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Found 500 results
  1. News Article
    Post-market surveillance of AI health tools must be “beefed up” to protect doctors as well as patients, England’s patient safety commissioner says. Henrietta Hughes also told The BMJ it was vital to establish clarity on where clinical liability sits when, not if, AI tools harm patients. Hughes, a GP and a former medical director at NHS England, is deputy chair of the National Commission into the Regulation of AI in Healthcare. The commission was set up by the Medicines and Healthcare Products Regulatory Agency (MHRA) to help guide development of a new regulatory framework for AI medical devices. The commission published interim findings from its consultation and engagement process last week. Hughes said some clear themes had already emerged during the process of engagement with patients, the public, and doctors. Among the most pressing was the need for greater surveillance of AI tools after approval, so the MHRA can act if patients are at risk. Hughes told The BMJ, “It’s really important that real time, real life monitoring happens when a device like AI is deployed in a real life clinical environment, particularly if the population of patients may be different from the population used to feed the model.” Hughes added that while medicines have to pass an “extremely high hurdle” and evidence base to reach the market, AI—where new products are rapidly launched and updated—is different. “We know that AI can change once it’s actually deployed, and so it’s important that the regulations are able to be updated to take account of that and to ensure that all medical devices, and particularly AI, are safe across its whole life cycle,” she said. “Whether we’re using the yellow card system or other kinds of ‘always-on’ postmarket surveillance and postmarket monitoring, that side of things really needs to be significantly beefed up if we’re going to lower the hurdles for products to come onto the market.” Read full story Source: BMJ, 18 June 2026
  2. News Article
    Health innovation and safety minister Preet Kaur Gill has said she is “very sorry” after being questioned by MPs about NHS England’s handling of information provided to the National Data Guardian (NDG) on access to patient data within the Federated Data Platform (FDP). Appearing before the Health and Social Care Committee on 16 June 2026, Gill was challenged over concerns that NHS England had incorrectly described who could access identifiable patient information within the FDP. The concerns relate to NHS England documentation submitted to the NDG, which incorrectly described who could access identifiable patient data within parts of the FDP. Martin Wrigley, MP for Newton Abbot, raised concerns about reports that identifiable patient data was flowing into the national FDP system and that Palantir engineers and others could obtain administrative access when required. Similar concerns were raised earlier this month by the NDG. Read full article. Source: Digital Health, 18 June 2026
  3. News Article
    The Department of Health and Social Care wants tech suppliers to take on more financial risk by agreeing to new contract models aimed at improving value, HSJ understands. Tech industry figures have told HSJ that government officials have started asking suppliers on NHS contracts to take part of their payment once productivity gains have materialised. This would see a company paid some or all of its fee once the trust had realised some of the efficiency savings that were promised in the business case. Some consultancies are paid in this way, but it is not common with tech procurements. One senior industry figure said: “I understand the logic, if technology is being funded on the basis of productivity, suppliers are asked to share some of the delivery risk.” However, they added this would be “difficult” for suppliers, as “technology is only one part of whether benefits are realised”. They told HSJ: “The bigger issue is usually transformation: workflow redesign, adoption, training, leadership, benefits tracking, and whether the organisation actually changes how it works. Those factors largely sit with the customer, not the supplier. Read full story (paywalled) Source: HSJ, 16 June 2026
  4. Content Article
    These two reports summarise findings from the National Commission into the Regulation of Artificial Intelligence (AI) in Healthcare’s research and engagement activities and call for evidence. The Commission’s purpose is to advise the Medicines and Healthcare products Regulatory Agency (MHRA) on improving its regulatory framework and to accelerate safe access to AI in healthcare and across the NHS. You can read a summary of Patient Safety Learning’s response to this call for evidence here. The work brought together evidence from patients and the public, healthcare professionals, industry, academics and wider health system stakeholders through public polling, surveys, stakeholder engagement, deliberative research, an open call for evidence, a public Ask Me Anything session and insights from the MHRA’s AI Airlock programme. Thorough analysis of this evidence, 10 key findings have been identified. The report summarises these as follows: 1. There is a clear call for a proportionate, lifecycle-based approach to regulation Stakeholders noted that the current framework, which is designed for more static medical devices, is not well suited to iterative and adaptive AI systems. Across groups, stakeholders called for a proportionate approach that is risk-based, considers patients’ safety and fairness, with clear practical guidance and addresses existing duplication and fragmented oversight. Stakeholders also underlined the importance of strengthening clinical evidence requirements, with strong support for enhancing post-market surveillance and improving coordination. With a more proportionate approach seen as essential for balancing innovation with patient safety. 2. There is strong consensus for significant regulatory reform Across respondent groups of healthcare professionals, healthcare providers and industry, most people said that the existing regulatory framework needed “significant reform” but did not need a “complete overhaul”. Amongst patients and the public, the number of respondents calling for “significant reform” and a “complete overhaul” were similar, with 34% asking for “significant reform”, and 35% for a complete overhaul. 