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Content ArticleThe Health Economics Unit (HEU) has developed A framework for the ethical and effective decommissioning and disinvestment in clinical services, in partnership with the HFMA. The framework is designed to support health and care leaders to systematically evaluate, prioritise and implement decommissioning and disinvestment decisions, particularly in systems facing significant financial deficit. In producing the framework, the HEU explored the following questions: Reasoning: How are services or providers identified for decommissioning, consolidation or other significant change? Process: What constitutes best practice in decommissioning, consolidation, service redesign and the reallocation of funds? Challenges: What gaps and limitations have been identified that affect or constrain the decommissioning process and associated decision-making. Decommissioning framework - accompanying guide.pdf
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Content ArticleWhile a growing body of evidence suggests that healthcare workers in low and middle-income countries often provide poor quality of care, the reasons behind such low performance remain unclear. The literature on medical decision-making suggests that cognitive biases, or failures related to the way healthcare providers think, explain many diagnostic errors. This study investigates whether one cognitive bias, overconfidence, defined as the tendency to overestimate one's performance relative to others, is associated with the low quality of care provided in Senegal. It links survey data on the overconfidence of health workers to objective measures of the quality of care they provide to standardised patients – enumerators who pose as real patients and record details of the consultation. We find that about a third of providers are overconfident – meaning that they overestimate their own abilities relative to their peers. It shows that overconfident providers are 26% less likely to manage patients correctly and exert less effort in clinical practice. These results suggest that the low levels of quality of care observed in some settings could be partly explained by the cognitive biases of providers, such as overconfidence. Policies that encourage adequate supervision and feedback to healthcare workers might reduce such failures in clinical decision-making.
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Content ArticleThis report shares learning gained through examination of a regional care pathway – that is, a pathway of assessment and care for patients with a particular health condition – during a Health Services Safety Investigations Body (HSSIB) rapid response investigation pilot. The investigation aimed to investigate safety concerns shared with HSSIB about the safety and effectiveness of a care pathway that spanned multiple organisations and where specialist services were centralised to a single site. The pathway had been redesigned with engagement from the organisations, the public and staff to reduce inequalities. It was intended to improve patient outcomes and ensure efficient use of resources across the region. The investigation provided insights into how the governance of care pathways, including oversight and risk management, is achieved, and how cultural and communication challenges between organisations impacted on patients receiving appropriate care. The investigation identified differences between how the redesigned pathway was expected to operate and how it worked in practice. These differences affected staff wellbeing and led to concerns about risks to patient safety, including delays in access to specialist care. The learning in this report is shared to support organisations and integrated care boards (ICBs) to adopt effective change management processes that are informed by patient safety considerations when designing, implementing and overseeing care pathways. Findings A cross-organisation implementation board oversaw the redesign and initial implementation of the care pathway. Support and oversight from the ICB was time limited, ending before the project had been fully implemented, which impacted on the operationalisation of the service. A business case for implementation of the pathway was approved but not fully realised. This created expectations for how the pathway would operate that were not met in practice. There was no shared view across organisations about what the redesigned pathway could offer patients in reality. This limited the organisations’ ability to understand the risks across the pathway and to mitigate them to as low as reasonably practicable. There was no single guidance document shared between organisations, and there were inconsistencies in the documentation used to support decision making about whether patients should be provided with specialist care. Organisations held different perceptions of the risks to patient safety created by the redesign of the pathway. This impacted on clinical decision making and led to disagreements between teams. Organisational oversight of the pathway after its implementation was limited due to disengagement among staff and the absence of a collaboratively agreed evaluation plan. The data collected about the care pathway differed across organisations and was not routinely shared between them. This led to a difference in understanding about how the care pathway was working in practice and where improvements could be made. The ICB had limited ability to support ongoing improvement of the care pathway and had limited access to information about the quality and safety of the pathway in practice. Differences in the perceived purpose of the pathway led to barriers to collaborative learning and improvement of the pathway. These included examples of incivility among staff, which is known to impact on staff wellbeing and patient outcomes. HSSIB suggests safety learning for integrated care boards Safety learning for integrated care boards ICB/2026/019: HSSIB suggests that integrated care boards proactively identify the impact of commissioning decisions on pathways prior to implementation and develop mitigations to reduce any potential impacts on patient safety and equitable access to care. Safety learning for integrated care boards ICB/2026/020: HSSIB suggests that integrated care boards support organisations to effectively evaluate the implementation of new care pathways. Local-level learning prompts HSSIB investigations include local-level learning where this may help organisations and staff identify and think