Barriers to information transfer for multi-trauma patients upon discharge from the Emergency Department in a tertiary level hospital

Purpose: Communication is integral to effective trauma care provision. This presentation will report on barriers to meaningful information transfer for multi-trauma patients upon discharge from the Emergency Department (ED) to the care areas of Intensive Care Unit, High Dependency Unit, and Perioperative Services. This is an ongoing study at one tertiary level hospital in Queensland. Method: This is a multi-phase, mixed method study. In Phase 1 data were collected about information transfer. This Phase was initially informed by a comprehensive literature review, then via focus groups, chart audit, staff survey and review of national and international trauma forms. Results: The barriers identified related to nursing handover, documented information, time inefficiency, patient complexity and stability and time of transfer. Specifically this included differences in staff expectations and variation in the nursing handover processes, no agreed minimum dataset of information handed over, missing, illegible or difficult to find information in documentation (both medical and nursing), low compliance with some forms used for documentation. Handover of these patients is complex with information coming from many sources, dealing with issues is more difficult for these patients when transferred out of hours. Conclusions and further directions: This study investigated the current communication processes and standards of information transfer to identify barriers and issues. The barriers identified were the structure used for documentation, processes used (e.g. handover), patient acuity and time. This information is informing the development, implementation and evaluation of strategies to ameliorate the issues identified.

Creating new narratives through shared time and space : the performer/audience connection in multi-site dance events

Site-specific performance provides choices in audience experience via degrees of scale, proximity, levels of immersion and viewing perspectives. Beyond these choices, multi-site promenade events also form a connected audience/performer relationship in which moving together in time and space can produce a shared narrative and aesthetic sensibility of collective, yet individuated and shifting meanings. This paper interrogates this notion through audience/performer experiences in two separate multi-site, dance-led events. here/there/then/now occurred in four intimate sites within the Brisbane Powerhouse, providing a theatricalised platform for audiences to create linked narratives through open-ended and fragmented intertextuality. Accented Body, based on the concept of “the body as site and in site” and notions of connectivity, provided a more expansive platform for a similar, but heightened, shared engagement. Audiences traversed 6 outdoor and 2 indoor Brisbane sites moving to varying levels of a large complex. Eleven, predominantly interactive, screens provided links to other sites as well as to distributed presences in Seoul and London. The differentiation in scale and travel time between sites deepened the immersive experiences of audiences who reported transformative engagements with both site and architecture, accompanied by a sense of extended and yet quickened time.

Practical improvements to simultaneous computation of multi-view geometry and radial lens distortion

This paper discusses practical issues related to the use of the division model for lens distortion in multi-view geometry computation. A data normalisation strategy is presented, which has been absent from previous discussions on the topic. The convergence properties of the Rectangular Quadric Eigenvalue Problem solution for computing division model distortion are examined. It is shown that the existing method can require more than 1000 iterations when dealing with severe distortion. A method is presented for accelerating convergence to less than 10 iterations for any amount of distortion. The new method is shown to produce equivalent or better results than the existing method with up to two orders of magnitude reduction in iterations. Through detailed simulation it is found that the number of data points used to compute geometry and lens distortion has a strong influence on convergence speed and solution accuracy. It is recommended that more than the minimal number of data points be used when computing geometry using a robust estimator such as RANSAC. Adding two to four extra samples improves the convergence rate and accuracy sufficiently to compensate for the increased number of samples required by the RANSAC process.

Using visuals to explore the contextual aspects of user-product interactions

Experience underlies all kinds of human knowledge and it is dependent on context. People’s experience within a particular context-of-use determines how they interact with products. Methods employed in this research to elicit human experience have included the use of visuals. This paper describes two empirical studies that employed visual representation of concepts as a means to explore the experiential and contextual component of user- product interactions. One study employed visuals that the participants produced during the study. The other employed visuals that the researcher used as prompts during a focus group session. This paper demonstrates that using visuals in design research is valuable for exploring and understanding the contextual aspects of human experience and its influence on people’s concepts of product use.

General characteristics of anticipated user experience (AUX) with interactive products

Providing a positive user experience (UX) has become the key differentiator for products to win a competition in mature markets. To ensure that a product will support enjoyable experiences for its users, assessment of UX should be conducted early during the design and development process. However, most UX frameworks and evaluation techniques focus on understanding and assessing user’s experience with functional prototypes or existing products. This situation delays UX assessment until the late phases of product development which may result in costly design modifications and less desirable products. A qualitative study was conducted to investigate anticipated user experience (AUX) to address this issue. Twenty pairs of participants were asked to imagine an interactive product, draw their product concept, and anticipate their interactions and experiences with it. The data was analyzed to identify general characteristics of AUX. We found that while positive AUX was mostly related to an imagined/desired product, negative AUX was mainly associated with existing products. It was evident that the pragmatic quality of product was fundamental, and significantly influenced user’s anticipated experiences. Furthermore, the hedonic quality of product received more focus in positive than negative AUX. The results also showed that context, user profile, experiential knowledge, and anticipated emotion could be reflected in AUX. The understanding of AUX will help product designers to better foresee the users’ underlying needs and to focus on the most important aspects of their positive experiences, which in turn facilitates the designers to ensure pleasurable UX from the start of the design process.