3. There was broad consensus that AI systems will increasingly require continuous post-market surveillance and monitoring Several stakeholders highlighted the need to upgrade current approaches to post market surveillance and monitoring, so they are better suited to AI systems. There was strong consensus that performance and risk cannot be adequately assessed through one-off approvals alone but instead require ongoing, real-world oversight across the lifecycle. Through qualitative evidence, stakeholders called for a more continuous and ongoing approach which helps track performance, monitor safety, and manage compliance across the AI system lifecycle. They also suggested that upgraded approaches need to help manage performance drift, validate performance in real world settings, and track changes in performance over time. 4. Responsibility should be shared across the system, with each individual and institution understanding their essential role and responsibilities There was strong consensus that accountability should not rest with a single person or institution, with respondents favouring a model which better distributes liability across the lifecycle. Patients and members of the public called for a comprehensive approach to accountability that addresses current gaps, healthcare professionals stressed that clinical accountability should be maintained whilst healthcare providers emphasised the need for robust governance structures and clear organisational responsibility. Stakeholders also highlighted uncertainty in how roles, responsibilities, and liability are defined and applied in practice. There were differing views on where liability should sit when an AI system causes or contributes to harm. Some respondents believed that liability should sit with the healthcare professional using the AI system. Another group of respondents argued that liability should sit with the healthcare provider who deploys the AI system. Others suggested that liability should sit with manufacturers, given their role in developing the technology and then maintaining their AI system’s performance. Across responses, there was a consistent emphasis on the need for greater clarity and consistency in how liability is allocated. Many respondents called for structured approaches to distributing liability that reflect the roles of different actors, including manufacturers, healthcare providers, and healthcare professionals. Suggested approaches included shared or distributed liability models that apportion responsibility based on specific circumstances. Stakeholders noted that clearer and more consistent frameworks would help address uncertainty and support the safe use of AI systems in healthcare. 5. Human oversight and responsibility for clinical judgment should be retained There was strong consensus from respondents that AI systems should continue to augment the work of professionals and should not be fully responsible for clinical decision making. Patients and the public emphasised the importance of human involvement in their care, including expectations that clinical decisions involving AI should be checked and validated by a human clinician. Healthcare professionals and professional bodies highlighted the risk of over-reliance on AI outputs at the expense of professional judgement. Industry respondents were supportive of ‘human-in-the-loop' safeguards. 6. Transparency and explainability will be key for the ongoing deployment of AI systems The ability to easily understand how an AI system works and to interpret its outputs will be key for building trust, enabling deployment, and ensuring the safety of an AI system. Patients, public and professionals advised that explanations of AI system outputs need to be clear, and providers called for greater transparency in the procurement process for sourcing AI systems. Industry organisations commented on the need for clearer and more structured regulatory documentation. 7. Data access and use is central to the role of AI in healthcare moving forward Respondents to the Call for Evidence noted that healthcare data is simultaneously an enabler and a barrier to the development and deployment of AI systems in healthcare. Patients and public expressed strong concerns about current approaches to consent for data access and how data is used by commercial entities. Some respondents cited governance and compliance burdens and fragmented data infrastructure as key barriers to development and deployment. Industry respondents called for clear and robust frameworks for accessing data including shared data governance templates and clearer guidance on data standards. 8. There is a need for robust training and improved AI literacy The Call for Evidence found a clear view that robust, ongoing training and clear understanding of AI in healthcare is critical for safe adoption. Healthcare professionals highlighted the risks of a lack of AI-specific training can bring such as increased risk of automation bias. Healthcare providers called for more structured workforce training on AI moving forward. Industry respondents advised that training is also needed for individuals who oversee the governance of AI systems in healthcare. 9. There is a need to improve incident reporting and learning mechanisms There were widespread calls for standardised reporting mechanisms for AI systems. Patients and public called for greater transparency and accountability over where AI is involved in care, including clearer communication when things go wrong. Healthcare professionals raised concerns about underreporting of safety incidents in healthcare more broadly, noting that workload pressures are a significant contributing factor. Responses also suggested limited awareness amongst some healthcare professionals that the existing Yellow Card scheme already applies to medical devices, including AI enabled devices. Healthcare providers highlighted the operational challenges of implementing incident reporting consistently across different settings. Industry respondents called for clearer guidance on how incident reporting should work within AI specific post-market surveillance frameworks. Several respondents also proposed improvements to surveillance and monitoring approaches, including establishing a national reporting system for AI incidents and providing guidance for healthcare professionals on what to report. 10. Patient and public engagement, trust, and communication will continue to be key for the deployment of AI systems. Through the Call for Evidence, trust emerged as a core enabler of AI adoption in healthcare. Patients and the public called for consistent involvement, consent, and clarity over the role of AI systems, whilst professionals highlighted the need to take a proportionate approach to explaining how AI is being used to patients. Providers advised that clear and consistent transparency and communication frameworks are needed whilst industry respondents recognised that trust is key for the uptake of AI systems in healthcare.