about how to respond to specific patient safety concerns at the local level. HSSIB has developed the following prompts to support local-level learning for NHS trusts when collaborating with other organisations across a regional care pathway. Safe implementation of the care pathway How do you identify and resource dedicated support to implement new care pathways? How do you ensure appropriate tools and resources are used to support the design and implementation of the care pathway? How do you identify and mitigate unexpected challenges to patient safety arising from the care pathway’s implementation? How do you identify and mitigate any mismatch between the expectations of patients, families, carers or staff and what the pathway can deliver in practice? How do you ensure that implementation of a care pathway is effectively evaluated to improve safety and learning? How do you identify and mitigate potential harm caused when implementing a new care pathway? The care pathway in practice How do you identify and manage incivility between staff across different organisations? How do you facilitate shared learning opportunities for staff across different organisations? How do you ensure information and documentation used to support the care pathway are aligned across different organisations? How do you enable staff to understand the context in which the care pathway may work in different organisations? How do you engage staff to understand the different requirements for electronic systems that may exist across the care pathway? How do you support interoperability of electronic systems to enable effective information sharing across different organisations? How do you enable new technology to be adopted and used across different organisations? How do you consider relevant tools and guidance when developing work processes across different organisations? Oversight of the care pathway How do you ensure shared governance forums are appropriately established and resourced, and are effective? How do you ensure concerns about the care pathway are escalated and acted on by senior and executive leadership teams across different organisations and the integrated care board? How do you ensure consistency in how data is collected and shared across different organisations, including with integrated care boards? How do you ensure that risks to the care pathway are identified and mitigated to as low as reasonably practicable across different organisations? How do you ensure messages about the care pathway are effectively shared and understood by staff across different organisations? How do you identify and facilitate proactive communication with a point of contact at the integrated care board with oversight of the care pathway?
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EventWhat does good consent look like in practice, and what are the patient safety consequences when patients are not truly informed? Join Radar Healthcare's webinar, Digital consent: How to deliver safer outcomes by bringing consent, risk and insight together, to explore the vital link between patient education, informed decision-making and safer care. Featuring perspectives from the Patients Association, Patient Information Forum, legal experts and frontline clinicians, this CPD-certified session will examine how organisations can strengthen consent processes, reduce risk and improve patient outcomes through better communication, education and insight. Register
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EventuntilThis 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
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EventAimed at Clinicians and Managers, this national virtual conference will provide a practical guide to human factors in healthcare, and how a human factors approach can improve patient care, quality, process, and safety. The conference delves into integrating human factors into healthcare systems and processes, clinical decision making, healthcare system design, quality of patient experience, medication safety, and workload, fatigue, and stress management. Throughout the day there will be interactive sessions, small breakout groups, and collaborative exercises, fostering a dynamic learning experience. This conference will enable you to: Network with colleagues who are working to embed a human factors approach. Learn from outstanding practice in using human factors and ergonomics to improve patient safety and quality. Reflect on national developments and learning including the patient safety syllabus and the role of human factors within the new Patient Safety Incident Response Framework (PSIRF). Understand the tools and methodology. Develop your skills in training and educating frontline staff in human factors. Understand how you can improve patient safety incident investigation by using a human factors approach. Learn from case studies demonstrating the practical application of human factors to improve patient care and safety. Understand the role of human factors in improving culture and delivering psychological safety. Self assess and reflect on your own practice. Supports CPD professional development and acts as revalidation evidence. This course provides 5 Hrs training for CPD subject to peer group approval for revalidation purposes. Register We are pleased to offer hub members a free place using the code HCUK00HFPSL
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Content ArticleThis Health Services Safety Investigation Body (HSSIB) report examines patient safety in relation to electronic prescribing and medicines administration (ePMA). ePMA is software used to prescribe medication and create a record of the medication: that has been given, or due and not given to a patient. Most people admitted to hospital will receive medication, and most acute hospital trusts in England have ePMA functionality in at least part of their organisations. This report focuses on the procurement process used by acute hospital trusts to purchase new ePMA functionality and/or upgrade their existing ePMA functionality and how patient safety learning about ePMA is identified and shared across the healthcare system. It considers how legal, regulatory, standards and assurance functions apply in relation to ePMA safety. ePMA functionality has been shown to reduce some medication errors. However, the current national mechanisms (legislation, regulation, standards and assurance) for ensuring patient safety in relation to ePMA functionality may not adequately provide staff and healthcare organisations with the assurance that