In the world of digital health, progress has been glacially slow in the past thirty years... There is no doubt that the eHealth ecosystem is incredibly complex, probably more so than any other domain.
If you need your health data to be fit for purpose, reusable and as futureproof as we can make it, the data needs to be designed by someone who can bridge between clinical, administrative and reporting requirements and the software engineers. You need someone who understands how the data will be used, clinical workflow needs, implementation constraints
Despite having working electronic health records for more than three decades, most major software projects have not changed the way they build clinical systems - and the result, yet another silo of data focused on a single project or purpose.
Interoperability of the whole health record will not be solved by the 'band aid' application of standardised messages or documents - it will only result in a single message or document being exchanged.
What are the key issues facing digital healthcare?
Health Knowledge Complexity
The scope of clinical data is massive - broad and deep - demonstrated by the hundreds of thousands of clinical terms and over a million relationships that exist within the SNOMED CT terminology alone.
Most understand this, yet underestimate one of the most important aspects of healthcare - it is evolving at a faster rate than you think - new information, addition of detail and granularity, and discovery of new relationships.
And if we consider something as simple to a clinician as a blood pressure reading of 120/80 mmHg, very few systems have the capability to directly share this ubiquitous piece of data without negotiation or transformation. And if you add in the variation in the subtler aspects of blood pressure measurement such as site of measurement, position of patient, cuff size etc then the complexity is amplified enormously. Measurement of blood pressure by clinicians is not as simple as most think, and most clinical systems are not capable of recording attributes that clinicians require for accurate clinical interpretation.
CLINICAL data Diversity
Different stakeholders have different requirements depending on:
- purpose of data use - direct patient care, clinical recording, data exchange, decision support, aggregation and analysis, population health and administration/reporting
- profession - profession, specialty
- variety of data required:
- free text vs structured data
- normal statements
- persistent data vs event based - longitudinal health record vs questionnaires or checklists
- multimedia representation eg images and videos
- visual representation eg graphs
- data source - patient history, clinical record, device, message, clinical portal, consumer entered
The chasm of MiSunderstanding
Who currently designs our data? The clinicians? Or the software engineers? Both?
Current software development is usually the result of a fragmented and patchy process where clinicians and implementers come together to communicate clinical requirements and technical constraints, but almost always the process is flawed because there is a frustrating communication gap between the two. Neither can be expected to fully understand the other's expertise and language. The resulting software is commonly disappointing.
If everyone creates their own 'special' health data silo then it's not hard to imagine the chaos that must result.
Everyone has different systems and the the majority have extremely limited ways of talking to each other. The vendor mantra of "Buy more of my software if you want interoperability" is simply not acceptable.
What is needed to change the status quo?
- A 'lingua franca' for healthcare - a common language - that represents accurately what clinicians, consumers, administrators, researchers, and government require from our health data, that can be passed on to our software engineers for implementation in functional and reliable clinical systems, consumer apps, aggregated research databases and reporting tools
- Experts who understand clinicians, clinical workflow, organisation processes, software design, user interface design and application delivery.
Atomica Informatics has more than a decade of experience designing the openEHR approach to clinical data as the lingua franca and 25 years designing clinical systems.