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Stefan Peil summarises a pilot study he has done to see whether a structured systems model can support the preparation of a morbidity and mortality (M&M) conference discussion. The example used is a coronary angiography risk scenario to explore whether a model-based representation of patient safety knowledge could serve as a reliable basis for an artificial intelligence (AI)-assisted decision template. The work was produced to address a practical problem in patient safety: relevant information for M&M preparation is often spread across diagrams, reports and team knowledge, which can slow and make shared understanding less consistent. The pilot study, therefore, examined whether systems modelling could help organise, make transparent and reuse safety relevant information in a more structured way. The full study is attached at the end of this page. The challenge The identified challenge was the lack of a structured, reusable approach to preparing patient safety discussions for M&M conferences. The aim was not to automate clinical judgement, but to test whether a model-based risk analysis derived from team knowledge could serve as a structured input for drafting an M&M decision template. M&M preparation often relies on fragmented information and informal interpretation. In complex clinical environments, such as coronary angiography, risks do not arise from a single isolated factor. They emerge from the interaction between tasks, people, technology, information flow and organisational conditions. In this specific pilot example, the safety concern was a risk scenario in coronary angiography in which cognitive overload during real-time decision-making and escalation could contribute to complications not being detected in time. This formed the basis for testing whether a structured model could provide a clearer and more traceable starting point for discussion. Method and measures To explore this, a systems model based on Systems Engineering Initiative for Patient Safety (SEIPS) 2.0 was created in Systems Modeling Language (SysML) using SPARX Enterprise Architect. The objective was to represent the work system, the contributory task factor, the resulting risk and the proposed measures in a traceable form. The model focused on one coronary angiography scenario. The critical task factor was described as cognitive density in real-time decision-making and potential escalation. In the model, this contributed to the risk that complications would not be detected in time. The text states an impact on quality of care, an occurrence rating described as relevant and an overall risk class of moderate. The proposed measures were: pre-procedure briefing risk-adapted staffing standardised laboratory layout regular simulation drills. The intended achievement was a more structured, transparent and reusable basis for M&M preparation and discussion. Outcomes and lessons learned The pilot showed that a structured model can be a useful way to organise safety-relevant knowledge. Because the model linked work system elements, risks and measures in a traceable way, it provided a clearer starting point for discussion than unstructured text alone. The practical process tested in this pilot was: defining a relevant patient safety scenario in coronary angiography modelling the work system and the contributory task factor linking this to a patient safety risk documenting possible mitigating measures using the model as the basis for an AI-assisted one-page decision template. One important observation was that the AI-generated output reflected the underlying model's content. This suggests that a structured model can support more consistent synthesis than relying only on memory or informal interpretation. The text does not describe multiple alternative technical approaches in detail, so it cannot be stated from the source whether other options were formally compared or ruled out. It also does not state direct patient involvement. Staff involvement is referenced indirectly by using team knowledge as an input to the model. The text does not report formal measurement tools, outcome metrics, time savings, patient safety indicators or model costs. Therefore, no validated impact measurement can be claimed from the source. A key lesson learnt was that AI can assist with drafting and synthesis, but cannot replace clinical judgement, governance or safety review. Any output generated from the model still needs to be checked against the source material and reviewed by responsible clinical and patient safety leads. Impact This work is only a prototype, not as a formal effectiveness study. As a result, the impact that can be claimed is limited. The main result was that the structured model appeared to support: clearer organisation of safety-relevant knowledge better traceability between work system factors, risks and proposed measures a more consistent starting point for multidisciplinary discussion reuse of modelled information for drafting a one-page M&M decision template. At the same time, the the study is explicit about what was not demonstrated. The pilot did not test whether the approach: improved patient outcomes reduced harm shortened preparation time in routine practice improved care delivery in a measurable way. A further limitation was that only a single, limited example was used, and some information was withheld for data protection reasons. This means the results were narrower than would be needed for broader implementation decisions. What worked was the structured linkage between the work system, contributory factors, risks and measures. What remains uncertain is whether this translates into measurable operational benefit in routine clinical governance. A likely barrier to improvement is the need for continued expert review, because AI-generated output cannot be used without clinical validation and governance oversight. If repeated, the next stage would need a clearer evaluation design, including defined measures of clarity, consistency, usability and possibly preparation time. Next steps The next step is a practical pilot in real clinical governance settings. A suitable next-stage comparison would be conventional M&M preparation versus model-supported preparation in a small, clearly defined pilot. The proposed questions for the next phase are: Does the approach improve clarity and shared understanding? Does it help teams identify contributory factors more systematically? Does it support consistency and traceability of measures related to patient safety? The study does not provide evidence of long-term organisational change, staff reaction, patient impact statistics or system-wide implementation results. Therefore, those elements cannot yet be stated as outcomes. However, based on insights from the pilot study, the anticipated longer-term value would be to make patient safety knowledge: more structured more reusable easier to discuss across professional groups more clearly linked to the wider work system rather than to isolated errors. A sensible next step would, therefore, be a controlled local test with defined governance, clinical review and evaluation criteria before any broader adoption.

