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Although it is widely acknowledged that health care delivery systems are complex adaptive systems, there are gaps in understanding the application of systems engineering approaches to systems analysis and redesign in the health care domain. Commonly employed methods, such as statistical analysis of risk factors and outcomes, are simply not adequate to robustly characterize all system requirements and facilitate reliable design of complex care delivery systems. This is especially apparent in institutional-level systems, such as patient safety programs that must mitigate the risk of infections and other complications that can occur in virtually any setting providing direct and indirect patient care. The case example presented here illustrates the application of various system engineering methods to identify requirements and intervention candidates for a critical patient safety problem known as failure to rescue. Detailed descriptions of the analysis methods and their application are presented along with specific analysis artifacts related to the failure to rescue case study. Given the prevalence of complex systems in health care, this practical and effective approach provides an important example of how systems engineering methods can effectively address the shortcomings in current health care analysis and design, where complex systems are increasingly prevalent.

Failure to rescue events, or events involving preventable deaths from complications, are a significant contributor to inpatient mortality. While many interventions have been designed and implemented over several decades, this patient safety issue remains at the forefront of concern for most hospitals. In the first part of this study, the development and implementation of one type of highly studied and widely adopted rescue intervention, algorithm-based patient assessment tools, is examined. The analysis summarizes how a lack of systems-oriented approaches in the design and implementation of these tools has resulted in suboptimal understanding of patient risk of mortality and complications and the early recognition of patient deterioration. The gaps identified impact several critical aspects of excellent patient care, including information-sharing across care settings, support for the development of shared mental models within care teams, and access to timely and accurate patient information.

This chapter describes the use of several system-oriented design and implementation activities to establish design objectives, model clinical processes and workflows, and create an extensible information system model to maximize the benefits of patient state and risk assessment tools in the inpatient setting. A prototype based on the product of the design activities is discussed along with system-level considerations for implementation. This study also demonstrates the effectiveness and impact of applying systems design principles and practices to real-world clinical applications.

Research on organizational culture has provided much needed subtlety in understanding organizational events. However, it has a cognitive bias which leaves implicit the treatment of emotional phenomena. Organizational stories can provide a window on affect in organizations if we view stories as symbolically embedded appraisals of wellbeing. Presents an illustrative case to demonstrate how such enquiry might proceed.

Presents a case description of a non‐profit educational agency whose organizational culture is based on the feminist values of caring, voice and self‐reflection. Grounded theory analysis of intensive interviews, focus groups, observations and organizational documents reveals how these values are embodied in the organization′s management practices and change processes. The case strongly suggests that a commitment to feminist values can prove highly generative of a wide range of desirable organizational competences.

Shift workers are more disturbed by changes in eating patterns than in sleeping patterns. The ill effects of shift working have, in any case, been exaggerated where they have not been invented.

Qualitative data analysis requires methodological knowledge and intellectual competence. Analysis is not about adhering to any one correct approach or set of right techniques; it is imaginative, artful, flexible, and reflexive. It should also be methodical, scholarly, and intellectually rigorous. (Coffey and Atkinson, 1996, p.1.

Brainstorming is a well‐known group process for generating new ideas and stimulating creativity. Important as well as robust findings have been achieved in determining which factors contribute most to facilitating or hindering the group's ideas productivity. Research aimed at comparing face‐to‐face (FTF) with computer‐mediated communication (CMC) led to the conclusion that this latter shared with the nominal group technique the advantages of avoiding either the blocking effect or the identification of the source. More recently, attention has turned to the possible effects of group support system (GSS) in the mediating cognitive processes of generating new ideas. The present study aims to examine the effects of the type of tool and of the anonymity condition on the quality, quantity and diversity of the generated ideas, as well as on group members' satisfaction.

Uses a 2 × 2 factorial design combining two different GSS tools (topic commenter vs EBS) with anonymity versus non‐anonymity.

It was found that anonymity generated more satisfaction among the group members. A marginal effect on satisfaction was also found to be related with the type of tools. Contrary to expectations, the EBS tool was not found to generate greater diversity of ideas. An interesting finding not anticipated was the impact of technology on the flow of ideas and on the emergence of new conceptual categories, probably due to alternative strategies of task structuring.

The use of students as subjects, and the running of the experimental work in a scholarly context, could have contributed to the elimination of fears and to freeing the participants from any inhibition in the anonymity conditions. Within an organisational context with higher social stratification, such anonymous procedures could have significant outcomes. Future research will have to examine whether this effect is relevant to other types of topics and other populations. Another aspect that it is important to re‐examine is the effect of anonymity on the emergence of minority ideas, which could stimulate innovation.

The type and characteristics of tools were shown to be a decisive factor in the participants' satisfaction, in the communication process and in the idea generation and clustering processes. Although tenuous, this set of data could mean that the characteristics of the tools interfere with the cognitive mechanisms present in the brainstorming technique.

Examines the effect of the technology and anonymity in ideas generation within a group context on the satisfaction of the participants.

Despite the potentially vital implications of time pressure for group performance in general and team effectiveness in particular, research has traditionally neglected the study of time limits and group effectiveness. We examine the small, but growing, body of research addressing the effect of time pressure on group performance and introduce our Attentional Focus Model of group effectiveness (Karau & Kelly, 1992). We examine recent research on the utility of the model and identify selected implications of the model for how time pressure may interact with other factors such as task type, group structure, and personality to influence team performance. Finally, we discuss methodological issues of studying attention, interaction processes, and team performance.

This paper explores how task characteristics in terms of trigger type and task topic influence individual participation in community-based free/libre open source software (FLOSS) development by considering participation in individual tasks rather than entire projects.

A quantitative study was designed using choose tasks that were carried out via the email discourse on the developers' email fora in five FLOSS projects. Choice process episodes were selected as the unit of analysis and were coded for the task trigger and topic. The impact of these factors on participation (i.e. the numbers of participants and messages) was assessed by regression.

The results reveal differences in participation related to different task triggers and task topics. Further, the results suggest the mediating role of the number of participants in the relationships between task characteristics and the number of messages. The authors also speculate that project type serves as a boundary condition restricting the impacts of task characteristics on the number of participants and propose this relationship for future research.

Empirical support was provided to the important effects of different task characteristics on individual participation behaviors in FLOSS development tasks.

The findings can help FLOSS participants understand participation patterns in different tasks and choose the types of tasks to attend to.

This research explores the impact of task characteristics on participation in FLOSS development at the task level, while prior research on participation in FLOSS development has focused mainly on factors at the individual and/or project levels.