  5. News Article
    The NHS is contending with severe operational pressures across several critical areas, with internal risk registers now tracking heightened threats to patient safety, data security, and core digital infrastructure. A newly updated operational risk register has escalated a number of warnings to critical levels, pointing to an acute capacity crisis in secure mental health services and deepening vulnerabilities within the health service's technology networks. The register, which assigns numerical scores to operational threats, has placed several indicators at levels that leave no room for further escalation. The risk score monitoring secure inpatient mental health capacity has been raised to the maximum possible level. The warning follows an urgent decision to relocate patients from a major healthcare site in Northampton after persistent patient safety concerns rendered continued occupation untenable. Health officials have cautioned that the resulting reduction in available beds has placed considerable strain on secure inpatient capacity, complicating appropriate patient placements across the country. Secure mental health beds are among the most difficult to replace at short notice. Alongside the mental health crisis, national IT platforms used to manage clinician performance and professional revalidations have been classified as both unstable and severely outdated. Chronic delays in rolling out replacement programmes have produced what internal documents describe as a fragile operating environment, substantially raising the prospect of widespread operational disruption. Cyber resilience remains one of the health service's most elevated operational concerns. Official assessments warn that existing vulnerabilities leave NHS networks exposed to data compromises, major service disruptions, and a measurable loss of clinical productivity. Read full story Source: Distilled Post, 11 June 2026
  6. News Article
    Trust boards must demonstrate they have “grip” of their cyber security, NHS England said. In a letter to providers, joint Department of Health and Social Care and NHS England head of cyber security Tom Wechsler said organisations should formally appoint an executive accountable for breaches. The NHS and its suppliers have suffered a string of high-profile attacks, including one on pathology provider Synnovis in 2024 that led to a death. Last week, NHSE CEO Jim Mackey warned risk to the NHS was accelerating, while the chair of the body’s technology committee Mark Bailie stressed it was a direct patient safety issue. The letter said trusts’ plans for what to do in the event of a breach should also “receive proper scrutiny and assurance”. Mr Wechsler said: “Geopolitical events and technology developments are increasing the cyber security threats we face. As seen in well-documented incidents across the economy, the impact of a cyber attack is felt across the entire organisation, not just its digital function.” Read full story (paywalled) Source: HSJ, 10 June 2026
  7. News Article
    A senior clinician at an east London NHS trust has told LBC News that patients have already come to harm because of serious failures linked to a new electronic patient record system — including one case where a patient is said to have died after a referral was missed. The whistleblower, who works at Barking, Havering and Redbridge University Hospitals NHS Trust and asked not to be named, alleged a patient with Covid, who also had cancer, died while waiting for a haematology referral after the request was not received by the department. The clinician said the problems have left staff “in tears”, caused missed referrals, delayed diagnoses, and created what they described as “chaos” across the organisation. They told LBC they were speaking out because they were “very, very worried for patient safety”. “It’s keeping me up at night,” they said. “We can’t deliver the service we want to for our patients, and I feel that we’re not being heard.” The senior clinician, who has worked in the NHS for several decades, said serious issues emerged after the Trust rolled out its electronic patient record system late last year. They alleged referrals were not always reaching the right teams, staff were struggling with missing or unreliable patient information, and serious findings were not always being escalated properly. “I think we are talking thousands of patients. I think we are talking about patient deaths," the whistleblower warned. “It will take some time for those to be revealed, the impact that it’s had.” Read full story Source: LBC News, 27 May 2026
  8. Event
    until
    This webinar, as part of Patients Association's Patient Partnership Week, will explore how organisations can partner with patients in the use of health data, placing trust and transparency at the heart of decision making. It will examine how technology currently uses patient data, why involving patient panels is essential, and how this supports better outcomes and public confidence. Register
  9. News Article
