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The conversation around Artificial Intelligence in healthcare is evolving. We are moving beyond the hype of algorithms and automation, and beginning to ask the more important questions: How do we ensure AI serves our people and patients? How do we adopt it in ways that strengthen the health and care system as a whole? What kind of leadership do we need to make that happen? More than that, how do we harness the reality of AI now even as we set a path for AI in the future? It is no longer enough to explore what AI can do. We must focus on how it should be done and why. Dr Nnenna Osuji explores the shift from 'what' to 'how' in her blog. Related reading on the hub: AI in London healthcare: The reality behind the hype- Posted
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Artificial intelligence (AI) is often portrayed with the ability to transform the delivery of care, improving patient outcomes, and easing pressures on an overstretched health system. While its potential is undeniable, the conversation around AI can sometimes become tangled with hype, complexity, and uncertainty. The reality is that AI is not a magic bullet, but another tool in our broader mission to solve the pressing healthcare challenges we are facing and redesign a more resilient health system. London is uniquely positioned to lead the way in transforming healthcare delivery, access, and experience. With world-class medical institutions, top-tier universities, and a thriving tech ecosystem, the city is at the forefront of innovation. Its rich, diverse multimodal data resources could further help to advance AI development. Many London NHS providers are already pioneering AI adoption, piloting solutions in diagnostics, workflow automation, and intelligent proactive care, exploring the art of possible of AI to drive smarter, more efficient, and patient. However, every deployment of AI needs to be purposeful, evidence-based, and aligned with real system needs. This report from the UCL Partners Health Innovation is about cutting through the noise around AI, and offering a better understanding of its current adoption within the London system. It presents insights from across different providers into where AI is making an impact, the obstacles its facing, and what needs to change to unlock its potential.- Posted
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The World Health Organization (WHO) has published a new edition of this guidance on health technology assessment (HTA) for medical devices. Health technology assessment (HTA) is described as ‘a well-recognised and methodologically robust evidence-based priority-setting process used to provide information on the safety, efficacy, quality, appropriateness, and cost-effectiveness of health technologies’. This document ‘is intended to provide guidance to policy-makers, particularly those in low- and middle-income countries that are currently developing HTA capacity.’ The document describes ‘general concepts of HTA and points to best-practice resources to enable low- and middle-income countries to make consistent, transparent and informed decision-making on the adoption and use of medical devices to ensure clinical needs are met whilst delivering value to patients, healthcare providers, and the broader health system.’- Posted
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New technology should be paid for ‘like medicines’, says NICE chief executive
Patient Safety Learning posted a news article in News
The purchase of approved digital products and services used for diagnosing and treating NHS patients should be reimbursed centrally, the chief executive of the National Institute of Health and Clinical Excellence has told HSJ. Sam Roberts said this was “the minimum a citizen should expect from a digitised health service” and that she was determined “to get that into the [government’s 10-Year Health] plan”. She described the different financial arrangements for NICE-approved digital products and services as “outrageous”, and said they should instead be treated “like medicines”. In a wide-ranging interview with HSJ, the NICE CEO also said: She wanted NICE to “lead the charge” in determining which digital innovations the NHS should adopt NICE would issue more guidance on which medicines it had previously recommended should no longer be used A new approach was needed to deal with the impending wave of expensive “preventive medicines” such as the new wave of weight-loss drugs. Read full story (paywalled) Source: HSJ, 3 June 2025- Posted
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Basic errors lay behind trust’s botched IT upgrade, leak reveals
Patient Safety Learning posted a news article in News
A string of basic errors led to a teaching trust botching a pathology lab IT upgrade, causing major disruption to tests, according to an internal review seen by HSJ. The problems with Leeds Teaching Hospitals Trust’s upgrade to the Clinisys WinPath system in December resulted in tens of thousands of blood tests being lost or delayed, with managers admitting patients were potentially put at risk. An internal LTHT review of how “communication and escalation” problems contributed to the disruption, including: Training delivered very late – even on the day of roll out – or not at all. No end-to-end testing of the system took place prior to roll out. There was no engagement with primary care to understand how the update could affect their workflows. Ineffective communication channels for escalation of problems. Lessons from previous NHS WinPath roll outs were not learned. Read full story (paywalled) Source: HSJ, 30 May 2025- Posted
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How remote patient monitoring is revolutionising patient safety
Lesley Barton posted an article in Telehealth
This article explores how remote patient monitoring (RPM) is transforming patient safety by enabling continuous, real-time tracking of health data outside clinical settings. It provides a comprehensive overview of RPM technologies, their clinical benefits, implementation challenges and best practices. It highlights the growing importance of RPM in proactive care models and its role in reducing hospital readmissions, improving medication adherence and supporting vulnerable patient populations. How is remote patient monitoring changing patient safety? A Mass General Brigham study of 10,803 participants found that RPM reduced mean blood pressure from 150/83 to 145/83, which significantly lowers cardiovascular disease risk.[1] RPM technologies provide clinicians with real-time data streams; this allows for quick interventions when patient conditions change. The continuous monitoring bridges dangerous gaps between appointments where medical complications developed undetected. Beyond crisis prevention, RPM enhances medication safety through adherence tracking and creates comprehensive longitudinal health records revealing subtle trends conventional episodic care might miss. The benefits reach vulnerable groups—elderly, rural and mobility-limited patients—who now get regular supervision free of transportation constraints, creating safety nets once inaccessible under conventional care models. Real-time monitoring: a lifeline for early intervention and patient safety RPM provides regular data collection that serves as a buffer against avoidable harm by detecting minute physiological changes that indicate clinical deterioration. RPM significantly bolsters patient safety by enabling early detection of health deteriorations, thereby facilitating timely interventions. A study published in NPJ Digital Medicine analysed 29 studies across 16 countries and found that RPM interventions led to a reduction in hospital readmissions and emergency department visits.