K-H Wolf1, K Hetzer, H M zu Schwabedissen, B Wiese, M Marschollek. 1. Peter L. Reichertz Institute for Medical Informatics University of Braunschweig - Institute of Technology and Hannover Medical School, Mühlenpfordtstr. 23, 38106, Braunschweig, Germany, Klaus-Hendrik.Wolf@plri.de.
Abstract
BACKGROUND: Falls are a major problem in hospitals and nursing homes. The consequences of falls can be severe, both for the individual and for the caring institution. OBJECTIVE: The aim of the work presented here is to reduce the number of falls on a geriatric ward by monitoring patients more closely. To achieve this goal, a bed-exit alarm that reliably detects an attempt to get up has been constructed. MATERIALS AND METHODS: A requirements analysis revealed the nurses' and physicians' needs and preferences. Based on the gathered information, an incremental design process generated different prototypes. These were tested for the reliability of their ability to detect attempts to get up in both laboratory settings and with geriatric patients. Based on the result of these tests, a scalable technical solution has been developed and proven its reliability in a 1-year, randomized controlled pilot clinical trial on a geriatric ward. RESULTS: The developed system is unobtrusive and easy to deploy. It has been tested in laboratory settings, usability tests and a 1-year randomized clinical trial with 98 patients. This paper focuses on the technical development of the system. We present different prototypes, the experiments and the pilot study used to evaluate their performance. Last but not least, we discuss the lessons learned so far. CONCLUSION: The developed bed-exit alarm is able to reliably detect patients' attempts to get up. The results of the clinical trial show that the system is able to reduce the number of falls on a geriatric ward. Next steps are the design of a specialized sensor node that is easier to use and can be applied on an even larger scale due to its reduced cost. A multicenter trial with a larger number of patients is required to confirm the results of this pilot study.
RCT Entities:
BACKGROUND: Falls are a major problem in hospitals and nursing homes. The consequences of falls can be severe, both for the individual and for the caring institution. OBJECTIVE: The aim of the work presented here is to reduce the number of falls on a geriatric ward by monitoring patients more closely. To achieve this goal, a bed-exit alarm that reliably detects an attempt to get up has been constructed. MATERIALS AND METHODS: A requirements analysis revealed the nurses' and physicians' needs and preferences. Based on the gathered information, an incremental design process generated different prototypes. These were tested for the reliability of their ability to detect attempts to get up in both laboratory settings and with geriatric patients. Based on the result of these tests, a scalable technical solution has been developed and proven its reliability in a 1-year, randomized controlled pilot clinical trial on a geriatric ward. RESULTS: The developed system is unobtrusive and easy to deploy. It has been tested in laboratory settings, usability tests and a 1-year randomized clinical trial with 98 patients. This paper focuses on the technical development of the system. We present different prototypes, the experiments and the pilot study used to evaluate their performance. Last but not least, we discuss the lessons learned so far. CONCLUSION: The developed bed-exit alarm is able to reliably detect patients' attempts to get up. The results of the clinical trial show that the system is able to reduce the number of falls on a geriatric ward. Next steps are the design of a specialized sensor node that is easier to use and can be applied on an even larger scale due to its reduced cost. A multicenter trial with a larger number of patients is required to confirm the results of this pilot study.
Authors: Anna M Sawka; Pauline Boulos; Karen Beattie; Alexandra Papaioannou; Amiram Gafni; Ann Cranney; David A Hanley; Jonathan D Adachi; E A Papadimitropoulos; Lehana Thabane Journal: J Clin Epidemiol Date: 2006-10-23 Impact factor: 6.437
Authors: Vincent T van Hees; Lukas Gorzelniak; Emmanuel Carlos Dean León; Martin Eder; Marcelo Pias; Salman Taherian; Ulf Ekelund; Frida Renström; Paul W Franks; Alexander Horsch; Søren Brage Journal: PLoS One Date: 2013-04-23 Impact factor: 3.240
Authors: Ian D Cameron; Suzanne M Dyer; Claire E Panagoda; Geoffrey R Murray; Keith D Hill; Robert G Cumming; Ngaire Kerse Journal: Cochrane Database Syst Rev Date: 2018-09-07
Authors: Meg E Morris; Kate Webster; Cathy Jones; Anne-Marie Hill; Terry Haines; Steven McPhail; Debra Kiegaldie; Susan Slade; Dana Jazayeri; Hazel Heng; Ronald Shorr; Leeanne Carey; Anna Barker; Ian Cameron Journal: Age Ageing Date: 2022-05-01 Impact factor: 12.782
Authors: Roberto Luis Shinmoto Torres; Renuka Visvanathan; Stephen Hoskins; Anton van den Hengel; Damith C Ranasinghe Journal: Sensors (Basel) Date: 2016-04-15 Impact factor: 3.576
Authors: Sandra M Eldridge; Gillian A Lancaster; Michael J Campbell; Lehana Thabane; Sally Hopewell; Claire L Coleman; Christine M Bond Journal: PLoS One Date: 2016-03-15 Impact factor: 3.240