Individual doctors saving an hour each day on admin. Nurses halving the time spent on handover preparation. And informed staff leveraging key information, whilst eliminating paper. This describes just some of the immediate impact witnessed on the shift from paper records to digital noting at South Tees Hospitals NHS Foundation Trust: results that are enduring as digitisation continues to progress.

“The general ward state is undoubtedly more efficient and safer because we now have availability of standardised, legible, and complete notes,” says Dr Andrew Adair, an emergency department consultant and the chief clinical information officer for the trust. “We have links into regional systems, all accessible through one window. Our healthcare teams are not having to leave the electronic patient record to look at x-rays, radiology reports, endoscopy, outpatient letters, or to look at other hospital attendances on the Great North Care Record.”

His comments reflect benefits being realised following a South Tees Hospitals decision to deploy Alcidion’s Miya Precision platform as a trust-wide electronic patient record.

Patient flow, e-observations and assessments, electronic prescribing and medicines administration, and clinical messaging were some of the first priority areas to be digitised in the EPR programme, with significant positive implications for patient care.

But the digitisation of clinical noting that Adair describes has become one of the most significant achievements in the programme to date.

“It’s that visibility right across the system of information for the people who need it, when they need it,” says Niki Idle, digital business change manager.

The trust has so far prevented the creation of 1.8 million paper documents as a result of digitised clinical noting. “That’s 1.8 million documents through the system so far, including 102,000 discharge letters that can automatically be sent to GPs electronically,” says Idle. “We are not building up notes that require physical storage. And other than for business continuity purposes, specialist notebooks that were used to capture notes are not being printed.”

‘I can’t believe we have never had this before’

South Tees Hospitals has worked with Alcidion to effectively reinvent noting at the trust. Intuitive technology has helped with clinical buy-in.

“Compared to other digital systems I’ve used, it just looks nice. It has been laid out with clinical teams in mind. It seems like a little thing, but this is important as your first impression of the system as a clinician,” says Adair. He describes Miya Noting, a component of the EPR platform.

Deeper under the hood, nurses and clinicians at the trust have fed back positively on a system built, configured, and deployed around their needs.

“All grades of medical staff, the nursing body, and allied healthcare professionals have all been really receptive of it,” says Dr John Greenaway, a consultant gastroenterologist and the trust’s deputy CCIO.

He recalls that in other trusts clinicians had left their positions at the thought of an EPR deployment. At South Tees Hospitals one clinician who was approaching retirement had voiced similar reservations.

“As we went live, she realised that there wasn’t much she was going to have to do, she saw the advantages of it, and there were big smiles over the next few days,” says Greenaway. “‘I’m not going to retire”, she told us.”

Another nurse, initially fearful about being able to cope with new technology, changed her mind by the end of her first shift. “I can’t believe how we’ve not had this before,” she said.

Now deployed across nearly all of the trust, and with plans to soon deploy to a remaining four areas out of 38 wards, clinical noting has had widespread engagement – with further configuration ongoing to respond to the evolving needs and requests of specialty noting. In the early stages of deployment, Idle recalls how clinical educators who were there to support staff, were told they could leave early because wards intuitively understood the system.

“We’ve been fairly swept away by how people have taken to this”, adds Greenaway. “We’ve not really had the ‘hard time’ often faced in large healthcare IT deployments. That’s partly a testament to the system and partly because clinicians do not find it too painful to input the electronic information that will be so beneficial further down the line.”

Collaboration to reinvent noting

A collaborative approach between the trust and specialists at Alcidion in designing how data is captured, has helped.

The design process delivered alongside frontline clinicians has meant that the noting has been configured around user needs from day one. Comments from staff that the system “lightens the workload”, that it has “made life a lot easier” and has released “far more time to care”, have resulted.

“It feels like you are in it with your mates,” says Greenaway. “We have a common goal, working through things together.”

The intention is that around 70% of the data required on many forms could eventually be auto-populated, either from existing parts of the patient record such as demographics, or pulled through from notes captured at earlier points of the patient’s hospital encounter.

For example, ‘pull through’ of comorbidities data is not only expected to save time, but aide in clinical decisions, and in accurate coding for financial purposes, says Idle: “Every time the patient is admitted, the system will present the clinician with a list of comorbidities, asking ‘are these still all valid and present?’ It’s prompting the clinician with information that already exists.”

“We are taking the brain power out of remembering what to do and where. We get to concentrate on important patient care decisions,” adds Greenaway.

The system has been configured to create efficiencies beyond the point of care too, for example supporting data requirements for national clinical audits. This is expected to prevent the need for clinicians to manually search for information for mandatory audits, so that they can then spend more time on quality improvement.

“We can just pull that data out of the system,” says Idle. “We’ve designed forms to ensure we collect as much pertinent information as possible, rather than somebody sifting through notes to then type into another computer system. This is freeing up time to ensure audits are complete and to address concerns raised in audit data.”

The availability of data for reporting is also supporting patient safety. “Within 14 hours of an emergency admission patients should have a senior clinical review,” Idle explains. “We’ve never been able to quantify that before without searching manually through paper notes. Now we can, just as we can examine where VTE assessments have been completed. We can now pull that data, see where it’s happening, where it isn’t, and then follow up with education.”

AI: The near future

Despite positive results, Greenaway insists more is to come and soon. “I don’t think we are anywhere near realising the benefits of the Alcidion system,” he says.

AI and other smart technologies are expected in the “near future”. “I don’t think this will be long,” says Greenaway. He refers to demonstrations already made to the trust, where a clinician can dictate a summary into a microphone for AI to then populate a form, or a plan, for clinicians to approve. And he describes “ambient listening”, where AI tools can listen to consultations in the background to generate notes.

Initially the trust intends to structure options to allow staff to ask AI to generate a handover document, or a discharge letter, or to pull through certain information from multiple encounters.