[2] Specifically, the study highlighted that RPM demonstrated positive outcomes in patient safety and adherence, and improved patients' mobility and functional statuses. This early warning feature considerably improves patient safety by enabling timely clinical interventions before symptoms worsen. A known patient with serious congestive heart failure can also be given diuretic adjustments remotely, avoiding hospitalisation. RPM also decreases the risks associated with medications by enabling physicians to identify missed doses and adverse reactions. Long-term data further strengthens safety by showing patterns—like low oxygen levels at night in chronic obstructive pulmonary disease (COPD) patients—that single tests might miss. Personalised interventions are supported by this fine-grained understanding, especially for high-risk populations such as patients living in rural areas that have improved access to attentive monitoring. By combining speed and accuracy, RPM transforms patient safety to an actionable, data-driven and efficient procedure rather than a fixed objective. Key technologies driving remote patient monitoring: enabling safer, data-driven care Remote patient monitoring depends on a complex ecosystem of linked technology that extends clinical supervision outside of facility boundaries. Wearable devices form the basic foundation of this system—with regulatory-approved sensors capturing vital metrics continuously. RPM is transforming healthcare by shifting from reactive to proactive safety strategies. These digital systems continuously track vital signs, medication compliance and physiological parameters outside traditional clinical settings. This enables early detection of deterioration before serious complications arise. Advanced cardiac monitors identify arrhythmias with 98% accuracy and smart glucose sensors provide real-time glycaemic information via subcutaneous readings. Connected devices for tracking urinary patterns help physicians diagnose various types of incontinence without requiring in-person assessments, improving dignity and convenience for patients with mobility challenges. Smart inhalers with embedded sensors record medication usage patterns and technique, enabling precise interventions for respiratory conditions. Mobile applications are a link between patients and clinical teams—with simple dashboards that show health trends and medication adherence. These platforms usually combine clinical protocols, secure messaging systems and alerts based on preset thresholds. Backend analytics platforms transform raw physiological data into clinically relevant insights through sophisticated algorithms. These systems analyse longitudinal data against established baselines to detect minor abnormalities that precede clinical deterioration. According to studies, these predictive capacities can detect sepsis 6–12 hours earlier than traditional approaches, considerably increasing survival rates.[3] Secure, Health Insurance Portability and Accountability Act (HIPAA) compliant electronic health record (EHR) integration—using end-to-end encryption and strict authentication—creates comprehensive patient profiles, enabling better-informed treatment decisions. Implementing remote patient monitoring: main challenges RPM has numerous benefits in healthcare, but putting it into practice involves challenges that need thoughtful solutions. Digital literacy gaps create accessibility barriers, particularly among elderly populations where only 64% report comfort with technology-based healthcare tools according to the Journal of the American Geriatrics Society survey of 3,450 seniors.[4] Privacy concerns are significant as continuous monitoring generates sensitive health data that requires strong security. To maintain patient trust while meeting regulatory standards, healthcare centres must use end-to-end encryption, unambiguous consent mechanisms and transparent data governance frameworks. Another problem is clinical workflow integration; RPM systems that function without the use of EHR platforms result in documentation silos. Customised integration pathways that embed remote monitoring data within regular clinical interfaces are required for successful RPM implementation. When clinicians get an overwhelming number of notifications, the intended safety benefits are undermined. Effective systems use tiered alert processes with tailored thresholds that are based on patient baselines rather than population norms. These graduated notification systems ensure that important notifications receive necessary attention while preventing frequent low-risk alerts. As healthcare organisations face these issues, good implementation frameworks that include technical assistance, privacy safeguards and workflow optimisation are relevant to fulfilling RPM's full potential. Best practices for patient-centered remote monitoring Effective RPM is beyond technological equipment; it requires an effective structure that can only come from consistent planning and review. Healthcare organisations should establish dedicated implementation teams comprising clinicians, IT staff and patient advocates to gather diverse viewpoints and boost adoption of RPM. This cross-functional strategy improves RPM acceptance and sustainability while lowering possible resistance. Healthcare administrators should train providers thoroughly on both technical use of medical devices and data interpretation. A 2023 NEJM Catalyst study of 76 healthcare centres showed that centres with robust training of healthcare professionals had 43% higher RPM use after a year compared to those with minimal training.[5] Healthcare professionals should also be trained to focus equally on patient support through easy enrolment, clear instructions in multiple languages and in-person device training. Dedicated tech support channels should be created for RPM users in order to prevent frustration whenever there is a network glitch. Clear clinical protocols defining intervention thresholds, escalation pathways and response timeframes should be made to transform data into actionable intelligence. Rigorous quality assurance measures—including regular connectivity testing, data validation audits and patient usability assessments—safeguard programme integrity. Periodic review cycles examining alert frequency, response times and intervention outcomes help refine system parameters for maximum clinical utility. The most effective RPM programmes integrate patient feedback mechanisms allowing continuous refinement of interfaces, alert frequencies, and educational materials based on real-world experience. Conclusion RPM is improving healthcare from reactive to preventive care. As technology advances, these systems will become standard practice. Future developments will include smaller sensors, longer battery life and better connectivity—making monitoring easier for patients while improving data quality. Better predictive analytics will help physicians identify health problems earlier with greater accuracy. Beyond helping patients, RPM is changing organisational safety culture by expanding care beyond hospitals. This shift represents a major advancement—creating continuous monitoring systems that protect patients throughout their healthcare journey and redefining patient safety for modern medicine. References 1. Mass General Brigham. Mass General Brigham Remote Healthcare Delivery Program Improves Blood Pressure and Cholesterol Level, 9 November 2022. 