risk and hazard identification process are robust and/or share learning associated with the use of ePMA in an acute hospital setting. Findings There are no core national patient safety standards that inform either the design or procurement of ePMA. This can lead to unwarranted variation in functionality across and between ePMA, other electronic systems, and acute hospital trusts, which may pose challenges for staff when prescribing and administering medication. Current assurance mechanisms do not provide national oversight or enforcement of either manufacturer or healthcare provider compliance with legally mandated standards relating to digital clinical safety and interoperability of digital health technology. The safety risks associated with software such as ePMA are complex and may change rapidly. Legislation, regulation and standards may not keep up with the speed of technological change. Manufacturers must self-assess and report whether their ePMA is compliant with relevant standards for their products to be included on an NHS procurement framework. There is variation in the core safety standards identified by acute hospital trusts when procuring and contracting for ePMA functionality. This leads to trusts identifying safety requirements individually, with limited consistency in the approach taken across trusts. Reliance is placed on acute hospital trusts to determine whether ePMA manufacturers have interpreted the medical device regulations appropriately, and to assure themselves that the trust complies with relevant standards. Some trusts do not have the resources, skills and expertise to do this effectively. Digital safety and patient safety teams at local and national level may work in silos, with limited ability to share information or collaborate on ePMA-related decisions that impact on patient safety. There are challenges with identifying national safety learning relating to ePMA as this is not reliably captured, shared or identified through formal reporting routes. There is ongoing work to improve the NHS reporting system to capture digital-related patient safety incidents. There is a reliance on informal networks for sharing ePMA safety issues which means safety concerns may not always be shared with those who need to be aware. Some ePMA manufacturers, whose ePMA functionality is not registered as a medical device choose to apply equivalent governance and assurance measures as if it is a medical device. This is in addition to complying with the digital clinical safety standard (DCB0129). Acute hospital trusts face challenges prioritising and resourcing procurement decisions for ePMA functionality. This leads to challenges and patient safety issues when ePMA is implemented. Clinical safety officers (CSOs) may not be adequately resourced, meaning they have limited capacity to support in managing clinical risks associated with ePMA. There is variation in how the CSO responsibilities set out in the digital clinical standards are interpreted and implemented by trusts. NHS England is working on plans for a formal curriculum and potential accreditation to improve CSO skills and capabilities. HSSIB makes the following safety recommendations Safety recommendation R/2026/086: HSSIB recommends that the Medicines and Healthcare products Regulatory Agency ensures that: routes for manufacturers and healthcare organisations to engage with them are clear and accessible it reviews and provides further guidance and clarification on when electronic prescribing and medicines administration (ePMA) software should be considered a medical device. This will support how ePMA software can be appropriately classified and regulated to improve patient safety. Safety recommendation R/2026/087: HSSIB recommends that NHS England/Department of Health and Social Care establishes a national framework for core electronic prescribing and medicines administration (ePMA) safety. This will provide a clear set of minimum patient safety requirements, helping to reduce unwarranted variation in the safety of ePMA functionality. Safety recommendation R/2026/088: HSSIB recommends that NHS England/Department of Health and Social Care develops an external assurance framework for information standards notices relating to electronic prescribing and medicines administration (ePMA). This is to reduce unwarranted variation and improve patient safety through expert-led assurance processes. Safety recommendation R/2026/089: HSSIB recommends that NHS England/Department of Health and Social Care provides additional support to acute hospital trusts, in relation to: supporting healthcare providers to access digital clinical safety knowledge, capacity and capability integrating digital clinical safety and patient safety, including the associated terminology supporting robust assurance of whether electronic prescribing and medicines administration (ePMA) manufacturers comply with relevant standards in order to be considered for inclusion on an NHS procurement framework. This will support effective decision making and oversight by acute hospital trusts and reduce unwarranted variation in the understanding of, and approach to, adopting ePMA. Safety recommendation R/2026/090: HSSIB recommends that the Care Quality Commission reviews the sector-level assessment frameworks it is developing to include assurance of ongoing compliance with the digital clinical safety standard (DCB0160) for electronic prescribing and medicines administration (ePMA) software. This will help to ensure oversight of ePMA functionality to improve patient safety. HSSIB makes the following safety observations Safety observation O/2026/086: Commercial manufacturers can improve patient safety by applying the standards and expectations for a medical device when developing electronic prescribing and medicines administration (ePMA) functionality, to help provide further assurance to acute hospital trusts procuring or updating ePMA functionality. Safety observation O/2026/087: Commercial manufacturers and NHS organisations can improve patient safety by ensuring the sharing of safety learning about electronic prescribing and medicines administration (ePMA) functionality nationally via incident reporting systems and relevant safety forums. Safety observation O/2026/088: Commercial manufacturers and NHS organisations can improve patient safety by contributing to and engaging with ePRaSE (ePrescribing Risk and Safety Evaluation) processes to support ongoing improvement and optimisation of electronic prescribing and medicines administration (ePMA) functionality across the NHS.
