Looking Glass: Tech trends shaping the UK health and social care sector

The UK health and social care sector is at a pivotal moment. Facing relentless challenges — including tight fiscal constraints, organizational uncertainty, stalled productivity, an elective care backlog, and an aging population with escalating demand for services continuing to strain the system — leaders more than ever are looking to technology to deliver better outcomes for patients, clinicians and communities. 

The latest Thoughtworks Looking Glass report identifies technology trends that promise to reshape industries globally, we’ll explore how these big tech trends are likely to play out in the health and social care sector nationally and locally, and the critical role they might serve in supporting the government strategy to shift from hospital to community, analogue to digital and treatment to prevention. 

This article serves as a sector-specific guide, highlighting the tech trends most likely to impact the future of UK health and social care, and offering insights into how senior leaders can prepare their organizations to thrive in a world of rapid technological change.

Operationalizing AI to transform care delivery

Artificial intelligence (AI) is already making strides in healthcare, and the Looking Glass report underscores its growing potential to revolutionize care delivery. For the NHS, operationalizing AI means more than piloting machine learning models; it requires embedding AI in workflows to unlock efficiency, reduce staff workload and improve patient outcomes.

Examples include:

• Population health: AI has the potential to significantly transform population health management by shifting it from a reactive, retrospective system to a proactive, predictive and data-driven approach. By analyzing vast amounts of health data in real time and identifying patterns that would be invisible to humans, AI can support earlier disease detection, risk stratification, and resource allocation. This will enable earlier disease prevention, more efficient healthcare planning, and targeted public health interventions - ultimately improving patient outcomes and easing pressure on hospitals. Beyond data science teams, there’s also a powerful opportunity to empower people across the NHS to tap into the wealth of data available. By making insights more accessible, staff at all levels can directly improve patient care in a more responsive way, reducing delays and driving better outcomes across the board.
   

• Demand forecasting: AI-powered tools can analyze historical and real-time data to predict patient inflows and optimize staff deployment, especially in critical areas like emergency departments. The NHS is using AI to predict patients who are at risk of becoming frequent users of emergency services so staff can get them more appropriate care at an earlier stage. The intervention will ensure that thousands of people get the support they need earlier, while also reducing demand on pressured emergency departments.
   

• Personalized medicine: By interpreting genomic data at scale, AI could enable tailored treatment plans for patients, help patients better understand their conditions, care choices and treatment plans and improve outcomes for conditions as diverse as cancer and rare diseases.
   

• Administrative support: Virtual assistants powered by AI cannot replace the expertise and judgment of clinicians, they can support safer, faster, and more efficient patient navigation. Virtual assistants can help automate repetitive clerical tasks, such as appointment scheduling or claims processing, freeing staff to focus on direct patient care. Reducing unnecessary and inefficient care pathways will reduce waiting lists and improve the patient experience.

The priority should be to accelerate the infrastructure, governance, and regulation necessary for the responsible adoption of AI, emphasizing ethical data use, benefit measured across the end-to-end pathway, and seamless integration into clinical workflows.

Strengthening the data value chain

At its heart, impactful technology in health and social care rests on unlocking the value of data. The Looking Glass report emphasizes a data-first approach, encouraging national and local organizations to continue to construct foundational data platforms to enable new efficiencies.

For the NHS, siloed and fragmented datasets can create significant operational inefficiencies. Strengthening the data value chain involves unifying these datasets, exploiting locally the value from the federated data platform and finding ways to turn raw information into actionable insights. 

Opportunities include:

• Datasets, platforms, and infrastructure: laying the foundations for AI-driven healthcare: To fully harness AI’s potential, strong foundations must be in place that includes high-quality data, robust infrastructure, and seamless interoperability. This must be built around the Federated Data Platform (FDP) and a unified Digital Personal Health Record (DPHR) that must deliver clean, reliable, and accessible data for AI model training and predictive analytics. 

   

• Mandate open standards and enforce compliance: The implementation of new legislation to mandate information standards for interoperability between IT systems will provide the teeth to persuade system suppliers to build systems that share data seamlessly. The critical factor in achieving this outcome will be in how the system enforces compliance in a consistent way locally and nationally across multiple contracts. Doing so will put the NHS back into the position of driving better public health outcomes nationally, not just locally.