2. Ying Tan S, et al. A systematic review of the impacts of remote patient monitoring (RPM) interventions on safety, adherence, quality-of-life and cost-related outcomes. NPJ Digital Medicine 2024; 7: 192. 3. King J, et al. Early Recognition and Initial Management of Sepsis in Adult Patients. Ann Arbor (MI): Michigan Medicine University of Michigan, 2023. 4. American Geriatrics Society 2024 Annual Scientific Meeting. Journal of the American Geriatrics Society 2024; 72: III-VI. 5. Barrett JB, et al. Reduced Hospital Readmissions Through Personalized Care: Implementation of a Patient, Risk-Focused Hospital-Wide Discharge Care Center. NEJM Catal Innov Care Deliv 2025;6(6). DOI: 10.1056/CAT.24.0420. Further reading on the hub Putting patients at the heart of digital health Digital diagnosis—what the doctor ordered? Electronic patient record systems: Putting patient safety at the heart of implementation How do we harness technology responsibly to safeguard and improve patient care?- Posted
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Medication dosing errors occur frequently and contribute to preventable patient harm and negative outcomes (including numerous patient deaths each year in the US). Dosing errors are particularly common in neonatal and paediatric populations, where weight-based dosing is often required and drug formulations are commonly tailored towards adult populations. Hospitalised neonates require frequent dosing adjustments as their weights can change substantially over the course of their hospitalization and even day to day, increasing the potential for dosing errors. Technologies such as computerised order entry, clinical decision support systems, and electronic prescribing strategies have been used to improve dosing accuracy and prevent adverse drug events with mixed results. Additionally, paediatric functionalities are often not integrated into electronic health records (EHR) or tools tailored to the adult population are incorrectly applied to paediatric patients. In this issue of Pediatric Research, Levin and colleagues compared the accuracy of three Large Language Models (LLMs) to nurses of varying clinical backgrounds and experience levels in calculating paediatric medication dosing. Although this study focused on nurses, it applies to all healthcare providers. Medication dosing errors do not occur in a vacuum and it is the responsibility of all healthcare providers (including nurses, physicians, pharmacists, technicians, etc.) to ensure that medications are given at the correct dose, route, interval, and duration.- Posted
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The NHS and social care systems in England are on a journey towards digitalisation. One particular technology that is generating high levels of both excitement and scepticism is artificial intelligence (AI). While many are excited by the opportunities offered by AI, others may be feeling more doubtful or unsure. This long read from the King's Fund provides context for how this technology is, or could be, applied. Further reading on the hub: How do we harness technology responsibly to safeguard and improve patient care? Putting patients at the heart of digital health- Posted
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Leadership Futures recently published a report 'Harnessing technology for human progress: Advancing into Industry 5.0', which is driven by a bold ambition: to transform organisations worldwide through technological advancements. In this blog, Caroline Beardall looks at the implications of this for healthcare and suggests five actions that organisation's should take to ensure we achieve the benefits from technology while keeping patient safety at the forefront of an evolving landscape. The recent Leadership Futures report 'Harnessing technology for human progress: Advancing into Industry 5.0' provides a valuable framework for integrating technology with human-centered leadership, which is highly applicable to advancing patient safety in health and care. Its vision of Industry 5.0 as a collaborative human-AI partnership offers a route to reduce errors, enhance clinician capacity and improve patient outcomes. However, realising these benefits requires caution—ethical and inclusive implementation strategies that address the complexities and risks unique to health and care settings. It throws up three fundamental challenges: How can healthcare leaders ensure AI tools are safe to use and that clinical staff can trust them? Who should be responsible if an AI system makes a mistake that affects a patient? How can healthcare organisations use technology to work better without losing the importance of human interaction and the skills needed for high levels of patient satisfaction and safety? In order to answer these questions, and deepen the discussion on harnessing technology responsibly to safeguard and improve patient care, there are some actions we can take to build on the report and begin to gain evidence and experience specific to healthcare. As the landscape of healthcare shifts and evolves, we should consider applying the following five actions (with examples of how to do this) so we can achieve the maximum benefits from technology for patient safety. 1. Foster collective, collaborative leadership across boundaries Leaders should actively promote cooperation and shared responsibility across organisational and professional boundaries, focusing on the overall patient journey rather than siloed departmental goals. This aligns with the report’s emphasis on human-machine collaboration and the need for integrative leadership cultures that support safe, seamless care delivery. By working collectively, leaders can ensure technology is implemented with broad input and oversight, reducing risks and enhancing patient safety. Implement interdisciplinary collaboration practices: Organise regular team meetings involving diverse healthcare professionals to discuss patient care holistically, ensuring all voices contribute to decision making. Create shared goals and aligned metrics: Develop common objectives focused on patient safety and quality that unify departments and reduce siloed working. Lead by example: Demonstrate collaborative behaviours and openness to input, encouraging a culture of trust and teamwork. 