Adair concludes: “What we have now is already undoubtedly so much better. Now we are planning to introduce robotic process automation to be able to bring in additional data from our comorbidities system. And we are working to integrate more data from pathology. Not having to go into a separate system for that information – for our clinicians, that’s massive.”

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“The only thing that was impossible was to do nothing.” These are the words of Terry Pirovolakis, CEO of Elpida Therapeutics, and father to Michael who was diagnosed as an infant in 2019 with an ultra-rare neurological condition, SPG50. Despite being told there was no cure, Terry moved mountains over four years to find a breakthrough gene therapy that his son and other affected children all over the world could benefit from.

Michael, Terry, and their family are not alone in facing a long, daunting journey to access life-enhancing therapy for a disease with no cure. In the European Union, less than five percent of rare diseases have at least one approved treatment.[1] It can take up to five years for adults to receive a diagnosis, and half of patients will receive a misdiagnosis first.

By 2030, the goal is to support the development of 1,000 new therapies in Europe.[2] However, rare diseases challenge traditional ways of doing business. Once a medicine is approved, organizations must launch and scale quickly, often across multiple markets. Field medical teams must keep track of complex science at a time when the volume of medical knowledge is doubling every 73 days.[3] They need to identify, engage, and provide education to relevant healthcare professionals (HCPs) and experts even though they’re harder to reach via traditional methods (Veeva Pulse data shows that in-person meetings with physicians have declined in Europe in the last 12 months).

Despite these difficulties, life sciences organizations are improving how their teams organize market access and educate prescribing doctors on new medicines. Companies with comprehensive, accurate healthcare ecosystem data and insights relating to medical experts can prepare the market pre-launch and hit the ground running to accelerate execution after launch. This helps all customer-facing teams to deliver a consistently high-value scientific exchange in which every interaction builds off the last.

Greater agility during launch

Emerging biopharmas play a key role in delivering treatments for affected patients. Of the 192 orphan medicinal products (OMPs) authorized by the European Medicines Agency (EMA) between 2010 and 2022, one in ten successful applicants was designated an ‘SME’.[4] Facing more resource constraints than their competitors (which may have sales organizations multiple times their size), early-stage companies are increasingly seeking the best customer reference data and key opinion leader (KOL) insights to become more nimble when launching new treatments.

Rich information on experts, available in CRM, supported Sweden-headquartered Sobi to launch the first and only medicine for hemophagocytic lymphohistiocytosis (HLH) — a rare, hyperinflammatory condition affecting one in 50,000 resulting in a two-month life expectancy. In the U.S., MSLs at the company now routinely use real-time intelligence to find the right KOLs, understand their interests, priorities, and activities, and consolidate scientific information and updates. “90% of MSLs found new insights for their next engagements, which is critical for a rare disease company with lean teams,” says Rich Palizzolo, executive director of CX and advanced commercial capabilities at Sobi.

An added complexity is that rare diseases often involve several specialties. MSL teams have to get up to speed quickly on multiple areas before meeting experts — while also being responsible for other (more mainstream) therapeutic areas. ADVANZ PHARMA, which focuses on specialty, hospital, and rare disease medicine, found having scientific resources and activity data in one place helped MSLs use their time efficiently. Head of CRM and Digital Solutions for Global Commercial Excellence, Andy Eeckhout, notes: “Our customer-facing teams need to be agile communicators and effectively switch to a more patient-oriented, in-depth scientific discussion than with generics. Pre-call planning is crucial for MSLs before and after launch. The more data they can find, including on past interactions, the better.”

Other companies use customer reference and patient data to improve operational agility as they launch and scale their first products across Europe. For example, one late-stage biotech leveraged its data on the healthcare ecosystem to get a head start on launch by identifying market access roles in Spain, Benelux, and the Nordic countries.

One voice to the physician

After identifying the right experts, teams can engage them more effectively by ensuring that each HCP interaction builds off the previous one. However, sales, marketing, and medical teams often use disconnected technology. As a result, 65% of HCP engagements are not synchronized.

When these teams are connected in the same system handovers are smoother, and HCPs can find answers quickly or connect with MSLs if needed. ADVANZ PHARMA introduced a pre-launch module in its CRM to help market access, medical, and commercial teams share information compliantly. Eeckhout explains: “Physicians need a direct line to the industry, so they know who to contact when they have questions. Medical and commercial teams need to talk to each other and remain agile across customer conversations.”

ANI Pharmaceuticals, which delivers treatments for certain rare autoimmune and inflammatory conditions, only had 75 days to commercialize following swifter-than-expected regulatory approval. By using an industry-specific CRM with master data management, it consolidated its view of each HCP to include interactions with medical and sales reps. “Having this information accessible within the CRM system facilitates more thoughtful and helpful conversations with providers, as well as sales teams’ success and high click-through email rates,” explains Bob Acropolis, executive director of operations and analytics at ANI.

The foundation of successful interactions is accurate reference data — on physicians, healthcare organizations (HCOs), or affiliations. If applied across functions as part of a complete life sciences-specific CRM, it helps companies speak with one voice. In most cases, data change requests (DCRs) can now be made (and resolved) in hours, so reps and field medical don’t duplicate attempts to modify account information and instead work from the same database. With greater trust and confidence in reference data, teams save time so they can focus on high-value scientific exchange.

Sharing medical content that engages

Europe’s fragmented regulatory landscape and evolving local requirements intensify the pressure on marketing teams: they must provide highly personalized, compliant medical content that field teams can share at scale with scientific experts and physicians. With a single view across the entire content lifecycle, biopharmas can streamline and speed up medical, legal, and regulatory (MLR) reviews.

To deliver highly personalized content across a large rare disease portfolio, marketing teams need clarity on which content to recommend, and when. One global biopharma uses data analytics on its global repository of promotional and medical engagement tools to support content use across 17 areas of focus (and a growing global footprint). As its head of marketing and customer engagement noted, “How we engage with HCPs is critical. We need to know what percentage of our content is being developed and relevant to support different HCPs, whose patients rely on them for their rare disease diagnosis and management.”

