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Highlights • A case study in a neuro-surgery department is presented. • Social and technical analyses are jointly adopted to cope with system complexity. • The Variability Impact Matrix for FRAM analyses is introduced. • Ad hoc functional performance indicators and corrective measures are proposed. Abstract Healthcare practitioners are generally forced to adapt their actions to cope with the complexity of daily conditions, taking advantage of their inherent potential for resilient performance. Following the principles of Resilience Engineering, this article details the application of the Functional Resonance Analysis Method (FRAM), for a semi-quantitative risk analysis of patient's pathway. The analysis adopts a holistic perspective on the complexity of everyday work in order to manage emergent behaviours, mainly related to iatrogenic disease associated with neuro-anesthesia treatment. Enhancing the traditional FRAM approach, the paper presents a structured systemic analysis for a case study in the neurosurgery peri‑operative patient's pathway. A multi-layer semi-quantitative framework is used as a basis for a novel decision support tool: the Variability Impact Matrix (VIM). The VIM aids to prioritize corrective measures and the need for functional performance indicators. A combination of social and technical perspectives is confirmed being necessary to cope with complex work environments, such as healthcare practices. [ABSTRACT FROM AUTHOR]

Post-operative delirium (POD) is a health hazard condition for the patients and it is associated with increased costs for the healthcare system. Following a system-theoretic approach, firstly a model, then a questionnaire, have been designed to probe the collective awareness about POD throughout the entire patient's perioperative pathway. The 58 reported answers pointed out that most of the information, specifically associated with POD, are routinely recorded but not used to stratify the patients' individual risk to develop POD. The results suggest the need for design a new socio-technical role within modern health care systems: the POD analyst. A Systems-Theoretic Accident Model and Processes (STAMP) model is proposed both to propel the awareness about POD and as a template for future POD risk factors collections. [ABSTRACT FROM AUTHOR]

• We discuss the relevance of cyber aspects for modern socio-technical systems. • The notion of Cyber-Socio-Technical Systems is presented (CSTSs). • The WAx framework is presented for the analysis of CSTSs. • Application examples of the WAx framework are discussed in different domains. Modern work domains are constituted by an intertwined set of social and technical actors with different, often conflicting, functional purposes. These agents act jointly to ensure system's functioning under both expected and unexpected working conditions. Considering the increasing digitalization and automation of work processes, socio-technical systems are progressively including interconnected cyber technical artefacts, thus becoming cyber-socio-technical systems (CSTSs). Adopting a natural science perspective, this paper aims to explore knowledge creation and knowledge conversion within CSTSs, as rooted in an in-depth analysis of work practices and work contexts. The paper proposes a conceptual framework which unveils the relationships between different work representations, i.e. relying on Work-As-Imagined, Work-As-Done, Work-As-Disclosed, Work-As-Observed, intended as knowledge entities generated by different agents, i.e. sharp-end operators, blunt-end operators, and analysts. The recursive and fractal nature of the proposed WAx (Work-As-x) framework ensures its adaptability for different granularity levels of analysis, fostering the understanding, modeling, and analysis of work practices, while abandoning reductionist and over-simplistic approaches. [ABSTRACT FROM AUTHOR]

There is a paucity of clinical evidence that guides perioperative glycemia management in patients undergoing craniotomy for brain tumor resection. The purpose of this study was to better understand global perceptions and practices related to glycemia management in these patients. Neuroanesthesiologists throughout North America, South America, Europe, and Asia filled out a brief online questionnaire related to their perceptions and practices regarding glycemia management in patients undergoing craniotomy for brain tumor resection. Over 4 weeks, 435 participants practicing in 34 countries across 6 continents participated in this survey. Although responders in North America were found to perceive a higher risk hyperglycemia compared with those practicing in European (P = 0.024) and South Asian (P = 0.007) countries, responders practicing in South Asian countries (P = 0.030), Middle Eastern countries (P = 0.029), and South American (P = 0.005) countries were more likely than those from North America to remeasure glucose after an initial normal glucose measurement at incision. Responders from North America reported that a higher blood glucose threshold was necessary for them to delay or cancel the surgery compared with responders in Slavic (P < 0.001), European (P = 0.002), South American (P = 0.002), and Asian and Pacific (P < 0.001) countries. Responders from North America were more likely to report that they would delay or cancel the surgery because of a higher blood glucose threshold. Our survey results suggest that perceptions and practices related to blood glucose management in patients undergoing brain tumor resection are variable. This study highlights the need for stronger clinical evidence and guidelines to help guide decisions for when and how to manage blood glucose derangements in these patients. [ABSTRACT FROM AUTHOR]

• A multilayer social network of resilience abilities in an intensive care unit. • There are four layers: monitor, anticipate, respond, and learn. • Three actor-centred and two layer-centred metrics are analysed. • Guidance for interpreting the metrics from the resilience engineering viewpoint. • Multilayer analysis is complementary rather than a replacement for the unilayer analysis. Resilient performance is influenced by social interactions of several types, which may be analysed as layers of interwoven networks. The combination of these layers gives rise to a "network of networks", also known as a multilayer network. This study presents an approach to develop and interpret multilayer networks in light of resilience engineering. Layers correspond to the four abilities of resilient systems: monitor, anticipate, respond, and learn. The proposal is applied in a 34-bed intensive care unit. To map relationships between actors in each layer, a questionnaire was devised and answered by 133 staff members, including doctors, nurses, nurse technicians, and allied health professionals. Two multilayer networks were developed: one considering that actors are 100% available and reliable (work-as-imagined) and another considering suboptimal availability and reliability (work-as-done). The multilayer networks were analysed through actor-centred (Katz centrality, degree deviation, and neighbourhood centrality) and layer-centred metrics (inter-layer correlation, and assortativity correlation). Strengths and weaknesses of social interactions at the ICU are discussed based on the adopted metrics. [ABSTRACT FROM AUTHOR]