2. Embed ethical, human-centred use of technology Leaders must champion ethical principles in technology adoption, ensuring AI and digital tools augment rather than replace human judgment and empathy. This includes rigorous validation of new technologies, transparency in AI decision-making, and ongoing monitoring to prevent harm or bias. Prioritising patient experience and human values in technology deployment safeguards safety and trust. Prioritise transparency and clinician involvement: Engage frontline staff early in AI and technology design and deployment to ensure tools meet clinical needs and ethical standards. Establish continuous monitoring and feedback loops: Use data and user feedback to identify and mitigate risks or biases in technology that could impact patient safety. Promote ethical leadership training: Equip leaders with skills to balance innovation with patient experience and accountability. 3. Develop and support workforce readiness and engagement Preparing staff to work effectively alongside new technologies is vital. Leaders should invest in training that builds digital literacy, critical thinking and resilience, while also fostering a positive work climate where staff feel valued and supported. Engaged and confident clinicians are better able to use technology safely and maintain high standards of care. Invest in targeted training and digital upskilling: Provide contextual, in-app guidance and interactive training to help staff adopt new technologies confidently and efficiently. Foster a culture of psychological safety and empowerment: Encourage open discussion, honest feedback and staff involvement in decision making to build trust and resilience. Practice empathetic leadership: Focus on emotional and professional needs of staff to reduce burnout and improve engagement. 4. Set clear, aligned objectives focused on quality and safety Leadership should establish clear, challenging and aligned goals at every level that prioritise patient safety and quality improvement over mere efficiency or target-driven metrics. This clarity helps reduce staff stress and confusion, enabling teams to focus on delivering compassionate, safe care supported by technology. Communicate clear expectations and priorities: Use consistent, transparent communication to align teams around patient safety goals and reduce ambiguity. Implement continuous feedback and learning systems: Regularly review performance data and patient feedback to refine objectives and improve care quality. Balance efficiency with human factors: Ensure operational goals do not compromise critical human skills or patient-centred care. 5. Champion diversity, inclusion and accountability in leadership Inclusive leadership practices that promote equality and diversity are essential to fostering innovation and ethical decision-making in healthcare technology adoption. Leaders must also clarify accountability frameworks for technology-related decisions and errors, ensuring responsibility is shared and transparent to maintain patient safety. Promote inclusive leadership practices: Value diverse perspectives and foster equity to enhance innovation and ethical decision-making Clarify accountability frameworks: Define roles and responsibilities clearly, especially concerning technology-related decisions and errors, to maintain trust and safety Model human-centred leadership traits: Practice self-awareness, compassion and mindfulness to create cultures of excellence, trust, and caring. By integrating these strategies, human-centric leaders can effectively translate the insights from the Leadership Futures report into practical actions that improve patient safety, staff satisfaction and overall health system resilience. This approach embraces complexity and change as opportunities, not obstacles, which then enables sustainable progress in better health and care delivery. Further reading Amelia N. 6 Effective Leadership Strategies for Healthcare in 2025. Edstellar, 31 December 2024. West M, et al. Leadership in Healthcare: a Summary of the Evidence Base. Kings Fund; Faculty of Medical Leadership and Management; Center for Creative Leadership, 2015. LeClerc L, Kennedy K, Campis S. Human-Centered Leadership in Health Care: An Idea That's Time Has Come. Nursing Administration Quarterly 2020; 44(2):p 117-26.- Posted
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Large Language Models (LLMs) are transforming the way in which people interact with artificial intelligence. This study explores how safety professionals might use LLMs for a FRAM analysis. The authors use interactive prompting with Google Bard / Gemini and ChatGPT to do a FRAM analysis on examples from healthcare and aviation. The exploratory findings suggest that LLMs afford safety analysts the opportunity to enhance the FRAM analysis by facilitating initial model generation and offering different perspectives. Responsible and effective utilisation of LLMs requires careful consideration of their limitations as well as their abilities. Human expertise is crucial both with regards to validating the output of the LLM as well as in developing meaningful interactive prompting strategies to take advantage of LLM capabilities such as self-critiquing from different perspectives. Further research is required on effective prompting strategies, and to address ethical concerns.- Posted
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Physician burnout persists in USA. In part, this burnout is believed to be driven by the Electronic Health Record (EHR) and its fraught role in the clinical work of physicians. Artificial intelligence (AI)-enabled healthcare technologies are often promoted on the basis of their promise to reduce burnout by introducing efficiencies into clinical work, particularly related to EHR utilisation and documentation. Where documentation is perceived as the problem, AI scribes are offered as the solution. This essay looks closely at existing studies of AI scribes in clinical context and draws upon experience and understanding of healthcare delivery and the EHR to anticipate how AI may related to provider burnout. The authors find that it is premature to assert that AI tools will reduce physician burnout. Considering the integration of AI scribes into Learning Health Systems healthcare delivery becomes a starting point for understanding the challenges faced in safely adopting AI tools more generally, with attention to the healthcare workforce and patients. The authors found that it is not a foregone conclusion that AI-enabled healthcare technologies, in their current state and application, will lead to improved healthcare delivery and reduced burnout. Instead, this is an open question that demands rigorous evaluation and high standards of evidence before we restructure the work of physicians and redefine the care of our patients. -
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Tech is helping GPs and clinicians see more patients
Patient Safety Learning posted a news article in News
