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The latest workforce census from The Royal College of Radiologists, recently featured by Digital Health, highlights an encouraging trend: AI adoption in radiology continues to increase as NHS organisations seek new ways to improve productivity and manage growing demand.
It’s a positive sign that healthcare is embracing AI. But as we read the findings, one thought kept coming back to us.
One of the most interesting themes emerging from the RCR findings is the opportunity to support the operational processes that underpin patient care. Every referral, appointment and clinical handover forms part of a wider care pathway, where hundreds of individual activities work together to move patients through the healthcare system. Improving these workflows not only helps ensure patients receive the right care at the right time but also releases valuable clinical capacity for the work that matters most.
As the Royal College of Radiologists points out, administrative and operational workflows remain an area where AI has significant untapped potential.
We believe this is where some of healthcare’s greatest productivity gains still lie.
Every improvement in a care pathway has the potential to make a difference. When AI, intelligent automation and workflow orchestration are applied to the operational processes that support patient care, NHS organisations can reduce repetitive administrative work, improve consistency and give clinicians more time to focus on patients.
Turning opportunity into practice
The good news is that this isn’t simply a future ambition. It’s already happening.
One example is the Radiology Referrals Vetting AI Agent developed by SS&C Blue Prism and deployed at Sandwell & West Birmingham NHS Trust. The solution demonstrates how AI can support imaging referral vetting while keeping clinicians firmly in control.
Rather than replacing clinical judgement, the AI agent works alongside existing radiology teams. It reviews incoming referrals, checks clinical information against local policies and guidelines, identifies duplicate requests and prepares structured recommendations for clinician review. Straightforward referrals are progressed in seconds, while more complex cases are escalated with the relevant clinical context attached, ensuring governance and human oversight remain at the centre of every decision.
The results demonstrate what’s possible when AI is integrated into a connected clinical workflow rather than a standalone tool.
At Sandwell and West Birmingham NHS Trust, the solution is expected to return approximately 3,000 clinical hours every year, reduce referral processing time by 75%, autonomously resolve 80–90% of imaging referrals, and reduce GP feedback times to under one hour. Most importantly, those hours are being returned to radiologists so they can spend more time on complex reporting, urgent cases and patient care.
If you’d like to see how the solution works in practice, you can watch the Imaging Vetting AI Agent demonstration and explore the Sandwell and West Birmingham NHS Trust case study.
Looking beyond individual AI projects
As AI adoption continues to accelerate across the NHS, the conversation is naturally evolving.
Rather than asking “Where can we use AI?”, healthcare organisations are increasingly asking “Where can AI, automation and intelligent workflows help us deliver better care?”
For us, that’s where the greatest opportunity lies.
Perhaps the most interesting question is no longer how many AI solutions an organisation has adopted, but how those technologies are supporting everyday clinical practice. When operational processes become more connected and efficient, clinicians gain more time to focus on patients and organisations are better placed to meet growing demand.
Whether it’s imaging referrals, outpatient pathways, waiting list management or clinical administration, the most impactful innovations are those that connect seamlessly into existing care pathways and help healthcare professionals spend less time on repetitive tasks and more time caring for patients.
Continue the conversation
If you’re exploring how AI, intelligent automation and workflow orchestration could support your radiology or diagnostic services, we’d love to continue the conversation.
Visit our NHS Healthcare page to discover how Digital Workforce is supporting NHS organisations in delivering more efficient, connected care through intelligent automation, AI and agentic AI. You can also join our NHS Community, where healthcare leaders exchange real-world case studies, practical insights and experiences from across the NHS.
If you’re looking to deepen your understanding of AI and healthcare automation, explore agentacademy.ai for on-demand learning, webinars and practical resources.
Later in autumn, we’ll host a dedicated webinar exploring how AI agents and intelligent automation can support imaging referral vetting and broader diagnostic pathways. We’ll share practical NHS experiences, lessons learned and discuss how organisations can identify where these technologies could deliver the greatest impact.
We also offer NHS organisations a complimentary imaging referral workshop and opportunity assessment.
Together, we’ll explore your current referral workflow, identify opportunities to reduce administrative burden and estimate how much clinical time could be released through AI-supported imaging referral vetting. Whether you’re just starting to explore AI or already have initiatives underway, the workshop provides a practical way to understand where the greatest opportunities may exist within your organisation.
If this topic resonates with you, we’d love to continue the conversation. Drop us an email 
The post AI in radiology is growing. The next step is transforming the workflow around it. appeared first on Digital Workforce.
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Digital Workforce has acquired the Agentic AI for customer service business of Front AI Oy, a Nordic leader in customer service automation. The transaction is a business purchase, and the business transfers to Digital Workforce on July 1, 2026. Front AI continues as an independent company.