Working across frontline emergency care, patient safety and digital patient safety over the course of my 22-year career in the NHS has given me a unique perspective on how digital systems shape real clinical practice. As a paramedic now working as a Clinical Safety Officer within NHS Wales, I’ve seen first‑hand how digital tools can support safer care—but also how they can contribute to patient harm when things don’t work as intended. In this blog, I reflect on the challenges of identifying issues and, more importantly, assessing patient harm in a digital context. These thoughts aren’t theoretical, they come from day‑to‑day reality: the calls, the investigations, the conversations and the moments where something in the digital healthcare system doesn’t work the way it should—and a patient feels the impact. I’m sharing these thoughts to stimulate conversation, hopefully build shared understanding and help strengthen our collective approach to digital patient safety across the UK. The growing complexity of digital healthcare Digital healthcare has evolved rapidly, and with that evolution comes complexity. Electronic health records, diagnostic platforms, telehealth solutions, national and local systems—all interacting with each other in ways that aren’t always obvious. When something goes wrong, pinpointing where the issue originated can be incredibly challenging. Was it a configuration setting? A workflow design flaw? A user misunderstanding? A vendor update? A mismatch between national and local versions of the same system? Add to that, the fact that some third‑party suppliers are unable or unwilling to share detailed technical information (I assume due to concerns that competitors may gain access to it) makes it even harder to determine how the incident occurred or how to prevent it from happening again. Interconnected systems, shared responsibilities Because digital care rarely sits within a single organisation, the responsibilities for harm often cross boundaries too. Different organisations use systems differently. Local configurations vary. Some teams rely on national services; others are still using legacy versions. All of this makes investigation slower, more complicated and highly dependent on strong cross‑organisational collaboration. No single organisation can fully assess digital‑related harm in isolation, but still we try! The challenge for non-patient‑facing Health Bodies For organisations like mine, there is an added complexity: we don’t have direct clinical access to patients. This means our ability to assess harm depends on the engagement of colleagues across health boards and trusts—many of whom are experiencing significant operational pressures. Data security and privacy Sharing information about harm while protecting patient data is essential, but not always simple. We must balance transparency with strict confidentiality requirements. Digital errors, diagnostic risks and human interpretation Not all harm is caused directly by digital systems. Sometimes the system works correctly, but the presentation of the data creates an issue, or the clinician/user interaction or interpretation of the data is the issue. Other times, issues stem from algorithmic limitations, technical malfunctions or messaging fabric (infrastructure that connects the system components and allows them to communicate) problems. Determining whether harm originated with the tool, the user or the interaction between them is rarely straightforward, and tools like Systems Engineering Initiative for Patient Safety (SEIPS) are vital in breaking this complexity down. Training, local workarounds and the gaps no one talks about Training remains a significant challenge. National bodies like mine are not responsible for delivering frontline training, and local approaches vary widely. This leads to several risks: Depth and quality of training varies. Important system features may be misunderstood or overlooked. Safety considerations are not always emphasised during training. Local 'shortcuts'—never designed, tested or approved—become normal practice. Once these shortcuts become embedded in everyday workflows, they can be incredibly difficult to unwind. Yet they often play a significant role in digital‑related incidents. The existing DCB0129 and DCB0160 standards provide a useful foundation, but they offer limited guidance on how to investigate and learn from digital incidents. They were designed at a time when digital healthcare was far less complex than it is today. Suppliers don’t like to highlight their products weaknesses or errors made; therefore, there is vast variation in the quality of investigation reports shared post incident. Rather than worrying about reputational damage, I wish the focus was on candour and opportunities for learning and development. The timeliness problem: when harm takes time to surface Digital harm isn’t always immediate. It may be a misfiled result, a confusing display or a workflow that gradually introduces delay. Additional challenges include: Variation in national policy timescales (in Wales six differing policies provide timescale guidance). The need for clinical review to confirm harm. Limited capacity among clinicians supporting digital investigations. This can make it difficult to meet regulatory expectations for timely disclosure—even