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Proceedings of the Eighth Annual Conference, International Society for Disease
Surveillance, 2009, 2009-12-04
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Preferred workflows for syndromic surveillance systems
Guthrie, Glenn; Vinson, Norman G.; Moore, Kieran
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Preferred Workflows for Syndromic Surveillance Systems
1Glenn Guthrie MSc
2, Norman G. Vinson PhD
3, Kieran Moore MD
22
KFL&A Public Health, Kingston, Ontario, Canada
3
National Research Council, Canada, Institute for Information Technology, Ottawa, Ontario,
Canada
1
This work was supported by CRTI (Chemical, Biological, Radiological-Nuclear, and Explosives (CBRNE) Research and Technology Initiative) grant #06-0234TA
OBJECTIVE
Workflows are a sequence of information processing operations that people carry out to meet certain in-formational goals [1]. Using various user-centered design (UCD) techniques we uncovered the workflows that epidemiologists wished to follow when using syndromic surveillance (SS) systems.
BACKGROUND
We studied four Canadian SS system installations that are intended to detect disease outbreaks as early as possible. Their main data source, and the focus of our investigation, is emergency department (ED) visit chief complaints obtained from triage nurse data en-try. ED chief complaints are the most common data source for SS systems in the US [2].
The systems we examined commonly offer different views of the data: maps, graphs, alerts, and case list-ings.
METHODS
Our analysis follows a user-centered design (UCD) approach, which prioritizes the users’ needs and work practices in the system design process [3]. We col-lected data through standard UCD techniques [1,3]: epidemiologist consultations and interviews, observa-tion of the epidemiologists as they interacted with the systems, and iterative user interface prototyping ses-sions. For the work presented here, we focused on uncovering the workflows the epidemiologists wished to follow in examining and analyzing SS data, and on determining the extent to which their current SS sys-tems supported these preferred workflows.
RESULTS
We identified three different investigation strategies that epidemiologists would like to apply when inter-acting with their SS systems: 1) assessing case listing similarities, 2) analyzing geographical hotspots, and, 3) using data filters to generate disease incidence epi-curves.
For each strategy, we elaborated a preferred workflow representing the information processing steps epidemiologists would like to follow when ap-plying the strategy.
Epidemiologists would choose a particular preferred workflow as a function of their experience, the amount of time available for reviewing the data and alerts in the system, the volume of cases, and the par-ticular health threat they were investigating. The workflows are not mutually exclusive and one workflow can lead into another.
We observed that the SS systems the epidemiologists were currently using did not provide the requisite user functions for them to follow all the steps in the preferred workflows. This typically resulted in the epidemiologists extracting the data from the SS sys-tems and analyzing it with other software, and re-duced productivity.
CONCLUSIONS
The preferred workflows we have documented are an embodiment of user requirements. As such they can be used to design SS systems that better meet the needs of epidemiologists and better support them in their SS activities.
We are currently building a functional user prototype SS system based on these preferred workflows. Sub-mitting this prototype to user testing by epidemiolo-gists, will allow us to further refine the preferred workflows.
REFERENCES
[1] Unertl, K.M., Weinger, M.B., & Johnson, K.B. Applying Direct Observation to Model Workflow and Assess Adoption. AMIA Annu Symp Proc. 2006; 2006: 794–798.
[2] Buehler, J.W., Sonricker, A., Paladini, M., Soper, M. & Mostashari, F. Syndromic Surveillance Prac-tice in the United States: Findings from a Survey of State, Territorial, and Selected Local Health Depart-ments. Advances in Disease Surveillance, 2008; 6(3)
2 [3] Beyer, H., & Holtzblatt, K. Contextual design: Defining customer-centered systems. San Francisco, CA, 1998.