As a new generation of digitally-savvy HCPs comes through, companies are considering the most effective tactics to engage them. More scientifically active than their peers and four times more likely to adopt a new treatment, younger HCPs require a different mix of scientific channels and content. They seek medical insights to inform their clinical and commercial decisions, which requires close coordination between medical affairs and field medical. “Gone are the days when medical could just focus on the top-tier scientific thought leaders. The range of stakeholders has broadened, and it’s imperative to expand our engagement strategies beyond traditional experts,” says Angela Smart, director of global medical excellence and operations at ADVANZ PHARMA.

Defying the odds, then beating them

Scientific discovery continues to bring hope to patients affected by rare diseases and their families. Life-changing conditions will eventually become chronic illnesses, thanks to the efforts of organizations willing to launch in a high-risk commercial environment. Companies ranging from emerging biotechs to global biopharma are using high-quality customer reference data, deep data on scientific experts, and connected technology to identify, engage, and provide medical education to the most relevant HCPs and KOLs.

Every rare disease patient faces a daunting journey. When Terry Pirovolakis’ son, Michael, was diagnosed, his family was told he was the only child in Canada with SPG50. Life sciences will do its part to help patients defy overwhelming odds — and eventually beat them.

By Chris Moore, President, Veeva Systems Europe

References

[1] “The building blocks to make rare disease treatments more common,” European Commission, February 2022

[2] “What is Rare Disease,” EURODIS, 2024

[3] “Challenges and Opportunities Facing Medical Education,” American Clinical and Climatological Association, 2011

[4] “Trends in orphan medicinal products approvals in the European Union between 2010–2022,” Orphanet Journal of Rare Diseases, 2024

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AI is transforming medical treatment in many areas and across many diseases, not just cancer. Within oncology however, which is a particularly complex and challenging disease, AI is making an even more significant difference.

Technology is accelerating the way molecules are designed and developed in new approaches against cancer, allowing us to invent innovative molecules that could work better and safer in a shorter amount of time. This stands to bring improved treatments faster to patients.

Findings published by the WHO last year revealed that in 2022 there were an estimated 20 million new cancer cases and 9.7 million deaths. Globally, about 1 in 5 people develop cancer in their lifetime, and approximately 1 in 9 men and 1 in 12 women die from the disease. This is the scale of the challenge.

Pharmaceutical and biomedical companies are now using increasingly powerful computational methods to fight this battle, strengthening their discovery efforts with AI to help find new compounds for killing cancer. In this early-stage, pre-clinical setting, AI is being used to search for, analyse and develop compounds aiming to eliminate the disease. As such, these new computational methods are gradually increasing accuracy, speed and reliability of treatments.

How does AI drug discovery work?

Our computational platform, called Synth AI, achieves acceleration by computationally producing molecules that meet three key objectives simultaneously.

Firstly, the platform ensures that prospective molecules can be synthesised using known chemical methods. Many computational approaches suggest potential drugs candidates that can’t actually be made or have significant challenges in their synthesis. Synth AI avoids this, ensuring the molecules can be not only made but also scaled using known technologies. This significantly boosts the chances of these treatments being successful when they reach clinical or commercial use.

The third key criterion is that Synth AI optimises the chances that these molecules have the desired biological effect. The platform delivers molecules that are not only synthesisable and scalable but also stand to be biologically effective, critically increasing the overall accuracy, speed and reliability of the drug discovery process.

These three metrics – ensuring the molecule can be active biologically, that it can be made in the laboratory, and that it may be scaled cost-effectively – are making these treatments more likely to come to market. This potentially more cost-effective drug development is a positive prospect for both patients as well as for investors in the space.

Balancing efficacy with side effects in oncology

AI drug discovery is playing a crucial role in improving efficacy, dose response and toxicity in cancer treatment as well.

Considering the unmet need and the lethal consequences of cancer, efficacy is typically prioritised, namely how effective the treatment is at killing cancerous cells. However, the market is being populated with an arsenal of anti-cancer agents which have side effects that remain a major burden for patients.

Our efforts, through the use of AI, are focused on improving efficacy while overcoming the side effect disadvantages that plague many existing treatments.

This comes back to the precision of AI.

As a concrete demonstration of how computationally sourced molecules are being validated, our initial tests against cancer in mice have produced clear evidence of tumour regression and a good safety profile. Remarkably, this is being achieved with a drug candidate that has not even been optimised in the lab.

This points to the chemical scaffolds identified using the proprietary AI computational component already producing molecules with significant advantages that would normally be far behind in the optimisation curve. The benefit for patients, physicians and also investors, is that because treatments are starting their journey to the clinic at a more advanced point, the time and capital at risk during the optimisation phase is reduced overall, speeding up the process and prospectively providing faster economic returns.

The fact that AI drug discovery can achieve such superior results with an unoptimised drug candidate means that we’ve jumped ahead in time compared to what would have normally been required to reach this point.

What AI means for patients and cancer treatment

AI is therefore getting better, more effective and safer treatment to cancer patients more quickly with the associated reduced risk for investors.

When such a validated, strong technology is devised and applied by a leading scientific team, the result can be potential treatments which begin their life cycle as if they’ve been optimised over many months or years. The saved time and valuable resources for drug discovery and development companies means investment then goes further and money can be used more efficiently within the industry.

Importantly, this new approach can positively impact disease areas beyond oncology. Within our own pipeline we have additionally demonstrated the versatility of AI in creating new potential treatments also against resistant infections.

And it isn’t just us. Drug discovery efforts of other pharmaceutical and biotech companies in numerous other conditions are demonstrating the broad applicability of AI computational technology in drug discovery.

Many novel AI methods being utilised within the industry today have already been found to work for a diversity of targets, independently of the therapeutic area or the nature of the target itself.