    NHS England is exploring how to push the federated data platform into primary and community care. A document seen by HSJ reveals the FDP, of which controversial US firm Palantir is the main contractor, was last month being scoped for use in integrated neighbourhood teams. Shifting care to the community is one of the government’s priorities for the health service. It said the “minimum viable product capabilities that address user challenges and are technically feasible to build” were: A triage patient list to prioritise patient by urgency, complexity or eligibility for interventions Tracking and coordinating tool to “assign and track actions with explicit ownership and escalation routes, supported by targeted alerts” Tool to monitor patient outcomes. This would “compare patient progress to baseline and intervention goals and iterate model of care” The British Medical Association last year called for the NHS to move to a publicly owned alternative to Palantir. Asked about the move to involve the FDP in neighbourhood health, a BMA spokesman said: “It is essential that patients can trust that their data is safe and being used responsibly by institutions across the NHS. “To have that trust, patients need confidence not only in the technical safeguards but also in the regulations governing these organisations. If that trust is eroded, there is a real risk that patients who fear their personal health information may be misused could delay seeking care, withhold important information from clinicians, or avoid engaging with vital services altogether." Read full story (paywalled) Source: HSJ, 27 May 2026
  10. Content Article
    More information about "Clinical competency in the age of AI safe, equitable and effective practice in AI-augmented healthcare"
    A recent white paper, Clinical Competency in the Age of AI,  presents findings from a systematic narrative synthesis of 445 studies examining clinical competency requirements in AI-augmented healthcare. It addresses a structural gap in how current competency frameworks prepare clinicians for AI-assisted practice. In addition to examining the breadth of research into clinical risks associated with use of AI in clinical care, the research analysed 23 existing AI competency and capability frameworks, including the NHS Health Education England AI and Digital Healthcare Technologies Capability Framework and the DECODE international consensus framework. It found that across all reviewed frameworks, the competencies most critical for frontline patient safety—critical appraisal of AI recommendations, detection of biased outputs, governance escalation, and protection of professional moral accountability—are largely limited to awareness statements for frontline users. Clinicians are expected to understand what AI is. They are not equipped to practise safely with it. The white paper proposes a five-domain competency framework, specified across three career stages, that translates intersecting AI risks into assessable clinical capabilities for practising clinicians. Key findings AI erodes clinical reasoning without competency safeguards. The Budzyń et al. (2025) multicentre colonoscopy study provides the first real-world evidence: adenoma detection rates fell from 28% to 22% among endoscopists after three months of AI assistance. The skill had not been assessed. It had not been exercised. It had atrophied. Cognitive overload drives uncritical AI acceptance. Alert override rates of 90–96% have been documented in deployed clinical AI environments—a workforce adapting to unsustainable demand by reducing evaluative effort. AI tools assessed as safe under controlled conditions carry significantly higher risk in busy, overstretched environments where they are most needed. Governance infrastructure is inadequate. Over 70% of NHS trusts lack documented clinical safety assurance for deployed AI tools (Oskrochi et al., 2025). Clinicians in these settings carry full personal professional accountability for AI-assisted decisions without the institutional infrastructure that should underpin them. Risks compound, but are treated as parallel separate risks. Time pressure increases automation bias severity. Automation bias accelerates deskilling. Deskilling undermines safety governance capacity. Equity failures concentrate where burnout is highest and training resources most limited. Current frameworks miss these feedback loops. Healthcare-specific competency frameworks are insufficient. Over 75% of medical students receive no formal AI education. Where training exists, assessment tools lack specificity for healthcare contexts. This research defines what AI clinical competency requires: technical understanding, critical appraisal, equity awareness, safety governance knowledge, and professional identity maintenance, integrated rather than treated as separate modules. Implementation guidance remains fragmented. Governance frameworks address safety. Education frameworks address training. Workforce research addresses burnout. Each treats its domain rigorously while missing the system dynamics. This research consolidates evidence into practical principles for curriculum development, organisational deployment and regulatory strengthening. Harm concentrates in those least able to detect it. The populations most at risk from biased AI outputs are served by clinicians least equipped to recognise that bias, in settings least able to monitor it. This convergence is structural and will not be resolved by improving AI performance alone.
