Skip to Main content Skip to Navigation
Journal articles

Dealing with uncertainty when using a surveillance system

Abstract : Introduction: Epidemiologists manage outbreak identification and confirmation by means of a ``situation diagnosis'', which involves validating (or invalidating) an alarm (signal identified as abnormal) as an alert (a real, characterized outbreak) and proposing the first countermeasures. This work investigates how uncertainty is materialized during this stage, and how experts develop strategies to address this uncertainty with the help of an early warning system. Methods: We built an experiment using a simulation platform with a scenario involving both a natural and an intentional outbreak. Observations of expert activities were recorded and formalised using a specific task analysis method. These formatted data were then categorized by applying RAWFS (Reduction-Assumption Weighing -Forestalling-Suppression) heuristics. Results: We quantified uncertainty and the mechanisms involved. During the situation diagnosis, two sorts of uncertainty were characterized: practice-imposed uncertainty and situation-imposed uncertainty. We did not find either weighing pros and cons or suppression strategies in this area of expertise, but highlight the predominance of coping strategies that relied on reduction (66,4%) and assumption-based reasoning. We observed a predominance of the phone (89%) to cope with uncertainty and among electronic tools, the surveillance system plays a major role (69% of cases) and is mainly used in reduction strategies. We detail tools and systems used to support experts in their coping strategy. Conclusion: We confirmed that a surveillance system must include different features that provide relevant information to help users reduce uncertainty and thus support their decision making. In that perspective, the flow diagram and proposal presented in this study can help prioritize the necessary changes to surveillance system design.
Document type :
Journal articles
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-01573752
Contributor : Isabelle Combe <>
Submitted on : Thursday, August 10, 2017 - 3:15:27 PM
Last modification on : Friday, February 26, 2021 - 12:24:01 PM

Identifiers

Citation

Gaëtan Texier, Liliane Pellegrin, Claire Vignal, Jean-Baptiste Meynard, Xavier Deparis, et al.. Dealing with uncertainty when using a surveillance system. International Journal of Medical Informatics, Elsevier, 2017, 104, pp.65-73. ⟨10.1016/j.ijmedinf.2017.05.006⟩. ⟨hal-01573752⟩

Share

Metrics

Record views

196