By Dr. Alan D Roth, CEO of Oxford Drug Design

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In healthcare we often talk about digital transformation, but what truly matters is how these changes impact patient care and experience. At the Humber Health Partnership, one of the new Group structures within the NHS, we’re embarking on an ambitious journey to revolutionise how patients interact with our services, starting with one of the most fundamental aspects – appointment booking.

Our upcoming patient-led booking system represents a significant shift from traditional methods. Currently, patients receive letters and face the often frustrating experience of making phone calls to arrange appointments, leading to high rates of non-attendance. By implementing smart booking solutions that integrate with the NHS app and use text messaging, we’re putting control back in patients’ hands while ensuring we don’t digitally exclude those who prefer traditional communication methods.

This initiative goes beyond mere appointment scheduling. It’s about creating a comprehensive support system that provides patients with information about managing their health while waiting for procedures, ensuring they’re better informed and engaged in their healthcare journey.

Embracing AI responsibly

One of our most exciting recent initiatives was a hackathon exploring the potential of Microsoft Copilot, which brought together over 150 staff members from various roles – clinical, operational, leadership, and frontline nursing. The event generated remarkable insights into how AI could transform our operations while maintaining our commitment to responsible innovation.

We’re taking a measured but ambitious approach to AI implementation. While acknowledging the legitimate concerns around data protection and privacy, we’re also recognising AI’s immense potential to streamline administrative processes and enhance patient care. From generating initial drafts of discharge summaries to improving patient communication, AI presents opportunities to reduce administrative burden on clinical staff while maintaining safety and quality.

Building system-wide integration through digital innovation

Digital innovation in healthcare isn’t just about implementing new technologies within hospital walls – it’s about creating a connected ecosystem that benefits the entire healthcare system. We’re expanding our virtual ward capabilities, looking at ways to prevent unnecessary hospital admissions and improve capacity management across the system.

Our approach to digital transformation is guided by two key principles:

• Focus on foundational improvements while planning for strategic change
• Deliver continuous improvement rather than waiting for perfection

This is exemplified in our Electronic Patient Record (EPR) programme. While we’re working towards procuring a new system, we’re simultaneously implementing improvements that can benefit patients and staff today. This dual approach ensures we maintain momentum while building towards larger strategic goals.

Data as a strategic asset

Understanding the critical role of data in modern healthcare, we’re investing in new data warehouse infrastructure to improve our analytical capabilities. This investment will enable better decision-making and support our broader digital transformation initiatives, ensuring we can effectively measure and improve patient outcomes.

Success in digital transformation requires more than just implementing new technologies though. It demands careful alignment with organisational strategy while maintaining focus on immediate improvements. We’re ensuring that digital considerations are embedded in all strategic conversations, particularly when discussing new models of care delivery or system-wide changes.

Our group strategic framework, published in July, represents a comprehensive approach to digital integration across our healthcare system. At its core, we’re focused on eliminating system duplication and ensuring interoperability between our various platforms. This goes hand-in-hand with our vision of moving towards a single architecture that can support our entire organisation efficiently and effectively. We’ve made it a priority to engage users in setting these priorities, ensuring that our digital transformation reflects the real needs of those delivering and receiving care.

A key component of our strategy is enabling virtual hospital models, which we believe will be crucial in meeting future healthcare demands. As we look ahead, our focus remains on delivering tangible benefits to patients while building the foundations for future innovation. The integration of AI, expansion of virtual care and implementation of patient-led booking systems are just the beginning of what promises to be an exciting period of digital evolution in healthcare.

As we continue this transformation journey, our focus remains on delivering tangible benefits to patients while building the foundations for future digital innovation.

Don’t miss the opportunity to hear more about our digital innovation transformation journey and participate in the discussion about the future of healthcare technology. Join me at Digital Health Rewired 2025, where I’ll be sharing detailed insights about our experiences and the lessons learned along the way.

By Andy Haywood Group Chief Digital Officer at NHS Humber Health Partnership

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Now available across Europe for the first time, the technology is supported by AI that has been tested on hundreds of thousands of samples. Leading haematology specialists have welcomed the technology, that is designed to help laboratories carry out more accurate and efficient platelet counting – a key process in the detection of many serious illnesses.

Accurate platelet count testing is one of the major challenges facing laboratories. Inaccurate counting can lead to misdiagnosis or missed diagnosis, and delayed treatment of a range of potentially deadly conditions – including acute massive haemorrhage, coagulation problems, infections, autoimmune diseases, and cancers.

A false low platelet count, known as pseudothrombocytopenia, can occur during platelet aggregation or due to improper sample handling. It may also arise in samples with large or giant platelets that conventional methods cannot identify. As a result, test results may show low platelet levels while the actual count remains normal.

Such misdiagnoses can lead to unnecessary anxiety, additional diagnostic tests, and potentially inappropriate medications or transfusions. Surgical delays may also occur if procedures are postponed based on inaccurate results.

Conversely, pseudothrombocytosis, or a false elevated platelet count, typically happens when red blood cell fragments or microcytes are miscounted as platelets. This can cause low platelet samples to be reported as normal or high, and normal counts to be falsely identified as elevated.

If low platelet counts are reported as normal or high, risks of bleeding in the patient may not be detected in time, delaying treatment and potentially posing life-threatening risks. Normal values being reported as high may lead to incorrect diagnoses or inappropriate treatments.

Mindray has now launched technology into European markets, designed to help laboratories respond to these challenges and overcome accuracy risks, with significant efficiencies also expected for laboratories facing rising demands.

Through the CAL 8000 Cellular Analysis Line, the company has combined platelet technologies to support high quality reporting. The technology automates platelet analysis, and also means that aggregated samples could take laboratory professionals as little as 30 minutes to report – rather than a typical two hours.

Huan Qi, Director of Clinical Research, Medical Affairs, Mindray, said: “Abnormal platelet counts are sometimes a precursor to life threatening illnesses, including cancers such as leukaemia or lymphoma. Inaccurate platelet counting can lead to significant and potentially deadly consequences.”