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Content ArticleEvery day, millions of Americans use artificial intelligence tools like ChatGPT and others to ask medical questions. Physicians also use AI: Two in three U.S. doctors report using large language models regularly in some form, and roughly one in five consult AI for questions on patient care. Yet critical questions have remained largely unanswered: What’s the best AI for medical questions, and how badly can AI get things wrong? New research by a team from Stanford, Harvard and several other institutions published under the fitting name Numerous Options Harm Assessment for Risk in Medicine, or NOHARM, offers the most rigorous answer yet.
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Content Article
Last month, Public Policy Projects hosted their annual Patient Safety Forum in partnership with Patient Safety Learning. Held at the Royal College of Surgeons of England in London, it was attended by senior healthcare leaders, patient safety experts, representatives from the HealthTech industry, frontline healthcare professionals and patients. In this article, Patient Safety Learning reflects on one of the panel discussions—AI for patient safety: Innovation, assurance and strengthening communication. From AI-enabled ambient scribing tools that reduce the burden of administration, to predictive systems capable of detecting early warning signs before harm occurs, AI has significant potential to improve patient care and outcomes. Yet, alongside these benefits come risks—algorithmic errors, data bias, and challenges in maintaining trust, governance and oversight. At the Patient Safety Forum 2026 an expert panel was convened to discuss this topic, with the following members: Clive Flashman, Chief Digital Officer, Patient Safety Learning Dr Alison Cave, Chief Safety Officer, Medicines and Healthcare products Regulatory Agency (MHRA) Anil Mistry, AI Safety Lead, Guy’s and St Thomas’ NHS Foundation Trust Dr Basil Bekdash, Clinical Safety Officer, Sheffield Children’s NHS Foundation Trust Aleksander Alski, Head of Region – USA, Canada and UK, Vasco Electronics Panellists had a lively discussion with each other and the audience about how to balance innovation with assurance, to ensure that the use of AI in healthcare enhances safety rather than undermines it. They spoke about how AI should be understood as a support tool for healthcare professionals—it provides information and removes burden but, ultimately, staff treat patients. In this blog we highlight several key topics that emerged from this debate. Importance of patient safety A key theme running throughout the panel’s discussion was the importance of patient safety being built into AI development at the outset. Clive Flashman from Patient Safety Learning reflected on this point, suggesting that too often this is seen as a compliance ‘tick box’ or treated as an afterthought. Speaking to digital innovators, his message was that “you need to think about this from the very start when you are conceptualising the product”. Panellists also recognised that putting safety at the centre of discussions around AI and healthcare means involving all stakeholders, not just the healthcare professionals using these technologies but suppliers too. Alexander Alski from Vasco Electronics emphasised the importance of this being an area of shared responsibility between suppliers and healthcare providers. Getting regulation right Alison Cave from the MHRA spoke about the ongoing work of the National Commission into the Regulation of AI. This Commission was established by the MHRA to review current regulations and provide recommendations for a new regulatory framework for AI in healthcare. It held a public call for evidence which Patient Safety Learning responded to earlier this year. Discussing how to approach future regulation, she highlighted the importance of ensuring that “the risk is associated with the decision, not the technology itself”. It was noted that in some cases there may be very complex pieces of software in use, but these may be making very low-risk decisions. Panellists underlined the importance of having a risk-proportionate regulatory framework to support safe innovation. Predicting future harm The potential to use AI to identify patient safety issues is understandably an area of significant interest. Last year the Department of Health and Social Care announced that it planned to develop a world-first artificial intelligence (AI) early warning system to automatically identify safety concerns across the NHS. Panellists were asked to consider what examples they had seen of AI moving from reacting to incidents, to predicting and preventing future harm. They spoke about the value of AI as a support tool for clinicians and more broadly how it might be used to identify emerging patient safety issues. Basil Bekdash from Sheffield Children’s NHS Foundation Trust spoke about work that had been trialled in this area, but noted that currently there have not been many examples where these have been proven on a significant scale, stating: “None of them have really quite got to the point where they're proven in widespread deployment and so I'm not going to predict that's going to happen in the next five years.” Tackling bias While an AI tool may be safe when properly implemented and used by a well-trained healthcare professional, it could be potentially dangerous if such training and support is absent. Panellists concurred that having appropriate training and tackling bias were issues of critical importance in ensuring the safety of AI in healthcare. In particularly they discussed risks presented by: Confirmation bias—healthcare professionals favouring AI outputs that align with their pre-existing view and overlooking signals that may challenge this. Automation bias—over-reliance on AI systems and accepting their recommendations without sufficient critical evaluation. Alison Cave from the MHRA said that part of the training should be