What is NHS Data Orchestration?
Data Orchestration, in short, is the art of getting data where it needs to go. A Data Orchestration platform is a system that pulls data from a range of different systems and makes it accessible from a single location, in a single format. In the case of the NHS, a Data Orchestration platform would integrate with Electronic Patient Records (EPRs) and other essential systems to create comprehensive patient records that cross geographic and institutional boundaries.
What’s critical about a Data Orchestration platform is that it makes data available at the point of need. That means it’s not just another database. It would be a matter of duplicating existing records to store in another location – that would just multiply effort, complicate processes, and create additional security risks should either of the platforms be hacked. The Data Orchestration layer accesses data where it is, no duplication required. The information on a single patient would be gathered from multiple platforms and presented in a single interface, eliminating effort, rather than duplicating it.
But Data Orchestration isn’t quite at the stage where we can plug it in and let it run. A few roadblocks still stand in the way:
- A patchwork of disparate procurement approaches and the tangled IT landscape that arises from it means that any Data Orchestration platform would have to integrate with a huge range of legacy systems.
- Concerns about cybersecurity, data privacy, and data hygiene will persist.
- Cultural resistance to new technology makes any new adoption, no matter how useful, a challenge.
There are some major challenges standing in the way of Data Orchestration. But that isn’t to say that adoption isn’t worth it.
NHS Data Orchestration Delivers Value Immediately
A Data Orchestration platform would represent a foundational step for the IT landscape of the NHS. Years, decades, down the line, new technology deployments will be made quicker, cheaper, and easier. But this isn’t just a long-term initiative. A Data Orchestration Layer would deliver major benefits from the moment of go-live.
Healthcare runs on data. Without comprehensive patient records, it’s impossible to deliver effective care. In the twentieth century, this data was stored in paper records, and underpinned the personal relationship between the doctor and their patients. Today, our society moves faster than ever. Patients move between different NHS trusts depending on their location, needs, and staffing situation. To deliver quick, effective care, patient data needs to be immediately accessible at the point of need, not siloed between systems.
By unifying patient data, a Data Orchestration layer would provide clinicians with comprehensive information on their patients and their medical history, no matter where they’re registered. When patients call up in emergency situations, call handlers don’t need to waste valuable time trying to extract that information from shocked and traumatized callers. Nationwide health data can be brought into a single location, allowing authorities to monitor developing health situations at the regional or national scale.
The outcomes for healthcare would be transformational:
- When doctors have access to all the information they need immediately, patients don’t have to repeat intimate details, and neither are details forgotten. The result is quicker consultations, more accurate diagnoses, and shorter GP wait-lists.
- When patients call up in emergency situations, call handlers get immediate access to associated patient records and medical histories. These can be passed to paramedics to support immediate care.
- At the regional and national level, comprehensive pooling and monitoring of health data allows for large-scale health trends to be identified. This is invaluable when it comes to identifying and containing potential epidemics.
From the moment of go-live, a Data Orchestration layer would deliver transformational efficiencies for the NHS. And that’s just the beginning.
NHS Data Orchestration Lays the Foundations for AI Adoption
At its core, Data Orchestration is about integration. It’s about linking diverse systems together to put data to work. And one potential use for that data is powering AI transformation.
It’s no secret that AI is going to change the way healthcare operates. Talk of AI doctors might be a bit far-fetched, but more small-scale solutions are already delivering value for clinicians. AI transcription and summarization features, for instance, allow clinicians and call handlers to focus on the patient during consultations, whilst an AI populates essential meeting details and summary points to systems of record. The result? A greater focus on patients, a better patient experience, and more time to focus on the next patient.
AI transformation begins with data. A Data Orchestration layer supports that in several critical ways:
- For AI to be used effectively, it needs to be able to view and edit patient data. When patient data is stored across hundreds of different EPRs, it’s not as simple as plugging an LLM tool in through API and letting it run. You need a comprehensive access point, or you’ll have to create hundreds of different API integrations for every AI tool you want to deploy – that’s a technical debt you’ll never pay off.
- To get better at supporting clinicians and patients, AI needs to be trained to handle healthcare contexts. To make that training possible, it needs data in a single, digestible format. It’s not just about making different systems accessible; it’s about making the data within them readable.
- With the data foundations laid, the AI horizons open up. As AI technologies evolve beyond what we can imagine today, new use cases and new requisite needs will emerge. We can’t predict what our technology might look like twenty years from now – we can predict that the success of that tech will depend on the steps we take today.
Data Orchestration lays a foundation for the future, but to be effective, that foundation has to be built on experience.