“Through innovative technology, we are now equipping laboratories with modern tools to enable efficient, high-quality, and cost-effective blood cell analysis. Through a combination of innovative tools, automation, and sophisticated algorithms, laboratories have the potential to enable 99.9% of samples to be reported with accurate platelet count results, without the need for manual intervention.”

The cellular analysis line includes PLT-H, a new platelet detection technology that uses high-precision optics and innovative algorithms to exclude interference and improve count accuracy without additional cost.

Self-de-aggregation technology, which involves heating, stirring and de-aggregation, is also able to disintegrate most ethylenediaminetetraacetic acid induced platelet clumping.

Samples flagged as abnormal by Mindray’s cost-effective technologies, can also be analysed using PLT-O. This fluorescent staining method for platelet detection is able to provide laboratories with accurate low-value results. When optical methods detect low platelet samples, laboratories are able to use the PLT-O instrument to automatically increase particle counting eight times without the need for re-sampling. This can greatly improve the detection accuracy of low platelet counts.

Mindray’s PLT-M technology, which is integrated into its digital morphology analyser, can be used to automatically estimate platelet counts through an advanced morphological imaging method.

Technology available in the line also includes high-definition, high-speed scanning to identify platelet aggregation samples by detecting platelets in the body, edge and tail of blood smears. Called PLT-Pro, this technology is able to scan slides in less than a minute – 30 times more efficient than traditional methods.

Research into effectiveness has been highly positive, with findings on platelet counting technology presented by specialists from France and Poland at the International Society for Laboratory Haematology’s 2024 International Symposium on Technical Innovations in Laboratory Haematology.

Professor Marie Christine Béné from the Faculty of Medicine at Nantes University, said: “The latest developments in platelet counting technology could help a lot of people in treating haematology disorders. We are getting more and more help from machines able to count cells with minimal supervision, alerting us and providing us with more time to spend looking after patients.

“Accurate evidence behind low platelet count could allow patients to have neurosurgery, or inform clinicians if patients don’t need a blood transfusion.

“Mindray has evidently listened to customers in the development of its latest technologies. Its disaggregation protocol and optical staining of platelets will help with productivity – reducing the time medical scientists need to spend examining low platelet counts to identify platelet clumping. Removing that process will be good for everyone – scientists, clinicians and patients.”

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As healthcare continues evolving at an unprecedented pace, integrating Artificial Intelligence (AI) in clinical settings presents extraordinary opportunities and significant challenges. Drawing from our experiences at one of London’s largest acute NHS trusts, I have witnessed firsthand how AI can transform healthcare delivery—but only when we carefully consider the human elements alongside the technological capabilities and promises.

Like many healthcare leaders, we were initially captivated by AI’s potential to revolutionise patient care when we began our AI journey. However, we learned that successful AI implementation in clinical practice requires much more than sophisticated technology. It demands a balanced approach between innovation and cultural adaptation.

For example, our implementation of speech AI for clinical letter dictation at Barking, Havering and Redbridge University Hospitals NHS Trust represented a significant shift. The traditional process involved clinicians dictating letters after patient consultations, which required medical secretaries to transcribe, format, and process them before sending them to general practitioners (GPs). This workflow could take over a month to complete. The initial pilot showed remarkable promise, reducing letter delivery times to GPs from 37 days to just four days. This success could be attributed to the clinicians’ enthusiasm for the pilot.

However, as we scaled the solution, we encountered significant operational doubts, cultural resistance, and varying adoption rates among clinicians. Some staff expressed concerns about job security, as their roles were deeply embedded in this transcription workflow. Others were hesitant to change their established documentation practices and worried about losing essential administrative support.

AI in clinical practice – The adoption curve: a journey of persistence

We’ve discovered that the adoption of AI typically follows a natural curve, which includes initial resistance, gradual acceptance, and, ultimately, meaningful integration. During the initial implementation phase, we observed an increase in average letter delivery times attributed to cultural barriers and a phenomenon known as ‘AI aversion.’ However, sustained support led to a stabilisation of delivery times at 19 to 23 days—an improvement from our initial starting point, though not as dramatic as the results suggested by the pilot.

Key factors contributing to our success included strong clinical foundations, operational partnerships, and perseverance. Over the course of a few months, we were able to reduce delays from 37 days to 21 days, with some letters being sent out on the same day as the clinic visits if they contained brief text.

This experience emphasises an important lesson: the success of AI in healthcare relies not only on the technology’s capabilities but also on our ability to manage the human aspects of change. As I often say, even the most advanced solution for a complex NHS issue is likely to fail if we do not adequately address how people will adopt it.

Ethics and accountability in AI implementation

One of our most important initiatives currently is to establish an AI and analytics ethics group. This is not merely a bureaucratic exercise but a fundamental step in ensuring that our AI implementations serve our entire patient population fairly and effectively. We have found a way to navigate this with thorough governance discussions. The ethics group will help us address complex ethical challenges, particularly in the context of population health-based AI, where biases can significantly impact equality.

The ethics group acts as a crucial checkpoint, ensuring that our clinical practice AI solutions not only solve technical problems but also align with our values as healthcare providers. This is especially important when working with diverse patient populations, where accountable organisations must carefully assess AI systems for potential biases or limitations.

Cultural change and professional impact

The impact of AI on healthcare professionals is a sensitive yet crucial aspect of its implementation. When we launched our stroke imaging AI solution, we received such a strong response that it was jokingly said that we needed to wear a helmet and shield when walking past our colleagues. This reaction highlights healthcare professionals’ genuine concerns about AI potentially replacing their roles. Initially, this was met with doubt; discussions focused on the allure of the product and the need to compare different solutions.

Fortunately, AI has become so integral to the stroke care pathway that regional clinical workflows cannot function effectively without it. Our experience demonstrates that successful AI clinical practice implementation involves more than mere replacement; it requires enhancing existing processes. We have built greater acceptance and trust in these technologies by actively engaging with staff, addressing their concerns, and showing how AI can support—not replace—their expertise.

