Skip to main content

Research Repository

Advanced Search

Health technologies for the prevention and detection of falls in adult hospital inpatients: a scoping review.

Cooper, Kay; Pavlova, Anastasia; Greig, Leon; Swinton, Paul; Kirkpatrick, Pamela; Mitchelhill, Fiona; Simpson, Susan; Stephen, Audrey; Alexander, Lyndsay

Authors

Pamela Kirkpatrick

Fiona Mitchelhill

Susan Simpson

Audrey Stephen



Abstract

Objective:The objective of this scoping review was to examine and map the evidence relating to the reporting and evaluation of technologies for the prevention and detection of falls in adult hospital inpatients.Introduction:Falls are a common cause of accidental injury, leading to significant safety issues in hospitals globally, and resulting in substantial human and economic costs. Previous research has focused on community settings with less emphasis on hospital settings.Inclusion criteria:Participants included adult inpatients, aged 18 years and over; the concept included the use of fall-prevention or fall-detection technologies; the context included any hospital ward setting.Methods:This scoping review was conducted according to JBI methodology for scoping reviews, guided by an a priori protocol. A wide selection of databases including MEDLINE, CINAHL, AMED, Embase, PEDro, Epistimonikos, and Science Direct were searched for records from inception to October 2019. Other sources included gray literature, trial registers, government health department websites, and websites of professional bodies. Only studies in the English language were included. A three-step search strategy was employed, with all records exported for subsequent title and abstract screening prior to full-text screening. Screening was performed by two independent reviewers and data extraction by one reviewer following agreement checks. Data are presented in narrative and tabular form.Results:Over 13,000 records were identified with 404 included in the scoping review: 336 reported on fall-prevention technologies, 51 targeted detection, and 17 concerned both. The largest contributions of studies came from the USA (n=185), Australia (n=65), the UK (n=36), and Canada (n=18). There was a variety of study designs including 77 prospective cohort studies, 33 before-after studies, and 35 systematic reviews; however, relatively few randomized controlled trials were conducted (n = 25). The majority of records reported on multifactorial and multicomponent technologies (n = 178), followed by fall detection devices (n = 86). Few studies reported on the following interventions in isolation: fall risk assessment (n = 6), environment design (n = 8), sitters (n = 5), rounding (n = 3), exercise (n = 3), medical/pharmaceutical (n = 2), physiotherapy (n = 1), and nutritional (n = 1). The majority (57%) of studies reported clinical effectiveness outcomes, with smaller numbers (14%) reporting feasibility and/or acceptability outcomes, or cost-effectiveness outcomes (5%).Conclusions:This review has mapped the literature on fall-prevention and fall-detection technology and outcomes for adults in the hospital setting. Despite the volume of available literature, there remains a need for further high-quality research on fall-prevention and fall-detection technologies.

Citation

COOPER, K., PAVLOVA, A., GREIG, L., SWINTON, P., KIRKPATRICK, P., MITCHELHILL, F., SIMPSON, S., STEPHEN, A. and ALEXANDER, L. 2021. Health technologies for the prevention and detection of falls in adult hospital inpatients: a scoping review. JBI evidence synthesis [online], 19(10), pages 2478-2658. Available from: https://doi.org/10.11124/JBIES-20-00114

Journal Article Type Review
Acceptance Date Dec 15, 2020
Online Publication Date Jun 18, 2021
Publication Date Oct 31, 2021
Deposit Date Dec 15, 2020
Publicly Available Date Jun 19, 2022
Journal JBI evidence synthesis
Print ISSN 2689-8381
Publisher Lippincott, Williams & Wilkins
Peer Reviewed Peer Reviewed
Volume 19
Issue 10
Pages 2478-2658
DOI https://doi.org/10.11124/JBIES-20-00114
Keywords Accidental falls; Health technologies; Hospital patients; Fall detection; Fall prevention
Public URL https://rgu-repository.worktribe.com/output/1010410