New figures from the NHS reveal that 31.4 million GP appointments were delivered in March 2025, a 6.1% increase on the same period last year and nearly 20% more than before the pandemic. This increase, the NHS claims, is due to GP practices adopting digital services to help meet growing demand while ensuring patients are directed to the right care more efficiently. Starting in October, all GP surgeries will be required to offer online appointment requests throughout working hours as part of a new contract, which aims to ease phone line pressure and allow smarter triaging based on medical need. Currently, 99% of GP practices in England have already upgraded their phone systems, expanding capacity and reducing long waits for patients. Professor Bola Owolabi, NHS England’s director of healthcare inequalities, said in a statement: “GP teams are delivering over 30 million appointments a month, up nearly 20% on pre-pandemic levels. Patients can also manage repeat prescriptions and view test results through the NHS App, making care more convenient.” The NHS has also announced that AI is enabling GPs and clinicians to cut the time spent on admin and increase the time and effort expended on patients. Data from AI trials shows an increase in patients seen by A&E, shorter appointments and more time by clinicians spent with the patient. Read full story Source: UK Authority, 30 April 2025- Posted
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NHSE could impose new cancer system on struggling trusts
Patient Safety Learning posted a news article in News
Trusts failing to meet cancer standards may be encouraged to use a new tool on the federated data platform, HSJ understands. NHS England today announced the launch of the Cancer 360 tool on the FDP, which it says will help clinicians to “identify and address delays immediately” in cancer treatment pathways. In a media briefing attended by HSJ, NHSE said no trust would be “forced” to take up the tool. It said there would be “no questions asked” if another system was already in place and the organisation was meeting performance targets, such as the faster diagnosis or 62-day referral-to-treatment standards. However, there “would be a conversation” about the need to use Cancer 360 if a trust had another system in place and was not meeting standards, officials confirmed. Read full story (paywalled) Source: HSJ, 4 May 2025- Posted
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Orthopaedic surgeon Sunny Deo has spent three decades diagnosing and treating knee joint issues. In this blog, Sunny argues that the healthcare community needs to take a more nuanced approach to diagnosis and decision making so that it can provide patients with safer, more appropriate treatment options. He reflects on why medicine prefers simple answers and looks at how this affects patient care. He goes on to explore how better data collection and the use of artificial intelligence (AI) could provide a more accurate picture of complexity and allow treatment options to be better tailored to individual patients’ needs. "To know the patient that has the disease is more important than to know the disease that the patient has." William Osler, father of modern medicine, 1849-1919. Diagnosis is the process of identifying the nature of an illness or other problem by examining the symptoms and objective findings from investigations. In modern medicine, it is a key focal point of the assessment and management of all patients. A huge amount of clinical medicine training is focused on the art and science of obtaining a diagnosis, and this focus continues into medical practice. The ease of getting to a diagnosis ranges from the glaringly obvious, the so-called ‘spot diagnosis’, through to cases that are very difficult to solve. In between these extremes there is a range from delayed to missed to incorrect diagnosis. The aim of doctors over the centuries has been to work out diagnoses from patients’ symptoms, presenting features (clinical signs) and, in the past century or so, from the evidence of clinical investigations. Quite often, symptoms, signs and investigations produce consistent patterns, and it is these patterns that are taught to medical and other healthcare professionals. This is how diagnoses and outcomes are portrayed in television series or films—just think back to the last episode of Casualty or Grey’s Anatomy you watched. It's also how things often appear in internet searches and on websites and social media. Seeking simple answers to complex questions However, the reality is different. When a patient is sitting in front of me, what I hear and observe may not exactly be what the textbooks, evidence or research tells me I should be seeing. But because we are wired and trained to recognise patterns, we tend to look for diagnoses and solutions that fit within the well-worn narrative. What if the pattern doesn’t fit the actual diagnosis? There are classic presentations for nearly every condition, and these are what you tend to find at the start of a Google search or when using NHS Choices. The expectation of typical symptoms sometimes means we ignore what we might see as annoying variance, superfluous detail or the patient embellishing the truth. This discordance then causes tension with a very basic trait of humans: when we’re faced with a difficult problem, we still seek the simplest solution. This is an evolutionary feature hardwired into us to optimise survival chances. It means we often believe there is a truth to be found that will provide us with a definite answer. From this answer we will come to the best, and ideally only, ‘correct’ solution. Patients who don’t fit the set patterns of diagnosis may then run into trouble when we offer them what is considered to be the ideal treatment. This is an important problem in clinical thinking, language and practice. As a medical community, we tend to create oversimplified approaches based on research that looks for binary answers to complex questions. This research evidence may be based on a small, highly selective ‘typical’ patient cohort, but its findings and conclusions are then translated on to the entire population. This approach results in poor patient outcomes and experience for a small but significant proportion of patients. Pathways designed for ideal diagnoses can cause harm to patients Over my 30 years as an orthopaedic surgeon, 15 as a knee specialist, I have seen that the assessment and treatment of any given condition isn't quite as predictable as we would like it to be. While many patients fit the pattern we are expecting, some do not. I would empirically put the proportion at 60:40, but some unpublished research we did a decade ago suggested the proportion of truly ‘typical’ case presentations for a common condition is much lower. For example, we found that in the case of suspected meniscal tear, this diagnosis actually applied to only 33% of patients with a variety of other diagnoses accounting for the rest. It gets worse when large organisations start to lump patients into a category by condition in a ‘one diagnosis fits all’ strategy. When this approach is taken, there are winners and losers. The winners are those patients whose condition very closely matches the classic presentation of a given condition in isolation. Let’s take the example of knee osteoarthritis—patients with the ‘right type’ of symptoms, physical signs and x-ray changes are generally more likely to do well. Their recovery is more likely to sit within the knowledge base of treating the condition that has evolved over the past half-century. In contrast, patients whose symptoms and test results fall outside of this category may be less likely to do well or recover in the predicted timeframe. This also applies to patients with additional diagnoses or conditions, often termed