Evaluating innovation in adult social care

England's social care system has faced chronic underfunding for decades. Nearly six million unpaid carers now support family and friends across the UK, and the thresholds for publicly funded care keep rising.

The Covid-19 pandemic made a difficult situation worse – and in response, central government invested heavily in digital innovation for social care. Local authorities began piloting new technologies, from virtual reality to falls detection sensors. But piloting technology is one thing. Understanding whether it actually works in care homes – and adapting it until it does – is another.

Our approach and partners

ARC OxTV established a research partnership with Innovate Oxfordshire, the innovation hub of Oxfordshire County Council, to bring independent evaluation to technology pilots in adult social care. This partnership has so far produced two projects.

The first (2021–22) evaluated a virtual reality system developed by Motus VR (previously ROVR Systems) designed to support the physical and social wellbeing of care home residents. The second (launched 2025, ongoing) is documenting the early implementation of sensor-based falls detection technology from Vayyar and its UK distributor ICON across five Oxfordshire care homes, working alongside Buckinghamshire, Oxfordshire and Berkshire West Integrated Care Board (BOB ICB).

What we found – and why it matters

Both projects revealed a consistent lesson: technology designed elsewhere must be reshaped to fit the realities of social care.

1. Care home staff drove a fundamental redesign of the VR system. The original platform required users to stand inside an enclosed unit. Staff raised safety concerns for residents with limited mobility, prompting Motus VR to develop a seated version – which proved more beneficial for people with a range of physical and cognitive impairments.
2. Infrastructure gaps forced practical innovation. Many care homes lacked reliable Wi-Fi. Rather than treating this as a barrier, the supplier adapted the product to operate without it – making the technology viable in a wider range of settings.
3. Falls detection technology needed context-specific adaptation. Each of the five participating care homes encountered different technical challenges, depending on how well existing systems – staff recording devices, emergency call infrastructure – integrated with the new sensors. The evaluation helped identify and address these friction points.
4. Regular feedback loops between technology suppliers, council project leads, and care home managers proved essential. In both projects, structured dialogue led to tangible changes in the technology, making it better suited to the people and settings it was designed to serve.

What this means

The VR project resulted in a commercially available system that encourages physical movement and social engagement for people with complex care needs – now accessible to individuals and care organisations. The falls detection evaluation has already changed how data from the sensors is communicated to care staff, making insights more actionable. If the technology delivers on its promise of earlier, real-time identification of falls risk, the longer-term benefits for residents and the care system could be substantial.

What needs to happen next

These projects demonstrate that technology can improve care quality in social care settings – but the evidence base remains thin. Individual pilots generate useful learning; they do not yet provide the scale of evidence needed to inform strategic funding and service delivery decisions across the system. Commissioners, funders, and local authorities need to invest in larger-scale evaluations that can build the case for – or against – rolling out specific technologies more widely.

Lessons for future research

Both projects highlight the value of embedding independent evaluation from the outset of technology pilots. The iterative feedback process – where research findings fed directly back to suppliers and project leads during implementation – produced better technology and more relevant evidence than a conventional end-of-project evaluation would have done. This model of researcher-as-partner rather than researcher-as-assessor is particularly suited to the fast-moving, resource-constrained world of social care innovation.