Objective 

To investigate how task delegation for perioperative anticoagulation management is reported in protocols and daily practice, and how this translates to additional information in work-as-imagined and work-as-done using FRAM to identify improvement possibilities. 

Methods

Existing FRAM visualisations of perioperative anticoagulant management in a Dutch academic hospital were extended to include task delegation in protocols using document analysis and in daily practice using a focus group of eight healthcare professionals, analysed using content analysis.

Results

Distinguishing between formal responsibility and task execution revealed additional functions and roles in both work-as-done and work-as-imagined, resulting in more discrepancies between work-as-done and work-as-imagined. Professionals experienced responsibility for delegated tasks, even without formal accountability, and needed to feel qualified and capable as well as complete clear information to accept these tasks. 

Conclusions

Including task delegation in FRAM models improves the understanding of healthcare processes, communication about distribution of responsibilities and thereby development of more effective improvement strategies.

The latest developments in AI have the potential to significantly support qualitative analysis of interview transcripts. This study explores the utility of the OpenAI o1-model to assist in efficiently obtaining reliable summarizations of safety culture interviews. Analysis shows that the current approach has the clear potential to significantly improve efficiency of interviewers by providing a concise report that summarizes multiple interviews according to a pre-defined format. However, some hallucinations are present in the generated report. Additional work will aim at reducing their presence, but such hallucinations also emphasizes that LLMs should primarily assist, rather than replace, interviewers in creating a definitive report.

Current treatment approaches for Autism spectrum disorder (ASD) primarily focus on symptom management rather than addressing underlying dysfunctions. The ketogenic diet (KD), a high-fat, low-carbohydrate diet inducing nutritional ketosis, has shown promise in treating epilepsy and may offer therapeutic benefits for ASD by modulating metabolic and neuroprotective pathways. This review examined the potential impact of KD on underlying mechanisms in ASD. While evidence from human studies on underlying mechanisms is limited, animal research has shown a large overlap of mechanisms modulated by KD and dysfunctions in ASD. As such, targeting multiple disrupted pathways at once, KD presents a potential multifaceted treatment approach for ASD. However, more evidence from human studies is needed on the effectiveness of KD in the modulation of underlying dysfunctions in ASD. Additionally, precision medicine approaches could help identify individuals who would benefit most from the intervention, potentially extending its use to other psychiatric conditions with similar metabolic patterns. Consequently, KD interventions might show the potential to induce a drastic paradigm shift in understanding and treating ASD.

Objectives The goal of sentinel event (SE) analysis is to prevent recurrence. However, the rate of SEs has remained constant over the past years. Research suggests this is in part due to the quality of recommendations. Currently, standards for the selection of recommendations are lacking. Developing a method to grade recommendations could help in both designing and selecting interventions most likely to improve patient safety. The aim of this study was to (1) develop a user-friendly method to grade recommendations and (2) assess its applicability in a large series of Dutch perioperative SE analysis reports. Methods Based on two grading methods, we developed the recommendation improvement matrix (RIM). Applicability was assessed by analysing all Dutch perioperative SE reports over a 12-month period. After which interobserver agreement was studied. Results In the RIM, two elements are crucial: whether the recommendation intervenes before or after an SE and whether it eliminates or controls the hazard. Applicability was evaluated in 115 analysis reports, encompassing 161 recommendations. Recommendation quality varied from the highest, category A, to the lowest, category D, with category A accounting for 44%, category B for 35%, category C for 2% and category D for 19% of recommendations. There was a fair interobserver agreement. Conclusion The RIM can be used to grade recommendations in SE analysis and could possibly help in both designing and selecting interventions. It is relatively simple, user-friendly and has the potential to improve patient safety. The RIM can help formulate effective and sustainable recommendations, a second key objective of the RIM is to foster and facilitate constructive dialogue among those responsible for patient safety.

When a train passes a red aspect, this is called a Signal Passed at Danger event or SPAD. Sometimes it is easy to identify the SPAD cause but in other cases it is unclear why the incident occurred, especially if the system operated as usual and the train driver was trained and experienced just like his or her colleagues. In previous research, train driver deceleration behaviour has been shown to be influenced by frequent exposure in the previous 14 days to less restrictive and visually similar signal aspects in the same location. Previous exposure can contribute to SPAD causation unless the initial insufficient deceleration is corrected in time. Six years of SPAD data and red aspect approaches in the Netherlands was used to test whether previous exposure to yellow:number aspects corresponds with a statistically significant increase in SPAD incidents if there is a small window for correction available to drivers. The permitted track speed and signal distance influence the size of this window. The results provide evidence for previous exposure as a cause for SPADs and details to identify locations with increased SPAD probability. Changes in infrastructure and timetable design or adding safety measures for these locations can prevent future SPADs.

Employee behavior plays an important role in the occurrence and prevention of incidents, affecting safety margins. In this study, we examine the potential impact of incidental learning on human behavior in the presence of variation in task design. Incidental learning is the day-to-day on-the-job learning that occurs unintentionally. This learning influences which behavior (schema) is more likely to be activated in the employee’s brain. We posit that an incorrect schema can be activated and lead to undesired behavior if the employee is often exposed to (visually) similar tasks that require different behavior. In rail transport, there is a risk of trains passing through red signals. The train driver’s behavior plays an important role in preventing these signal passed at danger (SPAD) incidents. In this study we used speed and location data to analyze train driver deceleration behavior during red signal approaches in the Netherlands. The Dutch rail system showed variation in yellow signal aspects and signal distance. An analysis using 19 months of empirical data indicated changes in behavior when the employee had been previously exposed to different behavior requirements in the same location with a similar yellow signal. These results imply that task design can be improved by taking into consideration what an employee is exposed to during other moments of the shift, and not just during the execution of the specific task.

