Collaborative Activities During an Outbreak Early Warning Assisted by a Decision-Supported System (ASTER)

Pellegrin, Liliane; Gaudin, Charlotte; Bonnardel, Nathalie; Chaudet, Hervé

doi:10.1080/10447310903499062

Cited by 7 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Observations were manually recorded by two ergonomists applying the EORCA method (Pellegrin et al 2007(Pellegrin et al , 2010a). This is a task-analysis tool for observing and modelling collective medical activities.…”

Section: Methods For Observation and Analysismentioning

confidence: 99%

Collective activities in a technology-mediated medical team. An analysis of epidemiological alert management

Gaudin

Bonnardel

Pellegrin

et al. 2012

Behaviour & Information Technology

View full text Add to dashboard Cite

We conducted an exploratory study of a complex and dynamic medical activity, namely the collective management of an epidemiological alert situation. With a view to improving our knowledge of how this activity is managed, we set up simulated situations of epidemiological alerts. A multidisciplinary medical team was assisted by a decisionsupport system called ASTER and we recorded a set of systematised observations of human-human and humanmachine interactions. Participants were physicians belonging to the Department of Epidemiology at the French Army's Institute of Tropical Medicine. After presenting the epidemiological domain and our theoretical approach, we describe the simulated situation and the communication dataset we collected and analysed, applying the EORCA method. Finally, in our discussion of the results, we suggest how communication could be enhanced between technology-mediated teams in complex and dynamic situations.

show abstract

Section: Methods For Observation and Analysismentioning

confidence: 99%

Collective activities in a technology-mediated medical team. An analysis of epidemiological alert management

Gaudin

Bonnardel

Pellegrin

et al. 2012

Behaviour & Information Technology

View full text Add to dashboard Cite

show abstract

“…While support for map-based interaction exists, and is often integrated with data collection and epidemiological modelling [22,17], collaboration support in these systems is mostly restricted to asynchronous interaction or individual data presentation. The nu-case system [17], for instance, introduced a unified platform to support data collection by epidemiologists and local fieldworkers working in remote regions.…”

Section: Analysis Of Disease Spreadmentioning

confidence: 99%

nu-view

Masoodian

Luz

Kavenga

2016

Proceedings of the Australasian Computer Science Week Multiconference

View full text Add to dashboard Cite

In general, many factors contribute to the spread of diseases among populations over large geographical areas. In practice, analysis of these factors typically requires expertise of multidisciplinary teams. In this paper, we present a visualization system which aims to support the visual analytics process involving multidisciplinary teams of analysts in colocated collaborative settings. The current prototype system allows coupled and decoupled modes of interaction, using a combination of personal visualizations on private small displays and group visualizations on a shared large display. We have conducted preliminary fieldwork and a review study of this prototype with a group of medical experts who have provided feedback on the current system and suggestions for other usage scenarios, as well as further improvements. We found that our target user group have a generally positive attitude towards the use of a shared display with support for the suggested interaction modes, even though these modes are substantially different from the way their groups currently conduct synchronous collaboration, and that additional support for sharing image and textual data over the geospatial data layer may be required.

show abstract