comorbidities, which may interact, usually in a bad way, with the condition at hand. Failure to consider other diagnoses, either by over-focus on one condition causing wilful ignorance, inattention or lack of attention, may lead to unexpected poor outcomes from a given treatment. It may also mean that the symptoms from the condition that the patient presents with are worse than expected. This doesn’t mean that they won't gain any benefit from a particular treatment, but the risks and potential outcomes may not be communicated adequately by the patient’s healthcare team, if at all. For example, for patients with painful knee osteoarthritis, the current diagnosis to treatment logic runs like this: Knee osteoarthritis is a painful condition. Total knee replacement surgery is a validated safe procedure with significant improvements in quality of life. Other treatment options do not produce as much positive therapeutic benefit compared to total knee replacement surgery. Therefore, total knee replacement surgery is the only treatment for painful knee osteoarthritis. However, there are patients for whom knee replacement surgery is not a safe or practical option, and these patients may benefit from alternative treatments that are not currently offered as they are seen as providing limited benefit. This may be because the participants in trials undertaken over the years had varying diagnoses, meaning that true comparisons of alternative options may have had additional interacting diagnoses or failed to account for differing severity. Understanding the spectrum of complexity As healthcare professionals, we have a duty to diagnose patients as accurately as possible. In orthopaedics, if treatments go wrong or are poorly undertaken, it may lead to prolonged or permanent pain or disability, and we obviously want to avoid this as much as possible. Incomplete identification and documentation of all relevant symptoms and health conditions can potentially lead to an increased risk of treatment failure and complications. Our priority should be to identify these diagnoses or diagnostic clusters as accurately as possible. I think these are basic principles we need to apply to create better systems and improved care for as many patients as possible. In my view, there are grades of ‘atypical patients’ and I have devoted the past decade to trying to demonstrate this, with surprisingly stiff resistance from peer-reviewed journals and funding organisations. I have tried to move away from lumping all patients into a single category. I have done some research on seemingly straightforward soft tissue problems and osteoarthritis in the knee. My initial analysis suggests that we need to collect more detailed and accurate data, rather than simplifying data into minimum datasets. This is where AI can really come into its own, not as a diagnostic tool initially, but as a powerful aid to unlocking and interpreting some of the diagnostic interactions that create problems for patients. However, the use of AI does need to be undertaken with extreme care and consideration, and this isn’t always happening currently. To offer healthcare that is truly person-centred, we need to look beyond our well-worn simple answers and solutions. By using better data and new machine learning tools to understand the nuances of each person’s condition and how it relates to their wider health, we can offer treatment options that are safer, kinder and more cost-effective. Share your views We would love to hear your views on the issues highlighted in Sunny’s blog Are you a clinician who would like to share your experiences? Do these challenges resonate with you? Or are you a patient who has experienced complications because of poor, missed or inadequate diagnosis? Add your comment below (you will need to be a hub member and signed in) or contact us at [email protected] and we can share your story anonymously. Related content on the hub: Using data to improve decision making and person-centred care in surgery: An interview with Sunny Deo and Matthew Bacon Diagnostic errors and delays: why quality investigations are key- Posted
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The rapid evolution of digital health technologies offers new opportunities for healthcare systems while also increasing pressure on public budgets. Governments and insurers face growing challenges in determining what to fund and at what price. Health technology assessment (HTA) remains a critical tool for informing these decisions, and several OECD countries are exploring ways to adapt their approaches to the fast-changing and diverse landscape of digital medical devices. The absence of a common taxonomy, coupled with the rapid pace of technological advancement, further complicates evaluation, prompting interest in more harmonised HTA approaches. This paper explores how France, Germany, Israel, Korea, Spain, and the United Kingdom are adapting HTA to evaluate certain types of digital medical devices for coverage and pricing decisions. Through desk research and interviews, it describes HTA approaches, focusing on relevant pathways, technology remits, and evaluation methods. Drawing on practical experiences, it highlights key challenges and potential learning opportunities. The findings contribute to ongoing discussions on adapting HTA frameworks to improve the assessment and integration of digital medical devices into healthcare systems.- Posted
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In the ever-evolving landscape of healthcare, patient safety and quality care remain the cornerstones of effective medical practice. Every day, healthcare professionals strive to provide treatments that not only heal but also protect patients from harm. As a passionate advocate for patient-centred care, Ssuuna Mujib, a volunteer at the Uganda Alliance of Patients' Organisations, believes that prioritising safety is not just a responsibility—it’s a moral imperative that shapes trust, outcomes and the future of healthcare. The importance of patient safety Patient safety refers to the prevention of errors and adverse effects associated with healthcare delivery. According to the World Health Organization (WHO), millions of patients worldwide suffer from preventable harm due to unsafe care each year. These incidents can range from medication errors to hospital-acquired infections, surgical complications or misdiagnoses. The consequences are profound, affecting patients’ lives, increasing healthcare costs and eroding trust in medical systems. Ensuring patient safety requires a multifaceted approach that involves healthcare providers, administrators, policymakers and patients themselves. By fostering a culture of safety, we can minimise risks and create an environment where quality care thrives. Key strategies for improving patient safety and care To deliver exceptional care while safeguarding patients, healthcare systems must adopt evidence-based practices and innovative solutions. Here are some critical strategies to enhance patient safety: 1. Effective communication Clear and open communication among healthcare teams is vital. Miscommunication can lead to errors, such as administering the wrong medication or misinterpreting a patient’s condition. Standardised tools like SBAR (Situation, Background, Assessment, Recommendation) can improve handoffs and ensure critical information is shared accurately. 