Liliane Pellegrin

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

This article introduces the resolution of a medical complex, uncertain, and time-constraint situation: the outbreak early warning in military deployment, which is assisted by a decision-supported system, ASTER, an application developed for early epidemiological alerting for French army forces. A simulated alarm occurring in the Department of Epidemiology in the Institute of Tropical Medicine of the French Forces, managed by physicians belonging to this department, has been studied. One goal was to have a set of systematized observations on the human–system interactions in a constrained and critical situation implying a team of public health experts. The ASTER system and a first study of its usage by experts in a simulated situation are presented, and the first results obtained in the context of the insertion of a complex human–computerized system interaction in a naturalistic situation of decision making are discussed.

Assessment of a military real-time epidemiological surveillance system by its users in French Guiana

In October 2004, a real-time surveillance system prototype was established for the armed forces in French Guiana; the ‘2SE FAG’ system (Surveillance Spatiale des Epidemies au sein des Forces Armees en Guyane). This is composed of a recording network and an analytical network (Fig. 1). In the recording network, all military physicians and nurses have been equipped with information technology tools to allow them to record, in real time, information about military patients presenting with fever, in a clinical form in dedicated software. This is forwarded to an analysis centre as soon as possible using telephone or satellite. The analytical network is based in both French Guiana (Cayenne) and mainland France (Marseilles). It is a secure and private network, and data are integrated within a geographical information system and an MySQL database. Statistical analysis is automatic and uses the exponentially weighted moving average and the current past experience

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

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 decision-support system called ASTER and we recorded a set of systematised observations of human–human and human–machine interactions. Participants were physicians belonging to the Department of Epidemiology at the French Armys 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.

EORCA: a collaborative activities representation for building guidelines from field observations

In the objective of building care team guidelines from field observations, this paper introduces a representation method for describing the medical collaborative activities during an ICU patient management. An event-centered representation of medical activities is built during a 3-step procedure, successively involving an event-centered observation phase, an action extraction and coding phase, and an event and collaborative representation phase. This method has been used for analyzing the management of 24 cases of neurological and multiple traumas. We have represented the different actions of the medical team members (clinicians, nurses and outside medical consultants), underlining collaborative information management and the strong interaction between information management and medical actions. This method also highlights the difficulty of cases management linked to diagnosis severity, complexity of the situation and time constraints.

Near real-time outbreak surveillance system for early warning as a JCS

Motivation -- This presentation introduces a near-real time outbreak surveillance system, ASTER, which assists physicians in the resolution the management of the outbreak early warning in French military deployment. Research approach. Our approach is to show that ASTER could be described as a joint cognitive system between actors belonging to a specific socio-technical network, a surveillance network and an artificial decision-supported system. Findings/Design -- Two simulations of an outbreak management have been set up. Observations of epidemiologists (analysis network) were conducted during simulated scenarii involving natural and intentional outbreaks within French Forces deployed for the first scenario, in Djibouti, and for the second one, in Tchad. Originality/Value -- The results of these studies highlight the central role of the building of a shared problem representation. This representation appears mainly to result from cooperative activities during decision making processes which are strongly supported by the main system, ASTER, but also by a panel of other decision-support systems and non-computerized and more classical artefacts.