Effectiveness of the Wearable Sensor-based Ambient Intelligent Geriatric Management (AmbIGeM) System in Preventing Falls in Older People in Hospitals

Renuka Visvanathan; Damith C Ranasinghe; Kylie Lange; Anne Wilson; Joanne Dollard; Eileen Boyle; Katherine Jones; Michael Chesser; Katharine Ingram; Stephen Hoskins; Clarabelle Pham; Jonathan Karnon; Keith D Hill

doi:10.1093/gerona/glab174

Effectiveness of the Wearable Sensor-based Ambient Intelligent Geriatric Management (AmbIGeM) System in Preventing Falls in Older People in Hospitals

J Gerontol A Biol Sci Med Sci. 2022 Jan 7;77(1):155-163. doi: 10.1093/gerona/glab174.

Authors

Renuka Visvanathan^{1

2}, Damith C Ranasinghe³, Kylie Lange⁴, Anne Wilson^{1

5}, Joanne Dollard¹, Eileen Boyle⁶, Katherine Jones⁶, Michael Chesser³, Katharine Ingram⁷, Stephen Hoskins², Clarabelle Pham⁸, Jonathan Karnon⁸, Keith D Hill^{6

9}

Affiliations

¹ Adelaide Geriatrics Training and Research with Aged Care (GTRAC) Centre, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Woodville South, South Australia, Australia.
² Aged & Extended Care Services, The Queen Elizabeth Hospital, Central Adelaide Local Health Network, Woodville South, South Australia, Australia.
³ School of Computer Science, University of Adelaide, South Australia, Australia.
⁴ Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, North Terrace, South Australia, Australia.
⁵ School of Medicine, Flinders University, Bedford Park, Australia.
⁶ School of Physiotherapy and Exercise Science, Curtin University, Perth, Western Australia, Australia.
⁷ Department of Rehabilitation and Aged Care, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.
⁸ Flinders Health and Medical Research Institute, Flinders University, Adelaide, South Australia, Australia.
⁹ Rehabilitation, Ageing and Independent Living (RAIL) Research Centre, Monash University, Melbourne, Victoria, Australia.

Abstract

Background: The Ambient Intelligent Geriatric Management (AmbIGeM) system augments best practice and involves a novel wearable sensor (accelerometer and gyroscope) worn by patients where the data captured by the sensor are interpreted by algorithms to trigger alerts on clinician handheld mobile devices when risk movements are detected.

Methods: A 3-cluster stepped-wedge pragmatic trial investigating the effect on the primary outcome of falls rate and secondary outcome of injurious fall and proportion of fallers. Three wards across 2 states were included. Patients aged ≥65 years were eligible. Patients requiring palliative care were excluded. The trial was registered with the Australia and New Zealand Clinical Trials registry, number 12617000981325.

Results: A total of 4924 older patients were admitted to the study wards with 1076 excluded and 3240 (1995 control, 1245 intervention) enrolled. The median proportion of study duration with valid readings per patient was 49% ((interquartile range [IQR] 25%-67%)). There was no significant difference between intervention and control relating to the falls rate (adjusted rate ratio = 1.41, 95% confidence interval [0.85, 2.34]; p = .192), proportion of fallers (odds ratio = 1.54, 95% confidence interval [0.91, 2.61]; p = .105), and injurious falls rate (adjusted rate ratio = 0.90, 95% confidence interval [0.38, 2.14]; p = .807). In a post hoc analysis, falls and injurious falls rate were reduced in the Geriatric Evaluation and Management Unit wards when the intervention period was compared to the control period.

Conclusions: The AmbIGeM system did not reduce the rate of falls, rate of injurious falls, or proportion of fallers. There remains a case for further exploration and refinement of this technology given the post hoc analysis findings with the Geriatric Evaluation and Management Unit wards. Clinical Trials Registration Number: 12617000981325.

Keywords: Hospital related; Morbidity; Preventative health care.

Publication types

Pragmatic Clinical Trial
Research Support, Non-U.S. Gov't

MeSH terms

Aged
Australia
Hospitalization
Hospitals*
Humans
Wearable Electronic Devices*