2. Robust training and education Continuous professional development ensures that healthcare workers stay updated on best practices and emerging technologies. Training programmes should emphasise error prevention, infection control and patient engagement. Empowering staff with knowledge builds confidence and competence in delivering safe care. 3. Leveraging technology Technology plays a transformative role in patient safety. Electronic Health Records (EHRs) reduce documentation errors, while barcode medication administration systems help verify medications before they reach patients. Additionally, artificial intelligence tools can predict risks, such as sepsis, enabling early interventions. 4. Patient empowerment Patients are active partners in their care. Encouraging them to ask questions, understand their treatment plans and report concerns fosters shared decision making. Educating patients about their medications and procedures can prevent errors and enhance adherence. 5. Creating a culture of safety A blame-free environment encourages healthcare workers to report errors or near-misses without fear of retribution. Root Cause Analysis (RCA) and Failure Modes and Effects Analysis (FMEA) can identify systemic issues and drive improvements. Leadership must champion safety as a core value, setting the tone for the entire organisation. The role of compassion in patient care While systems and protocols are essential, the human element of care cannot be overlooked. Compassionate care builds trust and promotes healing. Listening to patients, respecting their dignity and addressing their fears create a therapeutic environment. When patients feel valued, they are more likely to engage in their treatment plans and communicate openly, reducing the risk of errors. Challenges and the path forward Despite progress, challenges like understaffing, resource constraints and burnout continue to threaten patient safety across the world. Addressing these requires investment in workforce development, equitable resource allocation and mental health support for healthcare workers. Collaboration between governments, healthcare institutions and communities is crucial to overcoming these barriers. Looking ahead, the integration of data analytics, telemedicine, and patient-reported outcomes will further revolutionise safety and care. By embracing innovation while staying grounded in empathy, we can build a healthcare system that is both safe and compassionate. A call to action Patient safety and care are shared responsibilities. As healthcare professionals, we must commit to continuous improvement, learning from mistakes and advocating for our patients. As patients, we should actively participate in our care and hold systems accountable. Together, we can create a future where every patient receives safe, high-quality care. Let’s work hand in hand to make patient safety not just a goal, but a reality.- Posted
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Event
HIMSS25 - European Health Conference & Exhibition
Mark Hughes posted an event in Community Calendar
untilThis HIMSS flagship event is Europe’s leading digital health conference. With expert-led sessions, it’s a chance for health tech leaders to network, share ideas, discuss real-world data and build partnerships. Attendees include CIOs and senior executives, health providers and payers, C-Suite tech leaders and entrepreneurs, and government officials. You can find the programme for the event here. You can find registration details here.- Posted
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News Article
Flagship NHSE tech policy creating ‘patient safety risks’, claim analysts
Patient Safety Learning posted a news article in News
Patient safety risks are being created by central demands that NHS organisations adopt the new federated data platform and “close down” existing systems, according to the body representing the service’s analysts. In a letter to NHS England chief data and analytics officer Ming Tang, the Chief Data and Analytical Officers Network (CDAON) has stepped up earlier complaints about the FDP and its rollout, calling for a “reset” of NHSE’s approach. The letter also questions whether the FDP is fit for purpose in achieving the government’s goal of moving care into the community. The £330m seven-year contract to deliver the FDP platform was won by US data company Palantir in 2023. The FDP was originally launched on the basis that it could be used on a voluntary basis. However, under direction of ministers, NHSE has now moved to an “FDP-first policy”, to the alarm of many senior figures working in NHS technology. The letter, seen by HSJ, is signed by CDAON chair and Kent and Medway Integrated Care Board data chief Marc Farr and says: “Anecdotally we are aware of systems being directed to close down existing systems because the functionality is planned within the FDP… “However we are not convinced that the functionality is imminent and therefore that a risk to patient safety exists – we can cite specific examples.” Read full story (paywalled) Source: HSJ, 23 April 2025- Posted
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Lord Darzi’s review into the future of the NHS calls for a “tilt towards technology” to unlock greater productivity. But there’s a hard reality: many parts of the NHS aren’t yet ready to take advantage of what tech has to offer. Meaning, there’s a missed opportunity for trusts to streamline operations and transform care. Only one in five NHS organisations are considered “digitally mature”. And despite lots of progress in the last decade, there are still areas of the NHS relying on paper and non-digital processes. It makes embracing new technologies, such as AI, feel like an unattainable goal – one that goes beyond moving the health service from analogue to digital. As we enter this new era for the NHS, data and digital skills across the workforce will be fundamental to improving patient care, streamlining processes, and making cost savings. -
News Article
A growing number of healthcare workers and patients are demanding immediate legislative action to address rising workplace violence in hospitals, a survey by Black Book Research has found. The survey, which included responses from 240 individuals — emergency department physicians, nurses, hospital-based staff and 200 healthcare consumers — reveals widespread concern over increasing aggression toward medical professionals and overwhelming support for federal intervention. Key findings show that 98% of hospital staff and 93% of healthcare consumers support federal legislation mandating workplace violence prevention measures. All staff respondents said they had experienced or witnessed violence at work, with many expressing dissatisfaction with current safety protocols. According to the U.S. Bureau of Labor Statistics, an average of 57 healthcare workers are injured daily due to workplace violence, resulting in lost workdays, job reassignment or medical care. Incidents range from verbal threats and physical assaults to chronic aggression, particularly in emergency departments and behavioral health units. “Technology is now a cornerstone of prevention strategies in hospital safety plans,” Doug Brown, founder of Black Book Research, said in the report. “Healthcare IT vendors play a vital role in safeguarding hospital staff by embedding safety-focused features into the software and services used every day.” Read full story Source: Becker's Health IT, 14 April 2025- Posted