when everyone involved is committed to doing the right thing. Freedom to Speak Up: a critical enabler of early detection Speaking up plays a vital role in identifying digital‑related safety issues early. Many concerns emerge informally at first—“this doesn’t look right” or “this field always causes confusion.” If staff feel unsure about raising these concerns, they can remain hidden until harm occurs. Strengthening a Freedom to Speak Up culture is essential. It provides all staff a protected route to escalate concerns, even when they feel uncertain or worry that a system issue might be dismissed as user error or a training gap. I firmly believe that a strong speaking up culture means digital risks are more likely to be surfaced early, before they become incidents. A rapidly changing safety landscape Wales has seen significant changes in digital governance and health policy in recent years, from the transition from NHS Wales Informatics Service (NWIS) to Digital Health & Care Wales (DHCW) to updates in national structures (NHS Executive now NHS Performance & Improvement) and regulatory expectations. As I type, the National Health Service (Concerns, Complaints and Redress Arrangements) (Wales) Regulations 2011 (often referred to as 'Putting Things Right') are undergoing review and update. These shifts can create uncertainty about roles, responsibilities and reporting pathways. When something goes wrong, it’s not always clear who is responsible for what—and this ambiguity can complicate harm assessment. Where digital meets traditional healthcare Digital systems are embedded into clinical workflows, communication pathways and multi‑team processes. Every interface, integration point and manual interaction/data entry represents a potential source of risk. Reviewing these interconnected pathways is rarely quick or straightforward, but it is essential for understanding how digital harm occurs and how it can be prevented. Conclusion and call to action: building a safer digital future together The reflections in this paper highlight the complexity of digital patient safety work. Digital systems bring enormous potential for improving care, but they also introduce new risks that we are still learning how to manage. To address these challenges, we need a coordinated national approach that brings together healthcare organisations, digital suppliers, clinical safety experts, policymakers and frontline staff. This means: Updating and strengthening digital safety standards. Improving consistency in both incident investigation and harm assessment. Enhancing training and digital literacy. Supporting timely, transparent reporting. Facilitating availability of clinicians to undertaken harm reviews. Encouraging openness and speaking up. Improved incident data triangulation. Thematic analysis of incidents and nationally shared learning. Building stronger cross‑organisational collaboration. Most importantly, we need a culture where digital concerns are raised early and acted upon quickly. The opportunity ahead is significant, as are some of the challenges… But I truly believe that by working together, we can shape a safer digital health landscape—one that protects patients, supports professionals and ensures that innovation enhances care rather than complicating it. Further reading on the hub: How do we harness technology responsibly to safeguard and improve patient care? NHS England warns electronic patient record could pose ‘serious risks to patient safety’: what can we learn? The foundations for a safe digital service delivery in health—A blog by Rob Ludman Applying a robust approach to digital clinical safety in diagnosis b

Adverse event reporting is critical for advancing patient safety within healthcare systems. A significant factor in enhancing reporting rates is establishing a 'just culture'; a framework that emphasises accountability and learning over punitive measures. While just culture significantly enhances adverse event reporting, its successful implementation requires robust commitment at all organisational levels. Reporting adverse events is essential for ensuring patient safety and fostering a culture of continuous improvement in healthcare. Adverse events, defined as unintended injuries or complications arising from healthcare management, offer crucial insights into systemic weaknesses that, if addressed, can prevent future harm. However, underreporting such events remains a significant challenge, often driven by fear of punitive actions, reputational damage or legal repercussions. To address these concerns and promote a robust reporting culture, healthcare organisations must adopt a just culture by implementing standardised frameworks for evaluating errors and establishing robust reporting systems. Transparency in handling reported incidents is critical for building trust among healthcare professionals. Understanding just culture Just culture represents a shift from a blame-oriented approach to one that balances accountability with a focus on systemic improvement. Originating in high-risk industries such as aviation, the concept emphasises that errors result from flawed processes rather than individual negligence. In a just culture, individuals are held accountable for their actions within a fair and transparent system that prioritises learning and