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Hospitals are complex environments that rely on clinicians working together to provide appropriate care to patients. These clinical teams adapt their interactions to meet changing situational needs. Venous thromboembolism (VTE) prophylaxis is a complex process that occurs throughout a patient's hospitalisation, presenting five stages with different levels of complexity: admission, interruption, re-initiation, initiation, and transfer. The objective of our study is to understand how the VTE prophylaxis team adapts as the complexity in the process changes; we do this by using social network analysis (SNA) measures. We interviewed 45 clinicians representing 9 different cases, creating 43 role networks. The role networks were analysed using SNA measures to understand team changes between low and high complexity stages. When comparing low and high complexity stages, we found two team adaptation mechanisms: (1) relative increase in the number of people, team activities, and interactions within the team, or (2) relative increase in discussion among the team, reflected by an increase in reciprocity. Practitioner Summary: The reason for this study was to quantify team adaptation to complexity in a process using social network analysis (SNA). The VTE prophylaxis team adapted to complexity by two different mechanisms, by increasing the roles, activities, and interactions among the team or by increasing the two-way communication and discussion throughout the team. We demonstrated the ability for SNA to identify adaptation within a team.

Human factors/ergonomics recognises work as embedded in and shaped by levels of social, physical and organisational context. This study investigates the contextual or macroergonomic factors present in the health-related work performed by patients. We performed a secondary content analysis of findings from three studies of the work of chronically ill patients and their informal caregivers. Our resulting consolidated macroergonomic patient work system model identified 17 factors across physical, social and organisational domains and household and community levels. These factors are illustrated with examples from the three studies and discussed as having positive, negative or varying effects on health and health behaviour. We present three brief case studies to illustrate how macroergonomic factors combine across domains and levels to shape performance in expected and unexpected ways. Findings demonstrate not only the importance of context for patients' health-related activities but also specific factors to consider in future research, design and policy efforts. Practitioner Summary: Health-related activities of patients are embedded in and shaped by levels of social, physical and organisational context. This paper combined findings from three studies to specify 17 contextual or macroergonomic factors in home- and community-based work systems of chronically ill patients. These factors have research, design and policy implications.

Healthcare practitioners, patient safety leaders, educators, and researchers increasingly recognize the value of human factors/ergonomics and make use of the discipline’s person-centered models of sociotechnical systems. This paper first reviews one of the most widely used healthcare human factors systems models, the Systems Engineering Initiative for Patient Safety (SEIPS) model, and then introduces an extended model, “SEIPS 2.0.” SEIPS 2.0 incorporates three novel concepts into the original model: configuration, engagement, and adaptation. The concept of configuration highlights the dynamic, hierarchical, and interactive properties of sociotechnical systems, making it possible to depict how health-related performance is shaped at “a moment in time.” Engagement conveys that various individuals and teams can perform health-related activities separately and collaboratively. Engaged individuals often include patients, family caregivers, and other non-professionals. Adaptation is introduced as a feedback mechanism that explains how dynamic systems evolve in planned and unplanned ways. Key implications and future directions for human factors research in healthcare are discussed.