrounds, expertise and geographical location to ensure these models are suitable for use in clinical systems.

Traditional standards bodies, such as ISO, CEN or HL7 have well defined and fixed processes in place for managing the lifecycle of technical standards through a formal balloting process with registered member bodies. These are definitely not suitable for managing and governing an evolving and dynamic clinical content specification library.

There has been some early work on establishing abstract archetype quality criteria by QREC and more recently, ISO TC 215 Working Group 1 has established a new work item 13972, which is establishing “Quality criteria for detailed clinical models”.  However, neither of these are able to establish the quality of archetype instances for real world use.

I believe that HL7 is working to establish a Template Repository. As I understand it, it will operate as an indexing service to templates that will be stored on distributed servers. Others may be able to provide more details.

Other work is no doubt occurring, of which I am not aware. And of course, each clinical system has to establish the clinical content that it will use in its own proprietary information model. In the US alone, with thousands of clinical software vendors, this means that we have thousands of different computable versions of essentially identical clinical content, but none of it interchangeable without mappings or transformation – what a huge waste of resources! We need to change this blinkered way of thinking.

The openEHR Clinical Knowledge Manager (CKM) is the only online clinical knowledge resource, to my knowledge, which is supporting collaboration by clinicians, other domain experts, informaticians, technicians and translators to achieve consensus about quality and safety in clinical content models – in this instance, openEHR archetypes.  I am directly involved in the development of this tool, and am active as an Editor facilitating the review process of the archetypes – I have described it in previous blog posts.

While CKM is one of the early Web2.0 approaches to collaborating about clinical content models, I am sure there will be more over time. I have spoken to a number of Knowledge Management experts, and to my surprise no-one has yet been able to point me to similar tools, resources establishing quality within a Web2.0 environment. Are we really such pioneers? Surely there are similar approaches in other knowledge domains?

No matter. There is no doubt that we are only in the early stages of a transformation in clinical knowledge governance and we have a lot to learn about how to establish quality criteria in a Web2.0 environment. I’ll post some thoughts in my next post...