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

Visvanathan, Renuka; Ranasinghe, Damith C.; Lange, Kylie; Wilson, Anne; Dollard, Joanne; Boyle, Eileen M.; Jones, Katherine R.; Chesser, Michael; Ingram, Katharine; Hoskins, Stephen L.; Karnon, Jonathan; Pham, Clarebelle

doi:10.2139/ssrn.3705278

“…Fifteen of the included studies in the systematic review had a non-randomised design [ 36 , 37 , 39 , 41 , 42 , 51 , 54 , 58 , 60–62 , 64 , 65 , 67 , 69 ]. Supplementary Table 3 shows that many of these scored well on method quality [ 36 , 37 , 39 , 41 , 42 , 51 , 58 , 60–62 , 65 , 69 ].…”

Section: Resultsmentioning

confidence: 99%

“…Fifteen of the included studies in the systematic review had a non-randomised design [ 36 , 37 , 39 , 41 , 42 , 51 , 54 , 58 , 60–62 , 64 , 65 , 67 , 69 ]. Supplementary Table 3 shows that many of these scored well on method quality [ 36 , 37 , 39 , 41 , 42 , 51 , 58 , 60–62 , 65 , 69 ]. Three had a medium risk of bias; one associated with the statistical analysis, differences in participants in control and experimental groups and a lack of multiple measurements [ 54 ] another due to differences in participants, lack of follow-up and statistical analysis [ 64 ] and one had differences in participants in the control and experimental groups, uncertainty regarding multiple measurements, and unclear reporting of follow up measures [ 67 ].…”

Section: Resultsmentioning

confidence: 99%

Interventions to reduce falls in hospitals: a systematic review and meta-analysis

Morris

¹

,

Webster

²

,

Jones

³

et al. 2022

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Background Falls remain a common and debilitating problem in hospitals worldwide. The aim of this study was to investigate the effects of falls prevention interventions on falls rates and the risk of falling in hospital. Design Systematic review and meta-analysis. Participants Hospitalised adults. Intervention Prevention methods included staff and patient education, environmental modifications, assistive devices, policies and systems, rehabilitation, medication management and management of cognitive impairment. We evaluated single and multi-factorial approaches. Outcome measures Falls rate ratios (rate ratio: RaR) and falls risk, as defined by the odds of being a faller in the intervention compared to control group (odds ratio: OR). Results There were 43 studies that satisfied the systematic review criteria and 23 were included in meta-analyses. There was marked heterogeneity in intervention methods and study designs. The only intervention that yielded a significant result in the meta-analysis was education, with a reduction in falls rates (RaR = 0.70 [0.51–0.96], P = 0.03) and the odds of falling (OR = 0.62 [0.47–0.83], P = 0.001). The patient and staff education studies in the meta-analysis were of high quality on the GRADE tool. Individual trials in the systematic review showed evidence for clinician education, some multi-factorial interventions, select rehabilitation therapies, and systems, with low to moderate risk of bias. Conclusion Patient and staff education can reduce hospital falls. Multi-factorial interventions had a tendency towards producing a positive impact. Chair alarms, bed alarms, wearable sensors and use of scored risk assessment tools were not associated with significant fall reductions.

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“…The GEMU is a subacute ward providing comprehensive geriatric assessment and management to patients . The median length of stay for participants enrolled in the AmbIGeM intervention from the SA GEMU ward was 19 [IQR13–28] days, from the WA GEMU was 15 [IQR11–21] days, and from the WA Gen Med was 9 [IQR5–15] days [15]. Although the principles applying to GEMU are similar across Australia, length of stay can vary, in part influenced by the availability of discharge options.…”

Section: Methodsmentioning

confidence: 99%

“…Staff identified and entered individual patient risk movements (getting out of bed, sitting to standing, walking without supervision, walking without aid) and locations (patient room, toilet, corridor) into the system, to alert when sensors detected those risk movements. Alerts were sent to clinical staff via handheld mobile phones (vibration and or sound mode) (see Visvanathan et al [14, 15] for further description). The trial consisted of 4 × 25-week blocks, commencing on July 10, 2017, with all three wards being control (usual care) as shown in Table 1.…”

Section: Methodsmentioning

confidence: 99%

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Patient Acceptability of a Novel Technological Solution (Ambient Intelligent Geriatric Management System) to Prevent Falls in Geriatric and General Medicine Wards: A Mixed-Methods Study

Dollard

¹

,

Wilson

²

,

Ranasinghe

³

et al. 2022

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Introduction: As effective interventions to prevent inpatient falls are lacking, a novel technological intervention was trialed. The Ambient Intelligent Geriatric Management (AmbIGeM) system used wearable sensors that detected and alerted staff of patient movements requiring supervision. While the system did not reduce falls rate, it is important to evaluate the acceptability, usability, and safety of the AmbIGeM system, from the perspectives of patients and informal carers. Methods: We conducted a mixed-methods study using semistructured interviews, a pre-survey and post-survey. The AmbIGeM clinical trial was conducted in two geriatric evaluation and management units and a general medical ward, in two Australian hospitals, and a subset of participants were recruited. Within 3 days of being admitted to the study wards and enrolling in the trial, 31 participants completed the pre-survey. Prior to discharge (post-intervention), 30 participants completed the post-survey and 27 participants were interviewed. Interview data were thematically analyzed and survey data were descriptively analyzed. Results: Survey and interview participants had an average age of 83 (SD 9) years, 65% were female, and 41% were admitted with a fall. Participants considered the AmbIGeM system a good idea. Most but not all thought the singlet and sensor component as acceptable and comfortable, with no privacy concerns. Participants felt reassured with extra monitoring, although sometimes misunderstood the purpose of AmbIGeM as detecting patient falls. Participants’ acceptability was strongly positive, with median 8+ (0–10 scale) on pre- and post-surveys. Discussion/Conclusion: Patients’ acceptability is important to optimize outcomes. Overall older patients considered the AmbIGeM system as acceptable, usable, and improving safety. The findings will be important to guide refinement of this and other similar technology developments.

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