improvement. Central to the philosophy of just culture is the idea of psychological safety. When healthcare professionals feel confident reporting errors will not lead to unjust punishment, they are more likely to disclose incidents. This openness enables organisations to identify trends, address root causes and implement preventive measures. Moreover, just culture recognises the distinction between human errors, at-risk behaviours, and reckless conduct, advocating for tailored responses that align with the nature of the behaviour. Barriers to adverse event reporting Despite its potential, the implementation of just culture faces several obstacles. A predominant challenge is the deeply ingrained blame culture within many healthcare organisations. Historical reliance on punitive measures has created an environment where professionals fear repercussions, discouraging transparency. Additionally, managerial inconsistency in addressing errors often undermines trust in the system. For instance, discrepancies in how similar incidents are handled can create perceptions of unfairness, further discouraging reporting. Another barrier is the lack of understanding and awareness of just culture principles among healthcare staff. Without proper training and education, employees may misinterpret the approach as being lenient or as failing to hold individuals accountable. Legal and regulatory pressures also pose challenges, as concerns about litigation can deter organisations from fully embracing non-punitive reporting frameworks. Strategies for implementing just culture Implementing a just culture in healthcare requires a multifaceted approach that addresses organisational, managerial and individual factors. Leadership commitment is paramount; leaders must model just cultural behaviours, demonstrate accountability and prioritise safety over blame. Developing clear policies and guidelines for error classification and response is equally important as it ensures consistency and fairness in how incidents are addressed. Education and training programmes are vital in promoting awareness and understanding of just culture principles. These programmes should emphasise the distinction between human errors, at-risk behaviours and reckless conduct, providing staff with the tools to respond appropriately. Role-playing scenarios, workshops and case studies can help reinforce these concepts and demonstrate their practical application. The integration of non-punitive reporting systems is another critical component. Such systems should be designed to facilitate easy and confidential reporting, with mechanisms to protect the anonymity of reporters when appropriate. Feedback loops are essential for ensuring that staff are informed about the outcomes of reported incidents, which can reinforce the value of reporting and build trust in the system. Measuring the impact of just culture Assessing the effectiveness of just culture initiatives requires the development of standardised metrics and evaluation tools. Key performance indicators may include reporting rates, staff perceptions of psychological safety and the frequency of systemic improvements resulting from reported incidents. Periodic surveys and interviews can provide valuable insights into staff attitudes and identify areas for improvement. Case studies from organisations that have successfully implemented just culture can also serve as benchmarks for best practices. For instance, hospitals that report significant increases in adverse event reporting rates following the adoption of just culture principles often attribute their success to strong leadership, comprehensive training, and consistent application of policies. Sustaining cultural change Sustaining a just culture requires ongoing commitment and adaptability. Organisations must regularly evaluate their policies and practices to ensure alignment with just culture principles. Staff feedback should be actively sought and incorporated into decision-making processes, fostering a sense of ownership and engagement. Continuous education and training are essential for reinforcing just culture behaviours and addressing emerging challenges. Additionally, leadership succession planning should prioritise candidates who are committed to upholding just culture principles, ensuring continuity in organisational values. Conclusion Adverse event reporting is a fundamental component of patient safety, and the principles of just culture provide a robust framework for enhancing reporting rates and fostering systemic improvements. By balancing accountability with a focus on learning and improvement, just culture creates an environment where healthcare professionals feel empowered to report incidents without fear of retribution. Leadership commitment, staff education and integrating non-punitive reporting systems are critical for overcoming barriers and sustaining cultural change. A just culture represents a paradigm shift in addressing adverse events, emphasising systemic improvement over individual blame. Its successful adoption has the potential to transform healthcare organisations, making them safer and more resilient. Future research should focus on developing standardized metrics to evaluate just culture initiatives and exploring their applicability across diverse healthcare settings.

