Making decisions about what clinical tasks to prepare for is multi-factored, and especially challenging in intensive care environments where resources must be balanced with patient needs. Electronic health records (EHRs) are a rich data source, but are task-agnostic and can be difficult to use as summarizations of patient needs for a specific task, such as "could this patient need a ventilator tomorrow?" In this paper, we introduce ClinicalVis, an open-source EHR visualization-based prototype system for task-focused design evaluation of interactions between healthcare providers (HCPs) and EHRs. We situate ClinicalVis in a task-focused proof-of-concept design study targeting these interactions with real patient data. We conduct an empirical study of 14 HCPs, and discuss our findings on usability, accuracy, preference, and confidence in treatment decisions. We also present design implications that our findings suggest for future EHR interfaces, the presentation of clinical data for task-based planning, and evaluating task-focused HCP EHR interactions in practice.
This paper introduces the application of visual analytics techniques as a novel approach for improving economic decision making. Particularly, we focus on two known problems where subjectspsila behavior consistently deviates from the optimal, the Winnerpsilas and Loserpsilas Curse. According to economists, subjects fail to recognize the profit-maximizing decision strategy in both the Winnerpsilas and Loserpsilas curse because they are unable to properly consider all the available information. As such, we have created a visual analytics tool to aid subjects in decision making under the Acquiring a Company framework common in many economic experiments. We demonstrate the added value of visual analytics in the decision making process through a series of user studies comparing standard visualization methods with interactive visual analytics techniques. Our work presents not only a basis for development and evaluation of economic visual analytic research, but also empirical evidence demonstrating the added value of applying visual analytics to general decision making tasks. Patients do considerable information work. Technologies that help patients manage health information so they can play active roles in their health-care, such as personal health records, provide patients with effective support for focused and sustained personal health tasks. Yet, little attention has been paid to patients' needs for information management support while on the go and away from their personal health information collections. Through a qualitative field study, we investigated the information work that breast cancer patients do in such 'unanchored settings'. We report on the types of unanchored information work that patients do over the course of cancer treatment, reasons this work is challenging, and strategies used by patients to overcome those challenges. Our description of unanchored patient information work expands our understanding of patients' information practices and points to valuable design directions for supporting critical but unmet needs. Children with complex health conditions require care from a large, diverse team of caregivers that includes multiple types of medical professionals, parents and community support organizations. Coordination of their outpatient care, essential for good outcomes, presents major challenges. Extensive healthcare research has shown that the use of integrated, team-based care plans improves care coordination, but such plans are rarely deployed in practice. This paper reports on a study of care teams treating children with complex conditions at a major university tertiary care center. This study investigated barriers to plan implementation and resultant care coordination problems. It revealed the complex nature of teamwork in complex care, which poses challenges to team coordination that extend beyond those identified in prior work and handled by existing coordination systems. The paper builds on a computational teamwork theory to identify opportunities for technology to support increased plan-based complex-care coordination and to propose design approaches for systems that enable and enhance such coordination. Today the design of most healthcare technology is driven by the considerations of healthcare professionals and technology companies. This has several benefits, but we argue that there is a need for a supplementary design approach on the basis the citizen and his or her everyday life. An approach where the main focus is to develop healthcare technology that fits the routines of daily life and thus allows the citizens to continue with the activities they like and have grown used to -- also with an aging body or when managing a chronic condition. Thus, with this approach it is not just a matter of fixing a health condition, more importantly is the matter of sustaining everyday life as a whole. This argument is a result from our work -- using participatory design methods -- on the development of supportive healthcare technology for elderly people and for diabetic, pregnant women. 1. Information Visualization 2. Space 3. Interaction 4. Focus + Context 5. Data Mapping: Text 6. Higher-Level Visualization 7. Using Vision to Think 8. Applications and Innovations 9. Conclusion Bibliography Index This is the book form of the Research and Development Agenda for Visual Analytics to be published by IEEE in 2005.