Keeping a clinical list up-to-date in a local EHR current is not a trivial task. Keeping it up-to-date and accurate in a shared environment - well... Read on. It is not easy.
True or false: 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?
Incoherence is not ideal, but it is a realistic part of any work such as we are doing within the openEHR community. Transparency and openness can mitigate some of the incoherence. Within a transparent, governed and collaborative environment incoherence and apparent conflict can be recognised and leveraged constructively to improve the quality of archetypes.
"For the first time in Australia, we have strong evidence of the benefits of eHealth records in bridging the gaps in information that occur as patients move between different healthcare providers in the public and private sectors."
Bridging the gap between the clinical experts and software engineers involved in eHealth projects is well known for being difficult and frustrating for both sides. The openEHR methodology is having great success in bringing the non-technical clinicians along with us on the clinical modelling journey.
Watch what is evolving in Brazil... It is largely a greenfields nation as far as electronic health records is concerned, which gives it a great opportunity to make bold and innovative decisions, avoiding many of the pitfalls of those who have gone before and the constraints of legacy systems.
The scope and diversity of clinical content in the physical examination domain is huge and complex, with different clinicians requiring different levels of detail. We have developed a base pattern for recording physical examination findings, knowing that the concept-specific detail within each model will need be added as backwardly compatible revisions of these archetypes. In this way they will evolve in an organic way to suit clinical requirements, but within a tightly governed environment.
The extremely complex nature of the clinician's physical examination is an obvious benchmark test for the capability of any modelling paradigm. If you can't model the clinical requirement for something as fundamental, yet frustratingly diverse as physical examination, then you need to go back to the drawing board until it works. This post outlines our journey...
Through trial and error and implementation and iteration, we are starting to identify pragmatic and sensible patterns that will fast track future archetype development, but there is no denying that it has been a long and slow process to get to this point…