Visualising Emergency Department Wait Times; Rapid Iterative Testing to Determine Patient Preferences for Displays

Author:

Walker KatieORCID,Potter EdenORCID,Hwang Indae,Dwyer TimORCID,Egerton-Warburton DianaORCID,Joe KeithORCID,Hutton JennieORCID,Freeman Sam,Flynn DaphneORCID

Abstract

AbstractVisualising patient wait times in emergency departments for patients and families is increasingly common, following the development of prediction models using routinely collected patient demographic, urgency and flow data. Consumers of an emergency department wait time display will have culturally and linguistically diverse backgrounds, are more likely to be from under-served populations and will have varied data literacy skills. The wait times are uncertain, the information is presented when people are emotionally and physically challenged, and the predictions may inform high stakes decisions. In such a stressful environment, simplicity is crucial and the visual language must cater to the diverse audience. When wait times are conveyed well, patient experience improves. Designers must ensure the visualisation is patient-centred and that data are consistently and correctly interpreted. In this article, we present the results of a design study at three hospitals in Melbourne, Australia, undertaken in 2021. We used rapid iterative testing and evaluation methodology, with patients and families from diverse backgrounds as participants, to develop and validate a wait time display. We present the design process and the results of this project. Patients, families and staff were eligible to participate if they were awaiting care in the emergency department, or worked in patient reception and waiting areas. The patient-centred approach taken in our design process varies greatly from past work led by hospital administrations, and the resulting visualisations are very distinct. Most currently displayed wait time visualisations could be adapted to better meet end-user needs. Also of note, we found that techniques developed by visualisation researchers for conveying temporal uncertainty tended to overwhelm the diverse audience rather than inform. There is a need to balance precise and comprehensive information presentation against the strong need for simplicity in such a stressful environment.

Publisher

Cold Spring Harbor Laboratory

Reference45 articles.

1. Personal data visualisation on mobile devices: A systematic literature review;arXiv preprint,2022

2. Accurate emergency department wait time prediction;Manufacturing & Service Operations Management,2016

3. Australasian College for Emergency Medicine, Department of Policy, Research and Advocacy. Aboriginal and torres strait islander and nonindigenous presentations to australian emergency departments aihw 2014-15, 2018. Online; accessed 23rd March 2022.

4. Australian Institute of Health and Welfare. Emergency department care 2017-18: Australian hospital statistics. Technical report, Australian Government, 2019.

5. M. Bancilhon , Z. Liu , and A. Ottley . Let’s gamble: How a poor visualization can elicit risky behavior. In 2020 IEEE Visualization Conference (VIS), pp. 196–200. IEEE, 2020.

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