Designing effective visualizations of habits data to aid clinical decision making

BMC Medical Informatics and Decision Making

Research Article

Joost de Folter¹  Hulya Gokalp¹  Malcolm Clarke¹  Urvashi Sharma¹  Joanna Fursse² 

[1]Brunel University, UB8 3PH, Uxbridge, UK

[2]Chorleywood Health Centre, 15 Lower Rd, WD3 5EA, Chorleywood, Rickmansworth, UK

关键词: Visualization;    Decision making;    User centered design;    Habits data;    Feature extraction;   

DOI  :  10.1186/s12911-014-0102-x

 received in 2014-04-25, accepted in 2014-10-29,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundChanges in daily habits can provide important information regarding the overall health status of an individual. This research aimed to determine how meaningful information may be extracted from limited sensor data and transformed to provide clear visualization for the clinicians who must use and interact with the data and make judgments on the condition of patients. We ascertained that a number of insightful features related to habits and physical condition could be determined from usage and motion sensor data.MethodsOur approach to the design of the visualization follows User Centered Design, specifically, defining requirements, designing corresponding visualizations and finally evaluating results. This cycle was iterated three times.ResultsThe User Centered Design method was successfully employed to converge to a design that met the main objective of this study. The resulting visualizations of relevant features that were extracted from the sensor data were considered highly effective and intuitive to the clinicians and were considered suitable for monitoring the behavior patterns of patients.ConclusionsWe observed important differences in the approach and attitude of the researchers and clinicians. Whereas the researchers would prefer to have as many features and information as possible in each visualization, the clinicians would prefer clarity and simplicity, often each visualization having only a single feature, with several visualizations per page. In addition, concepts considered intuitive to the researchers were not always to the clinicians.

【 授权许可】

Unknown   
© de Folter et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.