Medical errors remain a significant challenge in healthcare systems across Europe, affecting patient safety and trust. Despite advancements in medical practices, barriers to effective error reporting persist, limiting opportunities for learning and improvement. To address these critical issues, the European Patient Safety Foundation (EUPSF) together with the World Patients Alliance (WPA) are hosting a webinar. This session will bring together experts, policymakers, and patient representatives to discuss the current landscape of medical errors, explore solutions for improving reporting mechanisms, and foster a culture of transparency and learning within healthcare systems. Join us as we work toward building safer and more accountable healthcare for all. Register

The overall objective of this masterclass is to build good governance commitment, capacity, and resilience in the face of severe resource constraints and complex staff, patient, political and regulatory expectations. The programme is interactive, developmental, based on best practice and focused on achievable improvement of practice, behaviours and outcomes. The course includes online access to the relevant CQG e-learning module for 12 months and a discount code to purchase additional modules. This masterclass is one of a series that will help enhance your understanding and application of governance in healthcare, this module is designed to help boards avoid silo thinking, over-complex agendas or multiple reports by exploring the three elements of Integrated Governance which are: Integrated thinking, systems, and reporting. At the completion of this module, the participant will be able to: Appreciate the value of integrated thinking Recognise the importance of building integrated systems Understand the importance of integrated reporting to inform management, the board, and stakeholders Apply the learning to the participant’s own organisation using the CQG Maturity Matrix. Register

After attending a recent Patient Safety Management Network session, Emma Walker reflects on reporting on near misses. I was on one of the great Patient Safety Management Network drop-ins the other week, where they were sharing the learning from a safety observation session. The Session had been in a busy A&E department and at one point the observer flagged that a patient hadn’t been given a name tag for their wrist. The observer stepped in, identified the harm and it was rectified. I asked in the meeting chat if the organisation in question had flagged this as a near miss? "No, I don’t think so" was the response – "there are just too many near misses, and we are just too busy to report every one." Many folk on the call agreed. I was surprised to hear this. Having spent nearly 20 years married to a chemical engineer and spending a lot of my free time with engineers from across industry, I know that this behaviour would be totally unacceptable across the organisational cultures they work in, and potentially a reportable/disciplinary issue. Interestingly, their ingrained behaviours and cultures are such that it doesn’t usually get to that stage as everyone just knows what the right thing to do is and there are systems and cultures to make it easy. However, not the NHS it seems. As my husband said when we discussed this later, "this is free learning, and there are hundreds of firms across the country willing to show you tools and techniques to make reporting quick and easy". A colleague of mine, who was recently clinical, mentioned how ‘busy’ and ‘longwinded’ some reporting forms are... having to log into a computer (if one is available) while so busy: "I used to do mine at the end of a shift, not getting home till after 10 at night despite finishing at 20:15". Going back to the PSMN drop-in, what was really interesting was a nurse from the USA at the meeting was one of the few who agreed that not reporting near misses was really poor safety culture. She talked about how they are an aspiring high reliability organisation and how "we love near misses – we call them great catches". What can you do today to start changing your safety culture? How can you make it easy for all staff to do the right thing? A culture that doesn’t blame with easy, quick processes to follow, and support for staff to do just that. Go and make a great catch and prevent the next patient/member of staff suffering the same harm. As we know, a great catch missed today could become something far worse tomorrow. Do you have a 'good catch' reporting system? Share your experiences and questions in our Community thread or comment below You'll need to register for free first. . Related reading: Near-Miss and Good-Catch Reporting Promote a culture of safety with good catch reports Using good catches to increase worker ownership of safety 5 Examples of good catches in healthcare and how to implement a near miss campaign