With the purchase, Digital Workforce expands agentic AI and virtual customer service agents to its process automation and orchestration. Digital Workforce can now transform and orchestrate customer service processes more extensively.
- Built for regulated industries. Banking, insurance, and the public sector require control, compliance, and data governance that are core to Digital Workforce’s business.
- One managed service. Customer service processes are offered service as software. Customers have one contract, with a single point of accountability across the services and technologies.
- Scales with demand. Customer service keeps pace while staying personal. Customers get faster service, and organizations can provide premium service without growing the team.
- Voice is ready also for the Nordics. Automation meets people in natural spoken conversation, also in Nordic languages.
Around 30 customer contracts and the team of 8 people transfer to Digital Workforce with the business.
Jussi Vasama, CEO of Digital Workforce, comments:
“I am excited for this major accomplishment and the potential it opens for our customers. Digital Workforce is built on two things: productized services and deep industry understanding. We use both to orchestrate complex business processes for large enterprises, the public sector, and regulated industries. These organisations now want to transform their operations and disrupt the way they collaborate with their customers. Agentic AI and voice are key technologies in delivering premium interactions.”
Jari Annala, Founder and CEO, Front AI, comments:
“We built a strong agentic AI business, with our customers at the heart of it. Digital Workforce is the right new home for it. Our customers keep the same team and the same service, now with deep automation and process orchestration expertise behind them. Our people gain a stronger platform to apply their expertise. We are proud of what this team achieved, and confident that agentic AI will go far as part of Digital Workforce.”
Media enquiries
Digital Workforce Services Plc
Jussi Vasama, CEO
Tel. +358 50 380 9893
Laura Viita, CFO
Tel. +358 50 487 1044
Investor relations | Digital Workforce
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SmartThings Safe Premium is powered by Arlo, a third-party partner that operates the professional monitoring center and coordinates emergency dispatch on our behalf. Feeling safe, whether at home or on the go, shouldn’t take more than a tap. With SmartThings Safe Premium, users can instantly send help requests, from inside the SmartThings app, to Arlo-powered […]
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Upcoming Changes to the SmartThings API Over the last several years, the SmartThings platform has grown into one of the most robust orchestration layers in the smart home industry, with over 460M+ registered users and hundreds of WWST partner brands — and our API is the gateway that connects third party apps and platforms to […]
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4.6.2026 Care Pathway Automation in Practice: Lessons from Helsinki University Hospital’s Cancer Care Implementation.
This article is a reflection on a Presentation by Finland’s Largest Hospital District, HUS: Results and Future Opportunities of Care Pathway Automation. Author Juha Nieminen is Global Head of Healthcare at Digital Workforce and a member of the executive leadership team.
At a recent healthcare IT event in Helsinki, HUS representatives Administrative Chief Physician Meri Utriainen and Planning Specialist Johanna Pakarinen shared their experiences of automating end-to-end care pathways. The case example focused on a breast cancer follow-up solution, for which Digital Workforce serves as the contracted supplier.
When a customer shares two years of production experience, it is worth listening carefully. I was particularly interested in three things: the tangible results achieved through automation, the unexpected effects of implementation, and the extent to which HUS believes this operating model can be applied to other care pathways. In this article, I reflect on the key observations and lessons I took away from the presentation.
The presentation examined HUS’s breast cancer follow-up solution from three perspectives:
• the initial challenge
• measured production outcomes
• scalability and potential use cases
Challenge: The Administrative Burden of Care Pathways
Breast cancer follow-up is HUS’s largest long-term post-treatment monitoring programme. After completing active treatment, thousands of patients remain under specialist follow-up, with monitoring programmes that can extend for up to ten years.
The follow-up pathway consists of recurring activities such as imaging, laboratory tests, outpatient appointments, symptom assessments, and patient communications. Managing these activities across a large patient population requires extensive coordination, creating a significant administrative burden and increasing the risk of delays and backlogs. HUS openly described how the COVID-19 pandemic further highlighted the need for better operational control, forecasting, and resource management.
From the patient perspective, follow-up should be timely and predictable. For clinicians and care teams, however, delivering that experience requires extensive coordination, communication, and administrative effort. Once again, this case highlights that a significant portion of healthcare’s productivity challenge stems not from clinical decision-making, but from orchestrating the fragmented workflows, communications, and administrative activities that enable care delivery.
How The Problem Was Addressed
HUS sought to shift towards a model in which the entire care pathway is designed upfront, with automation orchestrating its execution and escalating to clinicians only when clinical input or decision-making is required.