  11. News Article
    Proposed amendments to UK medical device regulations are “a disgrace” and risk creating the lowest barrier to entry for high-risk AI devices in the developed world, sector experts have told HSJ. Under the draft rules, which have been submitted to the World Trade Organisation ahead of being laid before Parliament, software designed to diagnose a condition can face greater regulatory scrutiny than software designed to treat one. This means a company could deploy an AI chatbot designed to treat patients with severe mental health problems without independent regulatory scrutiny by self-certifying its own safety in the same category as a walking stick. The Medicines and Healthcare products Regulatory Agency (MHRA) has published draft pre-market regulatory requirements for medical devices and in vitro diagnostic devices entering the market. This was the most significant update to the UK Medical Device Regulations (MDR) 2002 since Brexit, when the UK left the EU MDR. However, regulatory leaders have aired concerns about the draft amendments, particularly around the risk classification of software. Read full story (paywalled) Source: HSJ, 18 May 2026
  12. News Article
    Digital technology should be used to support whole-system patient flow rather than simply improving bed management, according to a new report from Public Policy Projects (PPP). Beyond bed management: enabling whole-system patient flow through digital intelligence argues that persistent flow problems across the NHS are rooted as much in governance and fragmented pathways as in operational pressures within hospitals. It says digital tools have potential to improve the movement of patients across acute, community and neighbourhood care settings. However, participants warned that technology alone will not resolve longstanding bottlenecks. Instead, it calls for a shift from viewing patient flow as solely a bed management issue. The report draws on a roundtable held on 18 March 2026, chaired by Dr Victoria Betton, director for digital, data and AI at Health Innovation Kent Surrey Sussex. Read full article. Source: Digital Health, 6 May 2026
  13. Content Article
    The UK stands at a crossroads, where technological innovation, healthcare transformation, and economic renewal converge, forcing the nation to make decisive choices about its future path. As the UK navigates modest economic growth and a healthcare system under profound pressure, Generative AI has emerged not merely as a technological advancement but as a strategic catalyst capable of addressing pressing national imperatives. This report was commissioned by Healthcare UK and identified five strategic imperatives to position the UK as a global leader in healthcare AI and drive meaningful economic growth. Establish the UK as the global leader in healthcare AI Make the UK the first port-of-call for safe, effective Generative AI by establishing a premier evidence-generation hub, implementing a focused model development strategy, strengthening a national conformity-assessment hub, running adaptive, risk-based regulatory sandboxes, and projecting UK standards internationally so innovators can take a product from proof-of-concept to global market. Turn UK health data into a strategic growth engine Convert the health service’s comprehensive longitudinal data into an economic asset by creating a sovereign healthcare data resource, simplifying secure access, cultivating a domestic synthetic-data industry, offering incentives for UK-based development, and building the energy and compute infrastructure that keeps workloads on-shore and sustainable Secure public trust through transparency, co-production and patient empowerment Put citizens at the centre by engaging the public early and often, ensuring transparent, accountable benefit-sharing and data-use reporting, handing patients meaningful control over their data, and embedding co-production in every Generative AI project—demonstrating that economic growth and responsible use go hand-in-hand. Unlock capital and new commercial models for scale-up Fuel adoption through a UK Health Data Sovereign Wealth Fund, extending fit-for purpose funding pathways, fixing market fragmentation that hampers deployment, bridging healthcare, academia and industry, and piloting sustainable payment models that reward real-world outcomes Develop world-class healthcare AI workforce and leadership Equip the system to implement Generative AI safely by modernising healthcare education, professionalising the data workforce, enhancing digital leadership, strengthening procurement expertise, and rolling out streamlined implementation frameworks that let frontline teams adopt proven tools quickly and responsibly.