Looking ahead: a five-year vision

As we look to the future, our vision for AI in healthcare is ambitious yet rooted in practical reality. We focus on developing clear problem statements before implementing AI solutions, ensuring that we use technology to address specific, well-defined clinical needs rather than adopting AI merely for its own sake. One important lesson I have learned is to avoid “shiny toys” and overhyped AI products.

In the next five years, I envision a healthcare system seamlessly integrating AI into clinical workflows, supporting decision-making while preserving the essential human elements of healthcare delivery. This vision includes robust ethical frameworks to guide AI implementation. Enhanced clinical decision support systems will complement professional expertise, streamline administrative processes, and free up clinicians for patient care. Additionally, AI-enabled tools will improve access to specialist expertise.

Implementing clinical AI is not a sprint but a marathon. Success requires patience, persistence, and a deep understanding of both the technical and human factors involved. As we continue to advance in this field, we must remain focused on our ultimate goal: improving patient care and outcomes.

The lessons we have learned about the importance of cultural adoption, the need for ethical oversight, and the value of clear problem statements will be crucial as we continue to develop and implement AI solutions in healthcare. By sharing these experiences and insights, we hope to contribute to a broader dialogue on effectively and responsibly advancing healthcare through AI implementation.

Our experience at Barking, Havering, and Redbridge shows that while AI holds tremendous promise for healthcare transformation, its successful implementation depends on navigating the complex interplay of technology, human factors, and organisational culture. I reflect on my background, where academic or scientific publications of AI and relevant degrees contrast with the real-life human aspects of AI implementation and delivery. While both are important, I later realised that balancing these perspectives is the key to success in implementation within the NHS. As we continue this journey, maintaining this balanced approach will be crucial for realising the full potential of AI in healthcare. I look forward to sharing more of these insights and experiences at the upcoming Digital Health Rewired Conference on 18-19 March 2025.

By Devesh Sinha, Chief Clinical Information Officer, Stroke Physician, Barking, Havering and Redbridge University Hospitals NHS Trust

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Healthcare institutions should be prioritising how their data is managed, stored, and shared across estates. The lack of unity and siloes puts sensitive patient data at risk, meaning that healthcare leaders may face hefty compliance fines, and patients may receive delayed support or a decrease in quality of care as a result.

As we look to the future, digitisation will be crucial to bring healthcare operations up to par – especially for a sector that handles such sensitive data and where efficiency gains can mean lives saved. Digitising patient touchpoints will give healthcare professionals a detailed picture of every patient’s medical history and ensure compliance with rules on data transparency.

But how do we deliver effective document management and ensure that digitised records are as safe and secure as the patients listed in them? And what role can AI and automation play in lessening the load on overstretched healthcare professionals?

Digitally-powered data compliance

More sensitive data means more scrutiny of data management. The NHS highlights the importance of looking after patient data carefully to adhere with the Data Protection Act (DPA), Common Law Duty of Confidentiality (CLDC), and GDPR. The DPA for example outlines that consent has to meet certain guidelines to be valid such as being used for a clearly defined purpose and being withdrawable – as easy to withdraw the data as it is to give it. However, outdated systems and disparate data make it difficult for NHS bodies to fulfil these requirements.

Creating a frictionless experience for busy healthcare professionals is crucial. Staff need to understand what data they can share, how they should share it, and what data should be deleted after a given time. A robust content services platform that centralises patient data improves this regulatory compliance by providing a complete oversight of record history and a single source of truth. Through this platform, medical professionals can share information securely and power automated retention policies that manage documentation throughout its lifecycle, ensuring compliance with regulations and retention laws.

This effective document management and record keeping should be scalable and flexible, allowing for changes in existing workflows and evolving regulatory requirements.

Protecting sensitive patient data through effective document management

Regulatory compliance is just one piece of the cybersecurity puzzle. Ageing IT infrastructure and legacy systems leave patient data vulnerable to cyber attacks that have the potential to affect real lives. For instance, the recent Synnovis attack led to the leak of 400GB of sensitive data and sparked huge impacts for end-users with the cancellation of thousands of medical procedures.

By introducing effective patient data management, healthcare professionals can also streamline security efforts and reduce the risk of cyber attacks. Healthcare institutions should manage all patient data and customer information with secure storage, encryption, and stringent access controls through a platform that can track user activities and provide detailed audit trails of document access and modifications.

What’s more, this digitalised data management gives healthcare providers the opportunity to use AI. They can use this to integrate various data sources, including patient information and medical records, into the Electronic Health Record (EHR) system, creating a comprehensive view of a patient’s health history. Healthcare providers can also use AI to optimise medical records management, facilitating secure and centralised storage of medical records. This enables authorised staff to access information quickly and efficiently, while adhering to regulations. Automation can also streamline record lifecycles, minimising manual work and potential compliance fines.

Taking the heat off healthcare professionals

In addition to data security benefits, AI and automation can automate many manual tasks to free up valuable time for clinicians, who can then focus on delivering improved patient care. A snapshot survey of NHS and social care managers found that 20% spent seven to eight hours a day on admin – valuable time that could be spent helping patients.

In the NHS, technology and systems can be varied across a healthcare estate. With cloud-based integrations, healthcare leaders can synchronise their estate’s legacy processes and technologies with new solutions, allowing clinicians, physicians, staff, and patients to access their records anywhere, anytime. Weaving in powerful workflow automation can also immediately reduce admin headaches. Automation easily captures and populates information between departments, eliminating the need for manual data entry and wasted time looking through physical paperwork.

In fact, AI could save clinicians four hours of admin time each week. This could be through automating patient communication such as appointment scheduling and sending post-operative reminders. It could mean the improvement of clinical decision-making, where AI can analyse large quantities of clinical data to identify patterns and trends that can inform better treatment decisions. It could also mean enhancing healthcare data exchange, where AI can easily capture and integrate various types of patient data, including demographics, insurance information, and medical records. This not only ensures accurate data processing, but also allows for quick retrieval of information.

