@article{ref1,
title="Automated fall detection technology in inpatient geriatric psychiatry: nurses' perceptions and lessons learned",
journal="Canadian journal on aging",
year="2018",
author="Coahran, Marge and Hillier, Loretta M. and Van Bussel, Lisa and Black, Edward and Churchyard, Rebekah and Gutmanis, Iris and Ioannou, Yani and Michael, Kathleen and Ross, Tom and Mihailidis, Alex",
volume="37",
number="3",
pages="245-260",
abstract="ABSTRACTHospitalized older adults are at high risk of falling. The HELPER system is a ceiling-mounted fall detection system that sends an alert to a smartphone when a fall is detected. This article describes the performance of the HELPER system, which was pilot tested in a geriatric mental health hospital. The system's accuracy in detecting falls was measured against the hospital records documenting falls. Following the pilot test, nurses were interviewed regarding their perceptions of this technology. In this study, the HELPER system missed one documented fall but detected four falls that were not documented. Although sensitivity (.80) of the system was high, numerous false alarms brought down positive predictive value (.01). Interviews with nurses provided valuable insights based on the operation of the technology in a real environment; these and other lessons learned will be particularly valuable to engineers developing this and other health and social care technologies.<p /> <p>Language: en</p>",
language="en",
issn="0714-9808",
doi="10.1017/S0714980818000181",
url="http://dx.doi.org/10.1017/S0714980818000181"
}