ensuring that healthcare professionals understand the devices they are using and where there are trade-offs between sensitivity and a specificity. Basil Bekdash from Sheffield Children’s NHS Foundation Trust noted the importance of having in mind the different levels of digital competence of staff, stating that when designing AI systems: “It is best to test by using your least capable people who are the least digitally enabled and that's not a criticism that's just the reality of the normal spread of what people do, and their primary function is to look after patients.” Transparency and patient communication As use of AI grows in healthcare, it is vital that patients understand how this is being applied if they are to have confidence in its safety. Panellists discussed issues around how to inform patients when AI influences their care, particularly when it affects clinical judgments. Anil Mistry from Guy’s and St Thomas’ NHS Foundation Trust suggested that: “If the AI result is going to affect their patient’s care, and it's going to limit their access to finite resources like a waiting list or appointments or ICU beds, then absolutely have that sort of communication.” However, he also spoke about some of the challenges this raises; for example, if a patient asked about whether AI has been used in their care. In practice this could cover a very broad range of areas, from the use of ambient scribes to take notes to tools that analyse images from scans. Panellists indicated that transparency needed to be balanced and proportionate to both the risk and impact on individual care. Governance requirements AI healthcare technologies have significant scope to evolve and change over time. When they iterate rapidly (with new versions being released at regular intervals) it can be difficult for existing governance frameworks, designed for other types of medical devices, to keep up. Panellists discussed the importance of having flexibility to governance arrangements. There was the suggestion that lower risks tools (such as those in Class 1 for Medical Devices under the MHRA framework in the UK) should have greater flexibility, with higher levels of scrutiny reserved for decision-influencing tools. It was also made clear that any new regulation will need to carefully consider the level of ongoing evaluation that will be required to account for these systems evolving and changing over time. This may be much longer than for other medical devices and change at significant pace. One audience member commented that with these tools becoming increasingly complex, in the future “realistically there is going to be a need for an AI tool that assesses AI tools”. Panellists also considered how procurement processes could act as potential leverage mechanisms for AI technologies in healthcare. It was noted they offer the potential opportunity to embed the open standards we want to see being used by AI technologies in the earliest stages of their design, putting safety concerns at the centre of the product before it ever reaches patients. Improving the quality of data Data accuracy, completeness and representativeness is key to ensuring AI technologies work safely in health and care environments. Panellists noted that poor foundational data standards undermine AI model training and lead to unreliable outputs. Their discussion reflected that a significant proportion of time is often spent on data cleaning before even applying AI. Improving this would have wider benefits for research, operational efficiency and public healthcare. As we increase the use of AI health technologies, it is vital that we do not embed existing health inequalities. Following on from comments in an earlier session from Professor Bola Owolabi from the Care Quality Commission, Alison Cave from the MHRA noted a “perennial challenge in all of our areas is to ensure that the training data is representative”. Training data for AI systems must be representative of diverse populations and care settings. Sharing insights from the frontline If healthcare organisations, professionals and suppliers are to share responsibility for the safe implementation of AI technologies in healthcare, this must go hand in hand with shared learning. Panellists discussed the need for sustained and transparent feedback loops between suppliers, regulators and healthcare organisations. On this point an audience member asked: “How do we ensure our learning keeps pace so that existing insight from frontline teams that really know the business can optimally inform the evolution of products, but without stifling the pace?” Panellists highlighted the absence of standardised mechanisms for frontline staff to provide real-time, structured feedback to AI suppliers on safety issues. One proposed suggestion to this was the potential to mandate native feedback functionality within AI health technologies. This would mean that feedback mechanisms are built directly into the AI tool’s user interface and workflow, allowing those using them to provide input about the AI’s output without leaving the system. Find out more about the Patient Safety Forum 2026 You can read more about different discussions and panel sessions at this year’s event in the below: Patient voice, safety and the NHS 10 Year Plan: Reflections from the Patient Safety Forum 2026 Safe systems, safe cultures: reflections from the Patient Safety Forum 2026 -
Content ArticleThis briefing from Arthritis UK finds that almost a fifth (19%) of integrated care boards (ICBs) in England are rationing joint replacement surgery by disadvantaging patients with a higher body mass index (BMI). A further 54.7% have policies that restrict or alter access to surgery in some other way for those with overweight or obesity. Not only are these policies unfair, but they also contradict National Institute for Health and Care Excellence (NICE) guidelines and government policy. Arthritis UK is calling for all ICBs to stop using these policies and stop rationing surgery based on a person’s BMI.