Multi-sensor data fusion for UAV navigation during landing operations

This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

Effective hybrid recommendation combining users-searches correlations using tensors

Most recommendation methods employ item-item similarity measures or use ratings data to generate recommendations. These methods use traditional two dimensional models to find inter relationships between alike users and products. This paper proposes a novel recommendation method using the multi-dimensional model, tensor, to group similar users based on common search behaviour, and then finding associations within such groups for making effective inter group recommendations. Web log data is multi-dimensional data. Unlike vector based methods, tensors have the ability to highly correlate and find latent relationships between such similar instances, consisting of users and searches. Non redundant rules from such associations of user-searches are then used for making recommendations to the users.

Individual user behaviour modelling for effective web recommendation

With the growth of the Web, E-commerce activities are also becoming popular. Product recommendation is an effective way of marketing a product to potential customers. Based on a user’s previous searches, most recommendation methods employ two dimensional models to find relevant items. Such items are then recommended to a user. Further too many irrelevant recommendations worsen the information overload problem for a user. This happens because such models based on vectors and matrices are unable to find the latent relationships that exist between users and searches. Identifying user behaviour is a complex process, and usually involves comparing searches made by him. In most of the cases traditional vector and matrix based methods are used to find prominent features as searched by a user. In this research we employ tensors to find relevant features as searched by users. Such relevant features are then used for making recommendations. Evaluation on real datasets show the effectiveness of such recommendations over vector and matrix based methods.

Identifying interests of web users for effective recommendations

Search log data is multi dimensional data consisting of number of searches of multiple users with many searched parameters. This data can be used to identify a user’s interest in an item or object being searched. Identifying highest interests of a Web user from his search log data is a complex process. Based on a user’s previous searches, most recommendation methods employ two-dimensional models to find relevant items. Such items are then recommended to a user. Two-dimensional data models, when used to mine knowledge from such multi dimensional data may not be able to give good mappings of user and his searches. The major problem with such models is that they are unable to find the latent relationships that exist between different searched dimensions. In this research work, we utilize tensors to model the various searches made by a user. Such high dimensional data model is then used to extract the relationship between various dimensions, and find the prominent searched components. To achieve this, we have used popular tensor decomposition methods like PARAFAC, Tucker and HOSVD. All experiments and evaluation is done on real datasets, which clearly show the effectiveness of tensor models in finding prominent searched components in comparison to other widely used two-dimensional data models. Such top rated searched components are then given as recommendation to users.

Collaboration : developing integration in multi-purpose services in rural New South Wales, Australia

Introduction: The Multi-purpose Service (MPS) Program was introduced to rural Australia in 1991 as a solution to poor health outcomes in rural compared with metropolitan populations, difficulty in attracting healthcare staff and a lack of viability and range of health services in rural areas. The aim of this study was to describe the main concerns of participants involved in the development of multi-purpose services in rural New South Wales (NSW). This article is abstracted from a larger study and discusses the extent to which collaboration occurred within the new multi-purpose service. Methods: A constructivist grounded theory methodology was used. Participants were from 13 multi-purpose services in rural NSW and 30 in-depth interviews were conducted with 6 community members, 11 managers and 13 staff members who had been involved in the process of developing a multi-purpose service. Results: The main concern of all participants was their anticipation of risk. This anticipation of risk manifested itself in either trust or suspicion and explained their progression through a phase of collaborating. Participants who had trust in other stakeholders were more likely to embrace an integrated health service identity. Those participants, who were suspicious that they would lose status or power, maintained that the previous hospital services provided a better health service and described a coexistence of services within the multi-purpose service. Conclusions: This study provided an insight into the perceptions of community members, staff members and managers involved in the process of developing a multi-purpose service. It revealed that the anticipation of risk was intrinsic to a process of changing from a traditional hospital service to collaborating in a new model of health care provided at a multi-purpose service.

Classifying the user intent of web queries using k-means clustering

Purpose: Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, some people may be looking for specific web sites or may wish to conduct transactions with web services. This paper aims to focus on automatically classifying the different user intents behind web queries. Design/methodology/approach: For the research reported in this paper, 130,000 web search engine queries are categorized as informational, navigational, or transactional using a k-means clustering approach based on a variety of query traits. Findings: The research findings show that more than 75 percent of web queries (clustered into eight classifications) are informational in nature, with about 12 percent each for navigational and transactional. Results also show that web queries fall into eight clusters, six primarily informational, and one each of primarily transactional and navigational. Research limitations/implications: This study provides an important contribution to web search literature because it provides information about the goals of searchers and a method for automatically classifying the intents of the user queries. Automatic classification of user intent can lead to improved web search engines by tailoring results to specific user needs. Practical implications: The paper discusses how web search engines can use automatically classified user queries to provide more targeted and relevant results in web searching by implementing a real time classification method as presented in this research. Originality/value: This research investigates a new application of a method for automatically classifying the intent of user queries. There has been limited research to date on automatically classifying the user intent of web queries, even though the pay-off for web search engines can be quite beneficial. © Emerald Group Publishing Limited.

A task-oriented approach to search engine usability studies

Usability is a multi-dimensional characteristic of a computer system. This paper focuses on usability as a measurement of interaction between the user and the system. The research employs a task-oriented approach to evaluate the usability of a meta search engine. This engine encourages and accepts queries of unlimited size expressed in natural language. A variety of conventional metrics developed by academic and industrial research, including ISO standards,, are applied to the information retrieval process consisting of sequential tasks. Tasks range from formulating (long) queries to interpreting and retaining search results. Results of the evaluation and analysis of the operation log indicate that obtaining advanced search engine results can be accomplished simultaneously with enhancing the usability of the interactive process. In conclusion, we discuss implications for interactive information retrieval system design and directions for future usability research. © 2008 Academy Publisher.