This review aimed to provide a comprehensive overview of the current state of evidence for the use of clinical and quality dashboards in health care environments. A literature search was performed for the dates 1996-2012 on CINAHL, Medline, Embase, Cochrane Library, PsychInfo, Science Direct and ACM Digital Library. A citation search and a hand search of relevant papers were also conducted. One hundred and twenty two full text papers were retrieved of which 11 were included in the review. There was considerable heterogeneity in implementation setting, dashboard users and indicators used. There was evidence that in contexts where dashboards were easily accessible to clinicians (such as in the form of a screen saver) their use was associated with improved care processes and patient outcomes. There is some evidence that implementing clinical and/or quality dashboards that provide immediate access to information for clinicians can improve adherence to quality guidelines and may help improve patient outcomes. However, further high quality detailed research studies need to be conducted to obtain evidence of their efficacy and establish guidelines for their design.

Although researchers have developed robust approaches for estimating, location, and user identity, estimating user activities has proven much more challenging. Human activities are so complex and dynamic that it's often unclear what information is even relevant for modeling activities. Robust approaches to recognize user activities requires identifying the relevant information to be sensed and the appropriate sensing technologies. In our effort to develop an approach for automatically estimating hospital-staff activities, we trained a discrete hidden Markov model (HMM) to map contextual information to a user activity. We trained the model and evaluated it using data captured from almost 200 hours of detailed observation and documentation of hospital workers. In this article, we discuss our approach, the results, and how activity recognition could empower our vision of the hospital as a smart environment.

Children with autism have difficulty sustaining their selective attention during therapy sessions. Attention management techniques involve the use of verbal and visual prompting, annotated on top of the physical objects used during therapies. Here, the authors explore how augmented reality helps integrate the physical and digital worlds, mimicking current strategies for attention management in autism. They describe their design decisions when developing the Mobile Object Identification System (Mobis), a mobile augmented reality application that lets teachers superimpose digital content on top of physical objects. The results of a five-week deployment study demonstrate that Mobis is useful and easy to use, increases the sustained and selective attention of children with autism, and elicits positive emotions during therapies. This article is part of a special issue on managing attention.

In this article, we introduce activity-aware computing, which uses activity-based computing to enhance pervasive environments in two ways: to help users associate resources and services with activities, resulting in seamless interaction with those resources and services, and to enable pervasive environments to automatically infer activities and thus opportunistically offer services that support the user's current goal. Thus, activity-aware applications persuade users to commit themselves to the technology, moving from a paradigm of activity-based ";interaction"; toward one of activity-aware ";engagement"; with a computationally augmented environment. We present a set of tools for developing activity-aware applications, including a computational representation of human activities that we defined using data from a hospital case study we conducted. We also used the data to create an activity recognition approach and a set of design principles for developing activity-aware applications. The mobile activity monitor we designed to create a wearable connection between patients and nurses exemplifies our design principles.