   

• Adopting data as a product thinking at scale: Data as a product applies product development principles to data management, transforming data into a dynamic, valuable asset that meets specific needs. This approach ensures secure, consistent and accessible data. It also enhances accuracy, trust and usability. Key benefits include 'democratizing data access and supporting better patient outcomes, as well as better decision-making, improved data quality, reduced silos and faster delivery of insights. 

Strategic investment in robust data infrastructure now is crucial. It lays the groundwork for advanced technologies like AI, fully exploits the opportunities from data science and positions the NHS to create new digital only treatment pathways.

Responsible technology for equitable outcomes

With the surge in digitalization comes an urgent need to address the ethical dimensions of technology application. For NHS and public health leaders, responsible technology goes beyond compliance. It is about ensuring fairness, accessibility and transparency in every decision.

The Looking Glass report introduces frameworks that can guide organizations toward responsible tech practices. Key areas include:

• Bias in AI systems: Ensuring algorithmic fairness in healthcare solutions, particularly in diagnosis and treatment recommendations, is crucial to avoid exacerbating health inequalities.

   

• Data privacy and security: NHS organizations must ensure robust data protection, adhering to legislative frameworks. Balancing data use for improved healthcare with privacy concerns is crucial.
  Privacy-enhancing technologies can help enable responsible data processing while minimizing risks.

   

• Digital inclusion: Technology must serve as a bridge, not a barrier, for vulnerable populations. NHS leaders must consider accessibility when implementing digital tools, ensuring they work for everyone, including digitally excluded communities. Giving individuals control over their health data empowers them to make informed decisions about their care. This is especially impactful for people who speak different languages, come from communities with a history of medical mistrust or have experienced discrimination in healthcare.

Adopting responsible technology practices will allow public health organizations to harness innovation, while maintaining public trust.

Multimodal interactions for enhanced accessibility

Multimodal interaction — technology that works across voice, touch, text and beyond — has the potential to make healthcare more accessible for all. The Looking Glass report places a sharp focus on this trend, which enables user-friendly interfaces tailored to patient needs and preferences.

• Voice-activated assistants: From enabling elderly patients to manage prescriptions via voice commands to assisting clinicians in documenting care during busy shifts, voice-powered solutions can simplify complex processes.

   

• Ambient AI technology: Ambient AI works passively in real-time, analyzing conversations, monitoring patient data and automating routine tasks without disrupting workflows. Existing trials demonstrate how AI and ambient technology can significantly enhance clinicians' work environments, reduce system pressures and improve patient experiences.

   

• Language processing tools: Natural language processing capabilities can help decode clinical notes, convert data into actionable insights and support non-english speaking patients more effectively.

For healthcare providers, multimodal interactions present an opportunity to reduce friction in patient engagement through inclusive, intuitive interfaces.

Physical digital convergence for proactive care models

The convergence of the physical and digital worlds has already proven its worth in industries like automotive and retail — but what about healthcare? The Looking Glass report points to an emerging trend where physical-digital convergence drives healthcare innovation, enabling new models of care. Digital systems that understand not just their local environment but nearby potentially complimentary health care locations with the potential to deliver just-in time care and improve flow. Notable applications include:

• Digital twins in healthcare: Digital replicas of patients and systems could support research, planning and even personalized surgery preparations and care plans, allowing clinicians to test treatments in a simulated environment before real-world applications.

   

• Predictive maintenance for equipment: Real-time sensor data on medical equipment can predict when repairs or replacements are needed, minimizing downtime and ensuring continuous patient care.

   

• Smart hospitals: Internet-enabled devices in smart hospital setups can help track assets, automatically adjust energy efficiency and even assist in patient fall-prevention strategies.

To unlock these opportunities, healthcare organizations need to invest in infrastructure and prepare staff for hybrid models of care.

Preparing the NHS for the future of health and social care

The Looking Glass report reinforces an essential truth for decision-makers in the NHS and UK health sectors at large: leveraging technology isn't just about optimizing operations, it's about transforming patient care and opening up data to a standardized interoperable model to enable seamless care, in any setting, when patients have time-critical needs. While the trends discussed here won't mature overnight, their trajectory is clear. Preparing now will make the difference between organizations that thrive in this tech-driven future and those that struggle to keep up.

For senior leaders in the NHS, the next step is to determine which of these trends aligns best with their organizational goals. Whether it's a focus on scalable AI, robust data platforms, or ethical practices, clarity of vision and incremental implementation will guide the way forward.