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The transition into Industry 5.0 is driven by a bold ambition: to transform organisations worldwide through technological advancements. As leaders navigate this era of unprecedented digital transformation, they must confront the challenges posed by emerging technologies as they begin to impact traditional work structures, employee productivity, organisational security and workforce dynamics. The rise of generative artificial intelligence (AI), digital tools and other technological innovations brings both promise and confusion. But it also presents an unparalleled opportunity: to redefine the role of human labour. To effect real change, leaders must meet this moment head on. By shifting from routine, repetitive tasks to higher-order, creative and strategic roles, organisations can unlock innovation, value and progress on a transformative scale, This report explores the importance of a human-centred approach to technological adoption. It emphasises the need for leaders to prepare their workforces for disruption, integrate AI as a force for good and embrace their ethical responsibilities in guiding their organisations forward. Additionally, it provides actionable insights into effective change management strategies, equipping leaders to navigate the complexities of AI and technological transformation with confidence and purpose.- Posted
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Live stream recording of Day 1 of the 7th Global Summit on Patient Safety, organised by the Department of Health of the Republic of the Philippines and co-sponsored by the World Health Organization (WHO). This event focuses on advancing international efforts to improve healthcare quality and safeguard patients worldwide. It brings together global leaders, experts and stakeholders to discuss and shape the future of patient safety. Advancing Patient Safety Reporting and Learning Systems can be found at 2:46:57 Plenary 3 on AI and health can be found at 08:05:10 Related reading on the hub: 15 hub top picks for the 7th Global Ministerial Summit for Patient Safety- Posted
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News Article
Ministers have cut millions of pounds of funding for potentially life saving AI cancer technology in England, which cancer experts warn will increase waiting times and could cause more patients to die. Contouring is used in radiotherapy to ensure treatment is as effective and safe as possible. The tumour and normal tissue is “mapped” or contoured on to medical scans, to ensure the radiation targets the cancer while minimising damage to healthy tissues and organs. Normally, this is a slow, manual process that can take doctors between 20 and 150 minutes to complete. AI auto-contouring takes less than five minutes and costs around £10-£15 per patient. Research shows that AI contouring can cut waits for radiotherapy by more than five days for breast cancer patients, up to nine days for prostate cancer patients and three days for lung cancer patients. In May 2024, the Conservative government announced £15.5m over three years to fund AI auto-contouring for all hospitals providing radiotherapy. Work continued on the scheme after the general election, with online webinars and follow-up calls for radiotherapy departments held in September. The 51 trusts offering radiotherapy continued to work on installing the cloud-based technology, with a number using it early, in the belief the funding was secured. But in February, in an email seen by the Guardian, Nicola McCulloch, the deputy director of specialised commissioning at NHS England, said the funding had been cancelled “due to a need to further prioritise limited investment”. There would no longer be a centrally funded programme to support implementation of the technology, she said. The decision means many radiotherapy departments face a return to manual contouring, prompting accusations that the government is ditching digital and going back to analogue cancer care. Analysis by Radiotherapy UK has calculated that removing funding for AI contouring in England will add up to 500,000 extra days to waiting lists for breast, prostate and lung cancer alone and leave each of the 51 trusts with a £300,000 shortfall. The chair of Radiotherapy UK, Prof Pat Price, said: “The government cannot laud the advent of AI in one breath, and allow this to happen. Far from moving from an analogue to digital NHS, when it comes to radiotherapy it feels like the opposite is happening. This wrong-footed decision will exacerbate the impact of severe staff shortages.” The leading oncologist urged ministers to intervene. “Some departments are so short-handed that they’re shutting machines down because no one is there to operate them and nationally, radiotherapy vacancy rates are running at 8%. This investment in AI could have alleviated some of these pressures. Without it, cancer patients will wait longer than necessary for treatment, potentially costing their lives.” Read full story Source: The Guardian, 31 March 2025 -
Content Article
NHS waiting lists are growing, staff are overburdened and patients are often stuck in the wrong queues. But there is a chance to change this by improving outdated patient navigation systems. Every year, 29 million GP appointments could be freed up if patients were directed to the right care from the start. This report from the Tony Blair Institute for Global Change explores how an AI Navigation Assistant could transform the NHS by guiding people to the right care, the first time, alleviating pressure on NHS staff and improving patient outcomes. Companies are already using AI to streamline patient pathways. If the government doesn’t take this opportunity, outdated systems will continue to fail patients.- Posted
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Failed CQC transformation cost £99m
Patient Safety Learning posted a news article in News
The Care Quality Commission spent £99m on a transformation programme that failed to achieve most of the promised benefits, a highly critical independent report has revealed. In 2021, the regulator launched its transformation programme under the oversight of former chief executive Ian Trenholm, which it said would simplify the assessment process for health and social care providers. It entailed major changes to the organisation and operations of the CQC’s inspection regime, but also the introduction of new IT, including a “regulatory platform and provider portal”. An independent review by IT expert Peter Gill and published after a CQC board meeting yesterday found the transformation programme was to blame for widespread IT failures that have caused “significant organisational disruption”. “The vast majority of the benefits expected to be delivered have not yet been achieved,” it said. Read full story (paywalled) Source: HSJ, 27 March 2025- Posted
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