How healthcare providers manage their data is fast becoming a top priority. Whether healthcare providers are looking to remain compliant, protect data, or weave in time-saving technologies like AI and automation, effective document management will be vital to success.

Article by Grace Nam, Strategic Solutions Manager, Healthcare, at Laserfiche

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The assay from global health technology provider Mindray allows clinical teams to measure cardiac troponin I proteins that are released into the blood during heart attacks, and when the heart is damaged.

Found to be highly precise and sensitive for both men and women, the cardiac troponin I assay has been the focus of a new study carried out by world-renowned cardiac biomarker specialists at Hennepin Healthcare’s Hennepin County Medical Center in Minneapolis, Minnesota. Early evidence has shown significant potential for clinical applications in helping to reduce pressure on busy emergency departments.

Opportunity for Clinical Diagnosis of Heart Attack Risk

Researchers found that the test not only performed as well, if not better, than those already available in the market, but that it also had the potential to help clinical teams rule out many patients with symptoms suggestive of a heart attack at an early stage.

Focussing on more than 1,500 patients who presented to the inner-city hospital’s emergency department with symptoms such as chest pain, arm pain, or jaw pain, the study found that 15% of early presenters could be ruled out for a heart attack based on a single blood test on arrival at hospital.

Typically for most assays of this kind, an initial blood examination would serve as a baseline measurement for early presenters, with a further test required to detect cardiac troponin I two hours later.

Combining this approach and applying a second blood sample to the Mindray assay after two hours, researchers also found that an additional 30-40% of remaining participants could also be safely ruled out with less than a 1% probability of an adverse event within 30 days.

Unusually precise measurements of cardiac troponin I made possible using the Mindray assay, meant additional individuals could also be ruled out. In total, across all cardiac troponin I measures, researchers were able to identify 60% of patients presenting to the emergency department with heart attack like symptoms, who could be safely sent home.

Opportunities for Cardiac Troponin Assay

Professor Fred Apple, the study’s principal investigator, a medical director in laboratory medicine at Hennepin Healthcare, professor at the University of Minnesota, and a former committee chair of the International Federation of Clinical Chemistry and Laboratory Medicine Committee on Clinical Application of Cardiac Bio-markers, said: “Patients who comes in to an emergency department with chest pain or arm pain, symptoms suggestive of a heart attack, would rather spend the night at their home with a surety that they aren’t going to have a heart attack, versus a bed in the hospital. But sometimes it can be difficult for a clinician to determine whether or not that pain is related to the heart.

“Our preliminary findings around Mindray’s high-sensitivity troponin I test are exciting for emergency medicine – with multiple ways this could be built into algorithmic clinical practice to help avoid overcrowding and enhance triage safety.

“Cardiac troponin alone doesn’t determine if you have had a heart attack, but it can tell the clinician if the heart has been injured, and when measurements are normal that it is safe to send a patient home.

“In 40 years of cardiac biomarker research, this assay is as good, if not better than any cardiac troponin assay I’ve worked with in my career. That it is so incredibly precise and analytically very sensitive to measure low cardiac troponin concentrations, opens new and unique possibilities when patients present early to an emergency department, so that clinicians can make informed decisions to send people home, without concern.”

In addition to ruling individuals out, findings also demonstrate that the assay can help to determine with high probability when patients are having a heart attack, with a high positive predictive value of approximately 70%. Researchers believe this could assist clinical decisions to immediately admit patients.

The Institutional Review Board approved study (MERITnI) was conducted alongside existing tests as patients presented to the hospital. Standard hospital procedures were used in the triage and care of patients, and the same blood samples drawn for routine clinical practice were also applied to the Mindray high sensitivity cardiac troponin I assay for research purposes, in order to evaluate the assay. The Mindray assay used in research was not used for patient care decisions during the study.

The assays were produced by Mindray after it acquired the Finnish company HyTest in 2021, where Professor Apple previously served on the board.

Preliminary findings are now undergoing peer review, but already additional possibilities are being explored. Future work in examining high sensitivity cardiac troponin I and high sensitivity cardiac troponin T assays are expected to inform applications that might help clinicians to better understand if myocardial injuries are chronic or acute – and help them to determine the best treatments and therapies for patients.

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The NHS Long Term Workforce Plan was delivered in 2023 and is the first comprehensive workforce plan for the NHS, putting staffing on a sustainable footing and in turn, improving patient care. The plan emphasises the need for increased training and upskilling to fill workforce gaps, retaining the right culture and improving retention rates and reforming the way that work and training is delivered, by enabling innovative ways of working.

According to the plan, without immediate action, the NHS will face a workforce gap of more than 260,000 – 360,000 by 2036/37.

Addressing the Skills Shortage

One key part of the plan is increased training and upskilling which is vital if we are to truly move the NHS forward. Traditional training models, particularly in clinical environments like operating theatres, have struggled to meet growing demand for education due to limitations around space, safety and logistics. These physical constraints have long limited the number of students able to engage in crucial hands-on learning – which is key if we are to increase the number of professionals working in the sector in medical positions.

North Tees and Hartlepool NHS Foundation Trust has taken an innovative step to address this challenge by incorporating augmented reality (AR) technology into its healthcare training programmes, allowing students in disciplines such as radiography, physiotherapy, and paramedicine to experience learning in a more immersive and scalable way.

Worn by surgeons, the lightweight wearable headset technology has an adjustable point-of-view camera, video stabilisation and precision zoom features which enable the students to see procedures vividly from the same perspective as the surgeon. Students can then observe and asks questions as they ‘see’ through the surgeon’s eyes.