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News ArticleNearly one in five NHS organisations are "rationing" crucial joint replacement surgeries based on patients' weight, a new report has claimed. Arthritis UK has warned that this practice is creating a "postcode lottery" of care across the country, leaving individuals in urgent need of operations at risk of enduring prolonged pain. The charity also expressed concerns that these policies are being implemented "in a bid to cut waiting lists and costs". An analysis conducted by Arthritis UK found that 31 out of 42 NHS integrated care boards (ICBs) currently have policies linking body mass index (BMI) to hip and knee replacements. Specifically, eight ICBs, representing 19% of the total, are "rationing" procedures by setting defined BMI thresholds as a criterion for surgical referral. A further 23 have policies that encourage or mandate weight loss to become eligible for these operations, the report said. According to Arthritis UK, ICBs justify the use of BMI policies by highlighting risks. However, it said research only shows a significant risk for people with a very high BMI, and these policies have “been inappropriately used” to cut off patients with lower BMIs, such as 35. This move has affected thousands of people “who would have received the significant improvements in their joint pain and function,” the charity said. The National Institute for Health and Care Excellence (Nice) advises against using BMI to exclude patients from referral to surgery. Read full story Source: The Independent, 26 March 2026
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EventThis innovative educational initiative was developed as a direct and constructive response to the communication inadequacies exposed by the Montgomery case, and subsequent legislation. While it is not difficult to give "more information" it is harder for surgeons and patients to achieve a decision partnership. The ICONS workshop content has been informed by internationally recognised experts in Shared Decision Making, by consensus among senior practising surgeons, by patients and by professional experts in risk management and risk communication. Delegates on the ICONS workshops will acquire skills and knowledge to implement best practice in sharing the complex decisions surrounding informed consent. By participating in a workshop, they will also contribute to the development of resources for future training in the important area of informed consent. Target audience All grades of trainees; SAS / LED / Trust Doctors; Consultants. Non FRCS surgeons – Ophthalmologists; Obstetricians and Gynaecologists. Learning style Focussed topic introductory talks. Small group facilitated discussion tutorials based on review of exemplar videos of consent and other patient doctor communication scenarios. Aims & objectives The objectives of the course include: Learn the potential catastrophic and costly consequences of failure adequately to share important surgical decisions. Recognise the importance of discussion treatment options rather than risks. Understand key features of the case Montgomery v LHB 2015. Appreciate the legal view of Shared Decision Making. Identify key elements of a Shared Decision Making consultation. Understand how to deliver treatment recommendations. Gain new consultation skills. Identify and apply effective ways of risk communication. Appreciate the role of decision support tools before, during and after the clinical encounter. Understand the added value of writing letters directly to patients. Learning outcomes Having attended the ICONS workshop you will be able to: Understand the practical importance of the Montgomery decision. Identify the key elements of a Shared Decision Making consultation. Discuss options including surgery – elective and emergency. Employ efficient methods of eliciting patient needs, preferences and values in a busy clinic. Understand the added value of patient activation before options are discussed, and decision distribution thereafter. Develop skills for well-balanced, meaningful surgeon patient interactions. Communicate risk to patients in a more realistic way. Appreciate the role of recommendation. Review the limitations of and variation in current consent forms. Register
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Content ArticleThe Covid-19 Inquiry published its second report and recommendations following its investigation into the ‘Core decision-making and political governance’ on Thursday 20 November 2025. It looked into core political and administrative governance and decision-making. It includes initial response, central government decision making, political and civil service performance as well as the effectiveness of relationships with governments in the devolved administrations and local and voluntary sectors. Recommendations include: Broadening participation in SAGE (the Scientific Advisory Group for Emergencies), through open recruitment of experts and representation of devolved administrations. Reforming and clarifying the structures for decision-making during emergencies within each nation. Improving consideration of the impact that decisions might have on those most at risk in an emergency: changes should aim to identify any risks to vulnerable groups, in both the planning for and response to emergencies. Ensuring that decisions and their implications are clearly communicated to the public. Laws and guidance should be easily understood and available in accessible formats. Enabling greater parliamentary scrutiny of the use of emergency powers through safeguards such as time limits and regular reporting on how powers have been used. Establishing structures to improve the communication between the four nations during an emergency to ensure better alignment of policies where desirable and to provide a clear rationale for differences in approach where necessary. See also: UK Covid-19 Inquiry Module 1: The resilience and preparedness of the United Kingdom Covid-19 Inquiry: Module 3 Report – The impact of the Covid-19 pandemic on the healthcare systems of the United Kingdom Questions around Government governance
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News Article
Do not impose personal views or beliefs on patients, doctors told
Patient Safety Learning posted a news article in News