Last minute risk assessment (LMRA) is a well-known work method to support employees’ risk perception. However, little is known about the effectiveness of LMRA in providing this support. Here, we describe an eye-tracking experiment with which we attempted to gain more insight into the relationship between LMRA and risk perception and to assess the difference between generic and specific supporting questions. Employees from an international energy production and desalination company participated in this experiment by assessing photographs portraying a (staged) work situation and deciding whether it was safe enough to continue activities and which risk factors were present or absent. The results show a consistent interaction effect over several parameters between work experience and the type of supporting questions, indicating that generic and specific supporting questions should be considered complimentary to each other. Furthermore, the results revealed several other challenges concerning real-world application of the LMRA.

Research question: What is the influence of general management trends and research into causes of accidents on safety management? Method: The literature study is limited to English and Dutch books, documents and articles in the scientific, professional, and technical literature from the period 1988–2010. Results and conclusions: Quite some developments occurred in the occupational safety domain. During the period concerned three models are developed, the Dutch Tripod Model, the Swedish Occupational Risk Unit Model (QARU), and the Dutch Occupational Risk Model (QRM), a barrier based model founded on the bowtie metaphor. These models address occupational accidents from different perspectives, and surprisingly similar factors. While terminology differs, these factors are called basic risk factors, situational, or management factors. Self-regulation of companies has been a strong stimulus for research on safety management systems and audits. Traditionally research in management related topics has not been part of safety research, and thus it has to be developed. While the quality of this type of research is rather low, a general structure of safety management systems is related to the Rhineland management concept. Such evidence is found in new management models such as the EFQM/INK and, to a lesser extent, Corporate Social Responsibility (CSR). While organisational learning, its quality and effectiveness on occupational safety is not researched in this period, research interests are focussing on other organisational aspects like safety culture and climate, including a renewed interest in human behaviour.

Ever since safety started to be investigated in a consistent manner, around 150 years ago, there has been a tremendous improvement, both in our understanding of accident processes, and in reduction of harm and damage caused by these occupational and major accidents. Major improvements in safety theories, models and metaphors were made after World War II, with the late 1970s till the late 1990s as the ‘golden years’. But still these major accidents occur and they will keep prompting future scientific developments in safety, as they have done in the past. Reducing the frequency of major accidents remains challenging. Improving design and automation, as starting point for safety has its limits due to the complexity of processes and the inability to foresee all safety related conflicts. The modern emphasis to assure the capacity to handle unforeseen events, such as resilience promises to deliver, will become even more important in the future. Inherent safe design on the other hand make a sensible approach when designing production processes for emerging and future technologies, like nano- and biotechnology. Also, it will remain difficult for small and medium sized enterprises to adhere to complicated laws and regulations. In addition, an increased participation of stakeholder groups makes future safety decision-making even more challenging than it already is today. Yet we foresee that there may be grounds for change in which safety rules, laws and regulations are set aside, the bureaucratic approach towards safety is stopped and the focus is on dynamic accident processes detection. Today, methods are developed to automatically assess time-dependant advancement of accident scenarios and barrier degradation. This direction will contribute substantially to a future higher level of safety in different industrial sectors and might alleviate the emphasis on bureaucracy. We end with developments in two countries where safety and safety science is emerging.

Objective: What is the influence of general management trends and safety research on managing safety? Method: A literature study which is limited to original English and Dutch books, documents, and articles in relevant scientific journals, for the period 1988–2010. Results and conclusions: Safety science does not yet have a unifying theory, which betrays its young age as a scientific discipline. In the period concerned, well-known theories, models and metaphors are established or re-issued, including the High Reliability Theory, the Man-Made Disasters and the corresponding Disaster Incubation Theory, and the Normal Accident Theory. The Swiss cheese metaphor takes its final form, the bowtie metaphor and the Drift into Danger model are published. All these theories, models and metaphors emphasize organisational aspects of major accidents in high-tech-high-hazard sectors. General management trends highlight the importance of external stakeholders, which are only reflected in the Drift into Danger metaphor. These developments must be considered in the context of a dynamic influence of external factors, like a decrease in government influence coinciding with strong market and technology developments, which can conflict with safety requirements for high-tech-high-hazard companies. Organisational/safety culture and risk/safety management systems take off during this period, both in terms of academic research and consultancy activities for companies. Whether these concepts will have a lasting influence on safety levels in companies is yet to be seen, given the unclear relationship with major accident processes. Research findings show that many companies suffer from sloppy management, having only a limited insight into possible disaster scenarios.

The field of safety and incident prevention is becoming more and more data based. Data can help support decision making for a more productive and safer work environment, but only if the data can be, is and should be trusted. Especially with the advance of more data collection of varying quality, checking and judging the data is an increasingly complex task. Within such tasks, cognitive biases are likely to occur, causing analysists to overestimate the quality of the data and safety experts to base their decisions on data of insufficient quality. Cognitive biases describe generic error tendencies of persons, that arise because people tend to automatically rely on their fast information processing and decision making, rather than their slow, more effortful system. This article describes five biases that were identified in the verification of a safety indicator related to train driving. Suggestions are also given on how to formalize the verification process. If decision makers want correct conclusions, safety experts need good quality data. To make sure insufficient quality data is not used for decision making, a solid verification process needs to be put in place that matches the strengths and limits of human cognition.