  14. News Article
    GPs waste half an hour every day navigating “clunky” IT systems that mean patients’ details get lost or bounced around between doctors, a survey suggests. The Royal College of General Practitioners said the NHS lost the equivalent of £410 per GP per day because doctors had to spend time on “avoidable” bureaucracy instead of seeing patients. Overall, GPs said they spent a quarter of their working hours on administrative tasks such as issuing sick notes or chasing information from other parts of the NHS. One of the biggest frustrations, according to the survey of more than 2,000 GPs, was the “inefficient” IT systems used for referring patients to hospital specialists for further tests. The college highlighted the loss of patient details and family doctors having to pick up the pieces. The report said: “The majority of GP participants reported spending 25-30 minutes per day completing tasks relating to a referral or follow-up activities, including manual data entry, re-issuing prescriptions and re-sending referrals, including those which had been lost, bounced back or rejected because of inconsistent and ‘clunky’ pathways.” GPs described having to act as a “safety net” for the rest of the NHS, dealing with follow-up work from the rest of the system and other “pointless” tasks creating a “hidden workload”. Read full story (paywalled) Source: The Times, 29 April 2026
  15. News Article
    Trusts passing an “AI readiness” test before being allowed to use the technology is one of the ideas being considered by an influential government commission. The National Commission into the Regulation of AI in Healthcare, this week, published meeting minutes that gave clues about what new rules it might propose. The minutes said discussion papers “outlined proposals to accredit healthcare providers who can demonstrate high levels of ‘AI readiness’ so they can provide earlier access to AI systems and a pathway for deploying earlier-stage AI systems, which maintains healthcare professionals’ confidence.” It said “AI readiness” would mean healthcare providers being able to show they have “the systems, digital infrastructure, governance and risk frameworks and capabilities in place to deploy AI systems safely”. Digital maturity varies widely across NHS organisations. The national commission was set up in September to help clarify the confused regulation of approval, deployment and liability in relation to the tools. AI use cases in healthcare range from automating administrative work and ambient voice technology to interpreting test results. The national commission is chaired by Professor Alastair Denniston. Minutes said he “emphasised throughout the discussion that the proposals were intended to stimulate forward-looking discussions around the possible future regulatory frameworks but were not under active development”. Read full story (paywalled) Source: 24 April 2026
  16. News Article
    NHS patients in England are facing a “postcode lottery” in access to robotic-assisted surgery, according to an analysis by the Royal College of Surgeons of England. The data, published on 20 April, shows that despite national guidance from NHS England there remain major differences in how the technology is funded, distributed and used across NHS trusts in England. Freedom of Information data from NHS trusts reveal that there is no consistent funding model for robotic surgery with some trusts, such as Royal United Hospitals Bath NHS Foundation Trust, relying on charitable funding. Read full article. Source: Digital Health, 21 April 2026
  17. News Article
    Health service staff have expressed alarm that engineers working for controversial tech company Palantir have been given NHS email accounts. Employees using NHS.net email accounts have access to a directory with the contact details of up 1.5 million staff. Sources believe Palantir staff were granted the same access. Palantir staff working on the introduction of its Federated Data Platform (FDP) for NHS England have also been given access to NHS SharePoint filesharing systems and internal Microsoft Teams groups. Hospital trusts and integrated care boards across the country are being encouraged to adopt FDP, which Palantir won a £300m contract to provide in 2023. NHS England says FDP allows NHS organisations to connect patient records historically held across different systems, allowing staff to manage waiting lists, allocate appointments, speed up diagnoses and personalise treatment more effectively. It is part of the government’s plan to “reinvent the NHS” through “radical shifts”, including moving systems from “analogue to digital”. The use of NHS email accounts and internal systems by private contractors is not unusual. However, Palantir’s association with AI-powered surveillance and war technology has made some staff, patients and human rights campaigners question the ethics and implications of allowing the spy-tech company to become embedded in the UK public sector. Rory Gibson, a resident doctor, said: “I – as a doctor – absolutely don’t want my personal email and number to be accessible to someone who works for Palantir on the NHS, and might next month be working on systems for drone strikes. NHS staff have not consented to sharing their email addresses with Palantir staff.” Read full story Source: The Guardian, 8 April 2026
  18. News Article