Doctors have been issued new guidance stipulating they must not impose their personal views, beliefs, or values on others. The General Medical Council (GMC) has published the draft rules, currently open for consultation, which apply to all doctors, physician associates, and anaesthesia associates across the UK. The guidance explicitly states that medics should not treat colleagues poorly based on assumptions about their beliefs or due to disagreements with their views. It also makes clear that personal beliefs or values must not be imposed on patients. The doctors’ regulator clarified that these directives relate specifically to professional practice and do not cover healthcare workers expressing their beliefs or values outside of the workplace. This updated draft guidance follows a series of incidents involving healthcare professionals, both within and outside their professional duties. The regulator is seeking views on draft updates to its “personal beliefs and medical practice guidance”, which also includes information about conscientious objections to providing certain treatment or procedures – which could include abortions. The guidance states patients must be prioritised and that such an objection must not prevent a patient from being able to access the care or service they need. Read full story Source: The Independent, 19 March 2026 -
Content ArticleLarge-scale programmes are a major feature of health systems worldwide, and the origins of problems often lie in the very early stages of their design and planning. They can play a valuable role in driving improvement and innovation, helping to decrease unnecessary variation, inequities and waste. But, as with other sectors, large-scale programmes in healthcare can produce mixed results and can face common challenges. To support better practice, THIS Institute has collaborated with Ipsos and The Health Foundation to develop a framework for designing large-scale complex change programmes in health and care – major initiatives run by national organisations aimed at securing improvement or service change. This framework is designed to guide early-stage planning (“the front end”) of large-scale change programmes in health and healthcare. It helps programme teams think rigorously and systematically before major decisions are made, with the aim of reducing avoidable failure and improving chances of success. It draws on evidence from the literature on large projects across multiple sectors, national guidance and reports, interviews with experienced programme leaders, and stakeholder testing with real policy teams.
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Content ArticleClinical practices guidelines (CPGs) play a fundamental role in improving healthcare and patients’ outcomes by helping clinicians make the best evidence-based decisions for their patients in a time-efficient manner. By following the available methods and criteria to create trustworthy CPGs, panel members can develop high-quality guidelines. However, despite the improvements over the years, CPGs are still subjected to biases and limitations, with conflicts of interest being the ugliest problem GCPs must face. This review discusses the main characteristics of clinical practice guidelines, their pros and cons, and the future challenges they need to overcome.
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Content ArticleWith financial constraints, record waiting lists and recent staff strikes, the role of being an NHS chief executive has arguably never been harder. But what impact is it having on those health service leaders? In recent months, Thea Stein has spoken to a number of NHS chief executives about the difficult choices they confront in their everyday work and the moral distress that may accompany those decisions. In this long read, Thea reveals what was said to her, and emphasises once more the importance of making the NHS a psychologically safe place to work.
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News Article
Using AI for medical advice 'dangerous', study finds
Patient Safety Learning posted a news article in News
Using artificial intelligence (AI) chatbots to help seek medical advice can be "dangerous", a new study has found. The research found that using AI to make medical decisions presented risks to patients, external, due to its "tendency to provide inaccurate and inconsistent information". It was led by researchers from the Oxford Internet Institute and the Nuffield Department of Primary Care Health Sciences at the University of Oxford, and published in the scientific journal Nature Medicine. Dr Rebecca Payne, who co-authored the study, said it found that "despite all the hype, AI just isn't ready to take on the role of the physician". "Patients need to be aware that asking a large language model about their symptoms can be dangerous, giving wrong diagnoses and failing to recognise when urgent help is needed," Dr Payne, who is also a GP, added. "These findings highlight the difficulty of building AI systems that can genuinely support people in sensitive, high-stakes areas like health," Dr Payne said. Read full story Source: BBC News, 10 February 2026 -
Content ArticleGlobal healthcare providers are exploring the use of large language models (LLMs) to provide medical advice to the public. LLMs now achieve nearly perfect scores on medical licensing exams, but this does not necessarily translate to accurate performance in real-world settings. The authors of this study, published in Nature, tested whether LLMs can assist members of the public in identifying underlying conditions and choosing a course of action (disposition) in ten medical scenarios in a controlled study with 1,298 participants. Participants were randomly assigned to receive assistance from an LLM or a source of their choice (control). T Tested alone, LLMs complete the scenarios accurately, correctly identifying conditions in 94.9% of cases and disposition in 56.3% on average. However, participants using the same LLMs identified relevant conditions in fewer than 34.5% of cases and disposition in fewer than 44.2%, both no better than the control group. The authors identify user interactions as a challenge to the deployment of LLMs for medical advice. Standard benchmarks for medical knowledge and simulated patient interactions do not predict the failures we find with human participants. Moving forward, they recommend systematic human user testing to evaluate interactive capabilities before public deployments in healthcare.