By introducing RealWear AR technology, the Trust, which serves approximately 400,000 people in Hartlepool, Stockton-on-Tees, and parts of County Durham, has created a solution that allows healthcare students to observe real-time surgical procedures without these limitations, expanding the reach of medical education while maintaining quality and safety.

Prior to using the technology, only a limited number of students could observe surgeries in person. Even when present, many students faced restricted visibility, hampering their ability to fully engage with and learn from the procedure. AR technology addresses this issue by allowing a much larger number of students to observe surgeries remotely, from the surgeon’s perspective and in real-time.

Revolutionising Healthcare Education with AR

This expanded access to real-time learning has allowed the Trust to offer training opportunities to a far wider pool of students from multiple disciplines, such as paramedics, radiographers, and physiotherapists. The scale of learning has increased substantially, enabling more students to gain valuable surgical experience in a single day than could typically be accommodated in a traditional training model over an entire year.

By implementing AR training methods, the Trust has also been able to increase its reach, welcoming healthcare students from 11 different disciplines across six universities. This broad access provides invaluable training opportunities for students from a range of healthcare fields, allowing them to engage with and learn from real-life scenarios in a way that was previously unattainable in such numbers.

Expanding Learning Opportunities

The success of this AR healthcare initiative has not only increased training capacity but has also attracted growing interest from students and institutions across the NHS. The ability to engage with live surgeries in an immersive and interactive manner has shown that AR technology can effectively bridge the gap between the traditional limitations of medical education and the need for broader access.

Additionally, this technology has expanded beyond surgical training. Paramedics, for example, have used it to connect with specialists in emergency departments, visually sharing real-time updates on a patient’s condition before arriving at the hospital. This cross-discipline collaboration improves communication, enhances patient care, and provides healthcare professionals with a more complete picture of the patient journey.

The Future of AR-Driven Healthcare Training

The use of AR technology at North Tees and Hartlepool NHS Foundation Trust represents a significant step forward in how education in healthcare can be delivered. Looking to the future, the Trust plans to expand AR integration even further, with the aim of covering the entire patient journey, from outpatient consultations to post-operative recovery. By offering students a comprehensive view of the healthcare process, this approach has the potential to inspire more individuals to pursue careers in specialised medical fields, helping to address the broader workforce shortages facing the NHS.

At a time when the healthcare sector is under immense strain, AR technology offers a promising solution for transforming medical education. By removing the physical limitations of traditional training and enabling more immersive, real-time learning, new standards can be set for how the next generation of healthcare professionals can be trained, empowered, and prepared for the demands of the future.

By Dr. Chris Parkinson, CEO and co-founder, RealWear

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Clinical professionals and end users were deeply involved in this complex undertaking, from the moment a decision was made to deliver a new emergency department electronic patient record. A comprehensive team managed the procurement, core design and implementation of Miya Emergency across three emergency departments.

This approach enabled rapid and effective progress – and within 10 months of contract commencement, teams redesigned complex clinical workflows, integrated key systems, engaged a full range of stakeholders, and prepared staff in and beyond emergency departments, before a successful simultaneous go-live on a single day.

Delivered on time and within budget, the new system now supports end-to-end patient workflow. It allows teams to capture data for patients coming into the trust’s emergency department, streamlining processes as they are treated, and ensuring seamless data continuity as they move forward in their care – as inpatient admissions, or during discharge back to community.

Paper processes are progressively being removed as Miya Emergency is integrated with other trust digital systems. Automation of once manually intensive tasks, such as data collection for the Emergency Care Data Set, is saving time, and efficiencies are being created as the system generates clinical assessments, forms, referrals, and task creation.

Led by a multi-disciplinary clinical and operational team representing various functions in the trust, implementation successfully took place during the summer at emergency departments in Andover War Memorial Hospital, Basingstoke and North Hampshire Hospital, and Royal Hampshire County Hospital.

Dr Tamara Everington, former chief clinical information officer for Hampshire Hospitals NHS Foundation Trust and now chief medical officer at Queen Victoria Hospital, Sussex, said: “Clinical and operational staff see enormous potential in Miya Emergency to help them work in more modern ways, in support of better outcomes and efficiency. The system works extremely well, providing cross-trust visibility of what is going on in our emergency departments.

“A broad range of people in and around emergency departments – doctors, nurses, pharmacists, operational specialists, and administrative teams, have worked hard together to ensure a successful implementation on time.

“We have had an extremely positive relationship with Alcidion – including engagement from the chief executive, and close communications at every stage with senior clinicians and technical people, allowing us to respond to challenges and design a solution collaboratively.

“This is a very important part of our organisation’s paper-free journey, and work here will also inform progress towards a shared main electronic patient record for all the acute hospital Trusts within our integrated care system.”

Implementation to-date has seen the deployment of a core system, which has been integrated into the trust’s current electronic patient record, and which is already able to communicate important discharge information to GP practices. Additional integrations, including the ability to send patients’ documents into the NHS App, will take place in the new year.

In addition to informing the future regional EPR strategy, the project is also expected to lend lessons to at least one other neighbouring trust that is expected to go-live with Miya Emergency next year.

Dr Paul Deffley, chief medical officer for Alcidion, said: “The complexity of reimagining workflow across not only three busy emergency departments – but across upstream and downstream services within and beyond hospitals walls – cannot be understated. Nevertheless, the team at Hampshire Hospitals has done this in an impressive and collaborative way. Every deployment is different, and we are pleased to have been able to be so closely involved and present onsite to understand and respond to local needs. We also look forward to sharing lessons with other emergency departments and other EPR implementations across the country, at a time when digitisation has once again been thrown into sharp focus.”

Hampshire Hospitals’ operations director (Medical Division) Zena Ludick, said: “Transitioning to MIYA while maintaining extremely busy emergency departments was no small challenge; this change impacted all members of our ED staff and also required departments throughout the trust to prepare and respond. As well as considerable planning ahead of the transition date, a full contingency response team met regularly throughout the switch to MIYA and this was supported by Alcidion.”

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