Evaluating the deployment of a mobile technology in a hospital ward
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Activity recognition from accelerometer data
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
AndWellness: an open mobile system for activity and experience sampling
WH '10 Wireless Health 2010
Mobile context inference using low-cost sensors
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
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Before Electronic Health Records (EHRs) were available on touch-panel tablets, doctors were confined to accessing the records on their hospital's computer stations, in their offices or at nurse stations. We deployed Dr. Pad, a mobile EHR application on the iPad, to resident doctors at the Taipei Veterans General Hospital in Taipei, Taiwan. We are able to extract direct usage and motion data from a large-scale in-the-wild use of a mobile EHR by 179 resident doctors over 4 weeks. Using machine-learning techniques, we can predict the doctors' mobile behaviors while using Dr. Pad, which were previously unobserved and mainly self-reported. Our data revealed trends in the doctors' use of the mobile EHR, which supported claims by doctors on their usage habits, our observations of their work routines, and even showed that the doctors used Dr. Pad more frequently than we had expected.