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Content ArticleThe barrage of misinformation in the field of healthcare is persistent and growing. The advent of artificial intelligence (AI) and large language models (LLMs) in healthcare has expedited the increase in misinformation, and LLMs are susceptible to false output if they are trained on incorrect healthcare information. This risk of misinformation is especially true for LLMs trained on vast datasets of information originating from online sources and can be particularly difficult to navigate when developers do not disclose the databases used to train such tools. Incorrect medical advice generated from LLMs have serious consequences for patients. How can we quantify and ultimately reduce the misinformation caused by LLMs to ensure better patient health outcomes?
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Content ArticleMultidisciplinary team (MDT) meetings have been endorsed by the Department of Health as the core model for managing chronic diseases. The proliferation of MDT meetings in health care has occurred against a background of increasingly specialised medical practice, more complex medical knowledge, continuing clinical uncertainty and the promotion of the patient’s role in their own care. In this environment, it is believed that MDT meetings ensure higher-quality decision-making and improved outcomes. However, the evidence underpinning the development of MDT meetings is not strong and the degree to which they have been absorbed into clinical practice varies widely across conditions and settings. In the light of this uncertainty, there have been calls for empirical research on MDT meeting decision-making in routine practice to understand how and under what conditions MDT meetings produce effective decisions. This large mixed-methods study of MDTs for a range of chronic diseases examines and explores determinants of effective decision-making (defined as decision implementation) and areas of diversity across MDT meetings. The authors of the study applied a transparent and explicit consensus development method to develop a list of indications of good practice, based on their results, to improve MDT meeting effectiveness.
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News Article
Millions offered no choice of provider
Patient_Safety_Learning posted a news article in News
Millions of patients are being offered no choice of provider when referred for secondary care and tests, contrary to national guidance, according to NHS England information. By law, patients are allowed to choose their provider when referred for a first appointment for consultant-led treatment. The NHS e-Referral Service is the NHS’s national digital system for booking and managing elective appointments and is used in primary care consultations to book appointments; as well as directly by patients via the “manage your referral” website or the NHS App. It was introduced in an effort to make referrals faster and more transparent, and it was claimed it would also lead to patients being offered more choice. Read full story Source: HSJ 9 December 2025 -
Content ArticleIn this interview, Dana Edelson, an expert in cardiac resuscitation at the University of Chicago, discusses how hospitals can best use early warning score tools to risk stratify patients—without adding to clinicians’ alarm fatigue. Dana recently co-authored a study which compared six different early warning scores designed to recognise clinical deterioration in hospitalised patients, including three proprietary AI tools.
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Content ArticleThis open access book explores epistemic justice in mental healthcare, bringing together perspectives from psychologists, psychiatrists, philosophers, activists and lived experience researchers. Through eight chapters, authors identify threats to the agency of people who hear voices, experience depression, have psychotic symptoms, live with dementia, are diagnosed with personality disorders, and face serious mental health issues while receiving palliative care. Considering the power asymmetries in clinical interactions, where patients are vulnerable and healthcare professionals are uniquely placed to offer support, this book reaffirms the importance of recognizing patients as agents and collaborators. Topics covered include trust in the therapeutic relationship, dignity at the end of life, the social dimension of health, stigma in an acute ward, the harm caused by biases and stereotypes, the role of clinical communication and the promise of digital health.
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Content ArticleArtificial intelligence-based clinical decision support systems (AI-CDSS) hold promise for improving patient outcomes. This review identified 26 articles on the effectiveness of AI-CDSS on patient outcomes. The content analysis revealed four themes: early detection and disease diagnosis, enhanced decision-making, medication errors, and clinicians' perspectives. Only three of the interventions, which were within the theme of early detection and disease diagnosis, were categorized as highly effective. Patient privacy, data security, and health equity were mentioned as continuing concerns.
