Australia has entered a new era in aged care. With the rights-based Aged Care Act and the Support at Home program now in place, expectations are shifting from “having policies” to consistently demonstrating safe, respectful, evidence-backed practice.
That shift matters because it changes the operating reality. Instead of occasional audits and periodic reporting, providers are moving towards a world where evidence needs to be captured in the flow of work, not rebuilt after the fact. At the same time, the workforce is tight and demand is rising, which means any new requirement that adds friction will be felt immediately on the frontline.
So, rather than asking “what new technology should we buy?”, it helps to ask a more useful question:
What patterns reduce workload while improving quality and oversight?
Other health systems have been forced to answer that question under similar pressures. Their solutions vary, but their lessons are surprisingly consistent.
A simple way to think about innovation in aged care
In practice, innovation tends to succeed when it does three things at once:
- reduces duplication (record once, reuse)
- improves visibility (leaders can see what’s happening without chasing)
- fits real workflows (staff can use it while moving, not only at a desk)
With that in mind, the global examples below become less about novelty and more about operational design.
Singapore: Use AI to remove the documentation load
Singapore has treated AI as a capacity strategy, backing it with major investment, including over US$730 million committed to boost national AI capability.
However, what’s more instructive than the headline figure is the use-case focus. The strongest applications are not “AI everywhere”, but AI placed where time is being lost.
A good example is SingHealth’s Note Buddy, which transcribes and summarises clinician–patient conversations in real time. The benefit is plain: if documentation happens during the interaction, less work spills into evenings, handovers are clearer, and the service is less dependent on memory and rushed end-of-shift notes.
Similarly, Singapore has leaned into predictive models such as JARVIS supporting screening for chronic conditions like diabetes and hypertension. This matters because earlier detection reduces avoidable deterioration, and in turn reduces avoidable workload.
What carries across: AI earns adoption when it returns time and reduces cognitive load, rather than adding another system to manage.
UK: Build the digital foundations before anything “advanced”
The UK has pushed hard on digital basics in adult social care, because without a consistent record system, everything else becomes hard to scale.
By January 2025, 75% of adult social care providers had adopted digital social care records.
That kind of progress matters because it changes what’s possible operationally. Once a service has digital records and consistent capture, several improvements become easier at the same time:
- reporting becomes routine rather than a scramble
- incidents and actions can be tracked through to closure
- audit trails exist by default, not as a manual rebuild
- quality oversight becomes visible without constant follow-up
On the other hand, when records are still scattered across paper, PDFs and disconnected systems, every new requirement becomes a manual task. Over time, that is how well-intended reform becomes workforce pressure.
What carries across: digital maturity is not a “tech project”. It’s an enabling condition for quality, safety, and sustainable compliance.
The Nordic region: Standardisation makes change cheaper and faster
Nordic countries have approached innovation through alignment. Through the Nordic Digital Health and Evaluation Criteria program, multiple systems agreed on shared benchmarks for evaluating digital health technologies.
Why does that matter for providers? Because fragmentation creates hidden work. When systems do not align, staff end up bridging the gaps through re-entry and reconciliation, and suppliers charge more for bespoke integration.
Sweden provides a simple illustration of what mature digital infrastructure enables, with 99% of prescriptions being digital.
What carries across: standardisation is not bureaucracy. It is how you reduce the ongoing “integration tax” that shows up as duplication, errors, and slow change.
Japan: Technology that protects staff and preserves workforce capacity
Japan’s demographic pressure is severe, with 36.25 million people aged 65 or older in 2024. In response, it has invested in assistive technology and robotics aimed at sustaining care delivery even as workforce supply tightens.
It began subsidising care robots in 2015, and by 2016 about 15% of nursing homes had adopted robots. More recently, prototypes such as AIREC have been demonstrated for supervised care manoeuvres.
The point is not that every provider should buy robots. The point is the design intent: reduce physical strain, lower injury risk, and keep experienced staff in the workforce longer.
What carries across: in a workforce shortage, the most valuable innovation is often the one that prevents your workforce from shrinking further.
What this means under Support at Home
Support at Home is designed to scale, with around 1.4 million people expected to benefit by 2035. As demand rises, small inefficiencies become major constraints.
Across these global examples, four principles repeat:
- Sustained capability beats one-off pilots
- Foundations first: digital records and mobile capture
- Standards enable scale and reduce duplication
- Workflow fit decides adoption
If you want to act now without launching a major program, start where friction is highest:
- mobile evidence capture at the point of care
- connected data so reporting and audit trails are automatic
- AI-assisted documentation that reduces after-hours admin
- fewer disconnected systems and fewer manual handovers
Where Sognos can help
Sognos builds Microsoft-powered solutions designed for Australian care environments – mobile care apps that support point-of-care evidence capture, connected workflows built on Microsoft
Dataverse, and AI-assisted documentation through Note Mate using Microsoft Copilot patterns. The goal is practical: reduce duplication, strengthen visibility, and support compliance in a way that fits how care teams actually work.
If you are preparing for Support at Home, the most useful next step is to identify the processes that currently create the most admin drag, then redesign them so evidence and oversight happen as part of work, not after work.