    An NHS trust has abandoned plans to trial a major US supplier’s ambient voice technology after concerns were raised about its compliance with NHS England accreditation requirements, HSJ has revealed. Epic Systems had this week planned to launch a trial of its native AI Charting functionality at Frimley Health Foundation Trust, despite not holding Medicines and Healthcare products Regulatory Agency (MHRA) Class I medical device status, which is required of all AI scribing tools capable of summarisation. Frimley Health has since confirmed the trial did not go ahead as it had not gone through the trust’s internal governance processes and has been paused pending further work. Epic’s AI Charting tool does not appear on the MHRA Class I medical device registry and the company is also not on NHSE’s AVT registry. HSJ understands that two other trusts – understood to be one in the north of England and one in the east – are currently live with Epic’s AVT. Several other trusts are understood to be in conversations with Epic about trialling its AVT, including University College London Hospitals FT, Birmingham Women’s and Children’s FT, the Royal National Orthopaedic Hospital Trust, and East Suffolk and North Essex Foundation Trust. Read full story (paywalled) Source: HSJ, 1 April 2026
  19. Content Article
    The King’s College London Cyber Security Research Group has published a white paper, Building NHS Resilience to Ransomware: Central Oversight and Shared Capability. The paper identifies ransomware as the most acute cyber threat facing NHS Trusts. This is driven not only by the nature of the threat itself, but by inconsistent implementation of established security controls and uneven governance maturity across organisations. The report finds that the primary constraint is often cultural rather than technical or financial. While the NHS has a strong patient safety culture, this has not yet fully extended to digital systems and third-party dependencies. As a result, cyber risk is still too often treated as an IT or procurement issue, rather than as a direct risk to service continuity, public trust, and patient safety. The paper proposes a Cyber Leadership Framework centred on Board-level ownership and empowered CIO or CISO leadership. It emphasises the need to connect technical controls with the operational realities of care delivery. It also argues for greater centralisation of core cyber capabilities and shared services to reduce fragmentation and support weaker Trusts in reaching consistent standards. The report highlights the importance of organisational culture alongside technical capability. This includes leadership tone, clear accountability, translating cyber risk into operational terms, and moving beyond compliance towards demonstrable resilience in care delivery. Ultimately, the paper argues that the future digital legitimacy of the NHS will depend not only on improved tools, but on embedding cyber resilience within the culture of safe care. Former Health Secretary Alan Milburn welcomed the report, noting in particular its focus on governance and cultural change as key to reducing risk, rather than relying solely on increased resources.
  20. News Article
    Poor IT represents a “critical” threat to patient safety and service delivery in a trust’s breast cancer unit, a report has warned. A Royal College of Radiologists review of County Durham and Darlington Foundation Trust’s breast cancer service found cases where the wrong women were scanned, while others had the incorrect side of their body examined. Problems with the trust’s picture and communication service (PACS) meant that clinicians were sometimes unable to access critical prior imaging – particularly from independent sector providers – leading to delays, system overload and reliance on incomplete records. There were also reports of misdirected or lost findings, risking time-critical results not being acted upon. The RCR report is the latest investigation into breast cancer services at CDDFT, where major failings were identified last year after a review of cases. While previous reviews have looked at surgical practice, leadership and governance, the RCR review focuses on the imaging and reporting aspect of the symptomatic breast service. However, leadership and governance problems were also found in radiology, the RCR said. Read full story (paywalled) Source: HSJ, 31 March 2026
  21. Content Article
    A study supported by the NIHR North West London PSRC examined the implementation of the Scan4Safety programme at an NHS demonstrator site to understand the hospital experience of adopting barcoding technologies and standards to improve patient safety and quality of care. Researchers found that using standardised data to identify patients, products, places and procedures, Scan4Safety helps build a robust information infrastructure across both internal and external hospital supply chains, with the potential to deliver significant value to patients, clinicians and the NHS. Related reading on the hub: Using barcode scanning technology to improve blood group testing in unborn babies Patient barcode scanning in NHS hospitals: safety, snags and workarounds. A nurse’s perspective
  22. Event
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    There is an increasing use of technology in healthcare and patient safety, though the implementation of such technology has had varied success. Healthcare operates in complex open systems and cultural, social and organisational contexts. Sociotechnical theory considers that people and technology are dynamically, reciprocally and recursively related and the relationships between human agency, the social and technology are considered as interdependent. The implementation, adoption and use of technology is therefore seen as a contextually situated social practice. This session will have interactive elements and opportunities for discussion. It will look to introduce and provide an understanding of sociotechnical theory. We will seek to understand how sociotechnical theory can be used to illuminate technological adoption in complex systems and the implications for patient safety. We will reflect upon how sociotechnical theory might be useful for patient safety research. SafetyNet Patient Safety 101 sessions are intended for researchers who may not be experienced in patient safety and would like to know the basics on a range of Patient Safety topics or those who would like a refresher. Register
  23. Content Article