In addition, there was a clear ambition to give patients greater involvement in their own care planning by enabling self-service appointment booking and allowing them to choose their follow-up approach—either symptom-driven or scheduled routine visits.
Measured Impact and Results
HUS replaced a manual operating model with a single configurable care pathway process that orchestrates patient flow and automates administrative tasks.
The solution has been in production for two years. Here are the key figures shared by Meri and Johanna:
- 6,909 patients on an automated care pathway
- 95% of all manual tasks in patient follow-up automated
- 52% of patients chose symptom-based follow-up, leading to a significant reduction in nursing visit volumes annually
- 47% reduction in inbound calls
- Over a three-week measurement period, automation executed 6,768 tasks, with only 1.2% escalated to clinicians
A particularly notable finding relates to the reduction in inbound calls. HUS had expected demand to increase as outpatient visits decreased, based on the assumption that patient uncertainty would grow. However, the opposite occurred. When follow-up is timely and patients have clarity on what will happen next, the need for additional contact is significantly reduced.
For patients, care pathway automation is experienced as timely communication, self-service appointment booking, and selection of follow-up mode. Communication channels remain unchanged—automation executes tasks through HUS-defined channels and can also use traditional channels such as letters where necessary.
The main value of care pathway solutions lies in reduced waiting times and delays, more reliable and timely follow-up, and enabling clinicians to focus more on patients requiring urgent clinical attention.
Scaling The Impact
Although the results presented by Meri and Johanna were impressive, a more interesting question is how widely the same operating model can be applied across other care pathways. In long-term patient monitoring, similar structural patterns tend to repeat, suggesting that HUS’s experience is not limited to a single patient group.
The presentation also identified several emerging use cases, including medication monitoring in dermatology and neurology, imaging-based follow-up in other cancer types, and monitoring of genetic risk carriers and meningioma patients. Further opportunities were highlighted in care coordination between specialist and primary care, such as secondary prevention of coronary artery disease events.
Based on HUS’s experience-based estimates, the scalability potential of the model is significant:
• Over 95% of suitable patient flows can be transitioned to automated pathways
• Over 95% of tasks within these pathways can be handled by automation
• Over 95% of imaging findings are classified as non-actionable and do not require intervention
• Approximately 50% of patients prefer symptom-based contact over scheduled follow-ups
Surprises and Key Learnings
At the end of the session, Johanna and Meri reflected on key lessons from the breast cancer follow-up implementation. Three particularly important insights stood out to me:
“One directive, ten years” framework
Replacing periodic decision-making with a single configurable workflow is key to scalability. The care pathway is implemented as a core template, with variations defined through parameters for different diseases, patient groups, and care plans.
47% reduction in inbound calls as an unexpected outcome
Healthcare automation initiatives are often justified by cost savings and efficiency gains. However, the most significant benefits are frequently those that cannot be predicted in advance. In this case, freed capacity was greater than expected, and more focus on change management could have improved early utilisation of that capacity.
“No rocket if a bicycle is enough”
The breast cancer solution is based on algorithm-driven process automation, not AI. It does not make clinical decisions and is not a medical device; instead, it orchestrates and automates scheduling and administrative tasks, while also managing work coordination in a single seamless flow.
A key lesson is that AI should not be used where simpler automation is sufficient. Instead, it should be applied where it adds real value. HUS identified applicable areas such as document processing, imaging, structured data capture, and referral handling.
HUS is also quite advanced in this area. Digital Workforce has been involved in HUS’s AI-based referral triage solution, which processes and classifies more than 300,000 specialist care referrals annually.
The key principle is simple: first design the process, then select the most appropriate technology for each step. In many cases, the best outcome is achieved through a combination of automation and AI, supported by strong orchestration of the overall system.
Summary
After leaving the session, I reflected on how much of healthcare’s productivity challenge is still driven by fragmented processes, limited coordination, and the burden of communication and administrative work. HUS’s experience shows that these tasks can be extensively automated without shifting clinical decision-making to technology.
As clinicians’ time is freed for clinical work and care pathways become more transparent, predictable, and timely, the benefits extend to patients, professionals, and organisations alike. In my view, transforming care pathways by leveraging automation and advanced process orchestration to create seamless workflows that deliver the core objective—better care and better outcomes at lower cost—is set to become one of the key development directions in healthcare in the coming years.
HUS’s example is compelling: two years in production, 6,909 patients on an automated pathway, and 6,768 tasks in three weeks—only 1.2% of which required manual intervention. While these results are significant for a single patient group, the real impact lies in the scalability of the model across other pathways and organisations.
