Communicative patterns in organizational (healthcare) teams

As team processes are often consigned to a ‘black box’, this dissertation contributes to unpacking team-level communicative processes as drivers for organizational team functioning. Both conceptually and empirically, we aimed to untangle how communicative processes unfold during collaboration periods in organizational teams. In the first part of this dissertation, we contributed to a more process-oriented understanding of team-based collective intelligence. In addition, we developed a comprehensive framework to study communicative patterns from various aspects (i.e., content, structure, and temporality) and showed how patterned communication may relate to team and organizational-level outcomes. In our own empirical work, we found fine-grained evidence for more back-and-forth communicative patterns underlying the decision-making process in multidisciplinary healthcare team meetings, which seems to be rooted in insufficient orientation of the patients’ background problems. In addition, we observed that team members respond with emotionally laden communication after naturally occurring workflow interruptions, together with more conversational clarification. In sum, both scholars and practitioners benefit from understanding patterned communication because these insights offer sound foundations to reflect on improvements regarding organizational team functioning

Communicative patterns in organizational (healthcare) teams

As team processes are often consigned to a ‘black box’, this dissertation contributes to unpacking team-level communicative processes as drivers for organizational team functioning. Both conceptually and empirically, we aimed to untangle how communicative processes unfold during collaboration periods in organizational teams. In the first part of this dissertation, we contributed to a more process-oriented understanding of team-based collective intelligence. In addition, we developed a comprehensive framework to study communicative patterns from various aspects (i.e., content, structure, and temporality) and showed how patterned communication may relate to team and organizational-level outcomes. In our own empirical work, we found fine-grained evidence for more back-and-forth communicative patterns underlying the decision-making process in multidisciplinary healthcare team meetings, which seems to be rooted in insufficient orientation of the patients’ background problems. In addition, we observed that team members respond with emotionally laden communication after naturally occurring workflow interruptions, together with more conversational clarification. In sum, both scholars and practitioners benefit from understanding patterned communication because these insights offer sound foundations to reflect on improvements regarding organizational team functioning

Multi-level agent-based modeling - A literature survey

During last decade, multi-level agent-based modeling has received significant and dramatically increasing interest. In this article we present a comprehensive and structured review of literature on the subject. We present the main theoretical contributions and application domains of this concept, with an emphasis on social, flow, biological and biomedical models.Comment: v2. Ref 102 added. v3-4 Many refs and text added v5-6 bibliographic statistics updated. v7 Change of the name of the paper to reflect what it became, many refs and text added, bibliographic statistics update

Mapping Health Care Innovation: Tracing Walls & Ceilings

Health care is in need of innovation on many strands. Patient-centered care appears to be the key to the realization of the main objectives: service quality, cost reduction, access, patient satisfaction and the quality of working life. Innovation, and more precisely, the diffusion and implementation of new methods, new techniques and new processes and systems appears to be a difficult task. Consequently, there is a strong need for knowledge about innovation processes in health care and the drivers and barriers affecting these efforts. This paper presents a framework for mapping innovation processes in health care services. The framework consists of two axes: (1) the horizontal axis of the health care process and the inter-functional walls which can complicate innovation efforts, and (2) the vertical axis of the echelons of power, which often create ceilings too impermeable to permit effective learning and decision making. The study is based on the experiences gathered in Publin, a running research network supported by the Fifth Framework Program and Innoflex, which ended in 2003.economics of technology ;

Advances in bioimaging - Challenges and potentials

[No abstract available

Evaluating the Potential of Leading Large Language Models in Reasoning Biology Questions

Recent advances in Large Language Models (LLMs) have presented new opportunities for integrating Artificial General Intelligence (AGI) into biological research and education. This study evaluated the capabilities of leading LLMs, including GPT-4, GPT-3.5, PaLM2, Claude2, and SenseNova, in answering conceptual biology questions. The models were tested on a 108-question multiple-choice exam covering biology topics in molecular biology, biological techniques, metabolic engineering, and synthetic biology. Among the models, GPT-4 achieved the highest average score of 90 and demonstrated the greatest consistency across trials with different prompts. The results indicated GPT-4's proficiency in logical reasoning and its potential to aid biology research through capabilities like data analysis, hypothesis generation, and knowledge integration. However, further development and validation are still required before the promise of LLMs in accelerating biological discovery can be realized