    Productivity-enhancing technologies remain the big hope for sustaining a high-quality NHS in future. The Health Foundation Chief Executive, Jennifer Dixon, looks at efforts to adopt AI applications quickly and at scale. Learning from the world’s most technology-enabled health care providers, Jennifer draws on case examples from some familiar places, such as Kaiser Permanente, the Mayo Clinic, Johns Hopkins Hospital, Massachusetts General Hospital and Memorial Sloan Kettering Cancer Centre. And some less familiar, such as Samsung Medical Centre (South Korea), Changi General Hospital (Singapore) and the Rigshospitalet in Denmark. Common ingredients for success While the regulatory environment for each country is different, some common ingredients for success are emerging. Across these examples we tended to see: Significant investment made over the years in their data infrastructure. Some kind of innovation centre or hub allowing access by in-house clinicians and scientists, and by vendor partners, to test ideas using patient-level data. A balanced approach to AI development – part in-house, often led by clinicians, and part procured from an AI vendor. A centre or unit focused on AI governance, including standard agreed rules for testing AI in real-world contexts. These focused on going beyond the early-stage development of AI models to investigate how things panned out ‘on the ground’ when implemented. Partnerships with large technology companies, such as Amazon Web Services, Microsoft and Google, stretching over years. Built-in training for staff on how to develop, test and use AI effectively. Many of these health facilities focused on AI to tackle challenges common to many settings, such as: Improving productivity and releasing clinical capacity, particularly by reducing administrative burden and improving operational efficiencies. Reducing waiting times by enabling earlier clinical interventions, streamlining processes and pathways, and speeding up discharge. Improving safety and clinical outcomes via predictive analytics to identify high-risk patients or post-operative complications. Promoting personalised medicine, combining genomics, imaging and electronic health record data to advance research and provide tailored treatments.
  24. Content Article
    To explore current use of electronic patient record (EPR) systems, The Health Foundation commissioned a survey of 1,725 NHS staff members in England between July and October 2025 to better understand NHS staff views towards them. Staff views provide valuable intelligence about the performance of EPR systems in practice. And as the primary users of these systems, staff support is essential if EPRs are to be implemented and used effectively. Buy-in from staff can help EPR systems become more useful and reliable, improving data quality and increasing opportunities for refinement and innovation.  Key points The survey found that EPRs are in widespread use, with 83% of respondents saying they now use them as part of their job in the NHS. On balance, the NHS staff we surveyed were positive about the impact of EPRs in several areas and felt these systems are already improving both patient care (75%) and patient safety (73%). Yet 37% of staff also felt EPRs are not currently working well in their organisation. The survey points to a mix of frustrations and barriers to the effective use of EPRs, including having to use multiple EPR systems every day, a lack of real-time support and limited opportunities to give feedback on how they are working. An area of particular concern is training. Only around half (49%) of survey respondents had received training on how to use the EPR system for their role, and less than a third (28%) had received training on how to fix or troubleshoot problems. Unlocking the full value of EPRs will require coordinated action across the NHS to improve the integration of systems, training and support for staff. Without this, there is a risk that many of the potential benefits for productivity, safety and quality of care will remain unrealised. Related reading on the hub: HSSIB Investigation Report: Patient safety issues associated with electronic patient record (EPR) systems – a thematic review Patient safety and electronic patient record systems: Patient Safety Learning’s response to HSSIB report Electronic patient record systems: Putting patient safety at the heart of implementation
  25. News Article
    Virtual ward occupancy hit a record high in January but expansion has stalled over the past 12 months, according to analysis of official figures. In January 2026, 11,474 patients occupied virtual ward “beds”, representing 90% occupancy of the 12,725 capacity. This is a 13% increase in patients compared to the same period in 2025, when there were 10,162 patients at 80% occupancy. February 2026 figures, published last week, show occupancy then fell from the peak in January 2026 to 84%. Despite this rise in use, capacity has stalled nationally. Between January 2025 and January 2026, virtual ward capacity grew by just 98 “beds” (0.8%) compared with an increase of 992 (8%) the previous year. The plateau reflects a shift in national priorities and the end of ring-fenced funding in March 2024. NHS England had provided £450m of dedicated funding over two years to support virtual ward expansion. One leader close to the programme told HSJ that the focus from the centre on A&E performance targets had shifted priority among commissioners. They added that the slower-than-expected rollout of the neighbourhood health service had also created uncertainty about where virtual wards – which involve the use of technology to care for patients in their own home when they would otherwise be in hospital – fit in future planning. Meanwhile, virtual ward technology suppliers told HSJ that some systems have had budgets reduced or paused, and others have been told to demonstrate clearer cash-releasing impact of virtual wards before further expansion. Read full story (paywalled) Source: HSJ, 16 March 2026

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