Ruth Chu-Ai Teh1, Neha Mahajan, Renuka Visvanathan, Anne Wilson. 1. 1School of Medicine, University of Adelaide 2Adelaide Geriatrics Training and Research with Aged Care (GRAC) 3Paramedic Unit, School of Medicine, Flinders University, Bedford Park, South Australia 4Prince of Wales Clinical School, School of Medicine, University of New South Wales, Sydney, New South Wales, Australia.
Abstract
AIMS: To analyse the evidence on the effectiveness, usability and acceptability of health technology in falls detection and prevention among older adults. METHODS: Five databases were searched from February 2004 to February 2014: PubMed, Medline, Embase, Cochrane and CINAHL, with reference lists reviewed and researchers contacted for additional articles. The interventions were health technology tools used for falls detection and prevention (e.g. computers, mobile phones, motion sensors). The outcomes were effectiveness of, and the attitudes of healthcare staff towards, health technology in preventing falls. Two review authors independently assessed full texts using modified versions of the Joanna Briggs Institute Critical Appraisal Checklists. RESULTS: Full-texts of 51 out of 7927 articles were examined and 17 articles accepted following appraisal using Joanna Briggs Institute modified criteria. These were divided into subheadings of health information technology tool with visual cues (n = 2), sensors (n = 4), Webcam (n = 1) and electronic medical records (n = 3). Three of the seven systematic reviews evaluated sensor technology alone, whereas the remainder examined multicomponent interventions. There is a lack of research into the efficacy of and staff attitudes towards health technology in falls detection and prevention. One study found nurses accepted a health information technology toolkit with visual cues, with a single randomized controlled trial demonstrating a reduction in falls rates. Most studies regarding sensor technology were of low quality and did not find reduced falls rates or number of falls-related injuries. There was also mixed response from healthcare staff and users regarding the use of sensors, with concerns about privacy and false alarms. Video camera surveillance effectively reduced falls rates and was well accepted by nursing staff. However, patients had concerns for their privacy. Electronic medical records have not so far demonstrated a reduction in falls, with ongoing staff concerns about their usability. CONCLUSION: Good-quality literature regarding the effectiveness and acceptability of health technology in falls detection and prevention is lacking. Further research into both these fields is vital prior to wider implementation of such tools in clinical practice.
AIMS: To analyse the evidence on the effectiveness, usability and acceptability of health technology in falls detection and prevention among older adults. METHODS: Five databases were searched from February 2004 to February 2014: PubMed, Medline, Embase, Cochrane and CINAHL, with reference lists reviewed and researchers contacted for additional articles. The interventions were health technology tools used for falls detection and prevention (e.g. computers, mobile phones, motion sensors). The outcomes were effectiveness of, and the attitudes of healthcare staff towards, health technology in preventing falls. Two review authors independently assessed full texts using modified versions of the Joanna Briggs Institute Critical Appraisal Checklists. RESULTS: Full-texts of 51 out of 7927 articles were examined and 17 articles accepted following appraisal using Joanna Briggs Institute modified criteria. These were divided into subheadings of health information technology tool with visual cues (n = 2), sensors (n = 4), Webcam (n = 1) and electronic medical records (n = 3). Three of the seven systematic reviews evaluated sensor technology alone, whereas the remainder examined multicomponent interventions. There is a lack of research into the efficacy of and staff attitudes towards health technology in falls detection and prevention. One study found nurses accepted a health information technology toolkit with visual cues, with a single randomized controlled trial demonstrating a reduction in falls rates. Most studies regarding sensor technology were of low quality and did not find reduced falls rates or number of falls-related injuries. There was also mixed response from healthcare staff and users regarding the use of sensors, with concerns about privacy and false alarms. Video camera surveillance effectively reduced falls rates and was well accepted by nursing staff. However, patients had concerns for their privacy. Electronic medical records have not so far demonstrated a reduction in falls, with ongoing staff concerns about their usability. CONCLUSION: Good-quality literature regarding the effectiveness and acceptability of health technology in falls detection and prevention is lacking. Further research into both these fields is vital prior to wider implementation of such tools in clinical practice.
Authors: Patricia C Dykes; Srijesa Khasnabish; Zoe Burns; Lesley E Adkison; Lois Alfieri; Michael Bogaisky; Diane L Carroll; Eileen J Carter; Ann C Hurley; Emily Jackson; Susan Kurian; Mary Ellen Lindros; Virginia Ryan; Maureen Scanlan; Kelly Sessler; Alexandra Shelley; Linda B Spivack; Mary-Ann Walsh; David W Bates; Jason S Adelman Journal: J Patient Saf Date: 2022-03-01 Impact factor: 2.243