Key Learnings:
- Automation delivers the greatest value at the level of orchestrating entire care pathways
- The most significant benefits are not always predictable in advance
- Change management is as important as the technology itself
- Many care pathways share a common underlying process logic, enabling solutions to be scaled
- AI is not a universal solution; automation and AI each have their strengths and can be used together. The starting point should always be clear process design
Author: Juha Nieminen is Global Head of Healthcare at Digital Workforce and a member of the executive leadership team. He has over two decades of experience in sales leadership and business development across healthcare, IT, and other industries. In his current role, he focuses on healthcare process automation and care pathway solutions. He holds a Master of Science in Engineering (Industrial Engineering and Management).
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The same trusted NHS team, now backed by Digital Workforce
e18 Innovation is now part of Digital Workforce, bringing together NHS pathway automation expertise with broader healthcare automation, AI and managed service capabilities.
For NHS organisations, this means continuity where it matters, combined with greater scale, resilience and innovation.
What remains the same?
- NHS focus
- Same specialist healthcare team
- Same trusted customer relationships
- Practical delivery approach
- Commitment to measurable outcomes
- Ongoing engagement with the NHS automation community
What is enhanced?
- Access to a wider range of automation and AI capabilities
- Broader healthcare expertise and access to broader range of proven approaches from the UK, Nordics and the US
- Greater delivery capacity and resilience
- Managed services and ongoing support
Access to broader automation capabilities and solution models built to scale
NHS organisations now benefit from greater scalability in both solutions and delivery models, helping automation programmes move beyond individual use cases towards wider, sustainable transformation across services.
Specialised solutions for care pathways and end-to-end process transformation
Digital Workforce brings globally leading expertise in end-to-end process transformation and orchestrated care pathway solutions. In collaboration with leading Nordic university hospitals, the organisation has developed configurable care pathway solutions that automate and coordinate entire patient journeys, delivering significant results in live healthcare environments.
Designed to support long-running pathways rather than individual tasks, these configurable solutions can be adapted to a wide range of use cases, including patient monitoring, screening programmes, diagnostics and outpatient care, helping NHS organisations improve patient flow, increase visibility and reduce administrative burden across the patient journey.
Scalable delivery model: multi-technology platform and 24/7 managed service
NHS organisations now have access to Digital Workforce’s Outsmart cloud platform, bringing together all the technologies and services needed for process transformation within a single platform. Combined with 24/7 managed services, Outsmart provides a secure and scalable foundation for automation programmes.
Designed to simplify both delivery and growth, the platform includes pre-built components that help organisations achieve results faster while reducing implementation complexity. A flexible consumption-based model allows organisations to scale up or down as needed, paying only for the capacity they use.
Applying Digital Workforce capabilities to NHS priorities
The Digital Workforce team continues to focus on helping NHS organisations address some of their most significant operational challenges and priorities.
Including->
Reducing waiting lists and improving access
Orchestrated pathway solutions help automate and coordinate referrals, waiting lists, patient communications and outpatient pathways, improving access and reducing delays.
Improving patient flow
By connecting processes across teams, departments and systems, pathway solutions help reduce bottlenecks, improve visibility, enable more effective resource planning and support smoother patient journeys.
Supporting cancer and diagnostic pathways
Configurable pathway solutions support complex, long-running pathways, helping improve coordination, tracking and operational efficiency. These proven solutions have already delivered significant results in cancer care and can be rapidly configured to support a wide range of NHS pathways.
Transforming outpatient care
Proven pathway models can be configured to support a wide range of outpatient, monitoring and follow-up pathways, including patient communications, screening programmes, diagnostics and long-term condition management.
Increasing productivity and reducing administrative burden
Automation, AI and pathway orchestration help reduce manual work, streamline administrative processes and enable staff to focus on higher-value activities.
Efficient and impactful scaling of automation programmes
The Outsmart platform brings together all the technologies needed for process transformation in a single managed environment, reducing complexity and eliminating the need to manage multiple suppliers or rely on a single technology. Through one flexible cloud platform, organisations gain access to market-leading automation, process orchestration and AI technologies, along with pre-built components and proven solution models that support faster deployment and improved outcomes. Combined with a flexible consumption-based model and managed services, organisations can scale securely with demand while helping to optimise costs.
Supporting population health and proactive care
Configurable pathway solutions can be applied to screening programmes, patient monitoring and preventative care pathways, supporting more proactive and preventative models of care.
Get in touch with our team of experts
e18’s NHS expertise is now combined with Digital Workforce’s international healthcare experience, creating a stronger healthcare automation and AI capability for NHS organisations.
If you have any questions or would like to explore how Digital Workforce could support your organisation’s transformation journey, we’d be pleased to hear from you.
Contact our team of experts here.
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