Integrating WiFi Based Positioning With A Job Management System to Study Task Management Behaviour

J. Pinchin, M. Brown, J. Blum, D. Shaw, J. Blakey

Abstract: Focus groups, interviews and anecdotal evidence suggest that senior clinicians are better than their juniors at man-aging their task load when working ‘out of hours’ in hospitals. For example experience allows them to prioritise cases which are likely to degrade and to organize their time to account for personal needs such as rest and refreshment. Quantifying this behaviour, and the variations between staff groups, is a complex task. Traditional direct observation and self-report methods are very intrusive, expensive and lack both scalability and validity. In this work we propose the use of positioning technology to augment or replace these traditional methods. We integrate contextual in formation from a digital task management system with location in formation to obtain a temporally ordered list of completed tasks with associated timings. The positioning system described in this work is based upon observations of visible WiFi access points. As the clinician moves between wards the set of visible access points changes and can be used to infer location. We propose a method by which access points can be associated with a discrete set of locations. This method removes the need for an expensive, intrusive ‘ground survey’ and is mindful of user privacy by only providing location with in the pre-defined set. This paper describes the structure of the problem and a method for the integration of contextual and WiFi visibility data. Exemplar results are given from a limited scale trial performed in a large UK teaching hospital. The novel application of positioning technology to the study of clinical work place behavior offers opportunities to drive efficiencies, enhance staff training and hence improve patient safety.
Published in: Proceedings of IEEE/ION PLANS 2014
May 5 - 8, 2014
Hyatt Regency Hotel
Monterey, CA
Pages: 193 - 200
Cite this article: Pinchin, J., Brown, M., Blum, J., Shaw, D., Blakey, J., "Integrating WiFi Based Positioning With A Job Management System to Study Task Management Behaviour," Proceedings of IEEE/ION PLANS 2014, Monterey, CA, May 2014, pp. 193-200.
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