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Time Spent on Floor After Falls of Frailty People Overnight

Reduced Time on Floor After Falls at Night of People Living in Long Term Care Facilities - NoDelayFall Study

Status
Withdrawn
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03116386
Acronym
NoDelayFall
Enrollment
0
Registered
2017-04-17
Start date
2017-01-20
Completion date
2019-05-31
Last updated
2018-04-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Dependence, Fall From Bed, Fall Injury, Fall in Nursing Home, Cognition Disorders

Brief summary

In the context of reduce staff for supervision of dependent elderly, automated risk alert systems could have a positive impact on the organization of night care by better targeting monitoring. Residents' sleep could be less affected with use of automatic alert system than by systematic monitoring visits. One study shows an improvement in the humor of residents after the use of such a system. The hypothesis of the study is that the use of a bed-raising detection system linked with the activation of a lighting environment and a caregivers alert system (Etolya-F® gerontechnology device, Anaxi Technology Company) would reduce intervention time in this population, thus limiting the time spent on floor and its physical and psychological consequences.

Detailed description

In France in 2011, more than 575000 elderly lived in long term care facilities. Most of them had comorbidities. The most frequent reason for admitting in long term care facilities is the worsening of health status of elderly, often triggered by a fall. Elderly living in long term care facilities have frequently several comorbidities; the first ones are Alzheimer and related diseases. The proportion of such very dependent institutionalized people has risen for the last recent years and they represent a population at very high risk of falling. In an epidemiological analysis of more than 70,000 falls from residents of Bavarian nursing homes, the prevalence of fall was estimated at 1.49 falls for women and 2.18 for men. Those results didn't take into account the fact that people could fall more than once a day. In Alzheimer people (or people with related diseases) who lived in long term care facilities, the incidence of falls was even highest with 2.7 falls per resident per year. The consequences of falls are not only physical injuries (wounds, fractures); they are frequently associated with psychological repercussions as loss of self-confidence, fear of new falls, reduction of abilities of moving which lead into declining of daily activities and loss of autonomy. The incapacity of getting up alone is reported by more than a third of patients who have fallen, even if the fall is not complicated by a fracture. The length of time people stay on floor is directly link to the ability of the elderly person to give an alarm and to the presence or not of someone else to help him/her to get up. Patients who live in long term care facilities have limited functional capabilities not compatible with an operational use of active alarm systems. In long term care facilities, 30-40% of falls occur between 8pm and 8am. Falls occurring at night seem to be associated with more severe injuries. Staff are less numerous at night with only 3 to 4 caregivers for 100 people. To the best of the knowledge of the investigators, delay intervention time after a fall occurring at night has never been studied. Based on the investigators' experience, elderly people can only be discovered and helped when caregivers find them on floor on the occasion of a planned surveillance visit. These visits are carried out every 2 to 4 hours at night. Automated alarms are used to alert staff to situations where there is a high risk of falling: an attempt to lift an armchair from a person who cannot stand or to detect the night-time rise of a high-risk people with the use of various sensors (pressure sensors connected to the mattress or environmental sensors). In the context of staff reduced at night for the supervision of dependent elderly, automated risk alert systems could also have a positive impact on the organization of night care by better targeting monitoring. Residents' sleep could be less affected with use of automatic alert system than by systematic monitoring visits. One study shows an improvement in the humor of residents after the use of such a system. The hypothesis of the study is that the use of a bed-raising detection system linked with the activation of a lighting environment and a personnel alert system (Etolya-F® gerontechnology device, Anaxi Technology Company) would reduce intervention time in this population, thus limiting the time spent on floor and its physical and psychological consequences.

Interventions

OTHERrun-in period

observational time i.e. baseline situation

neither activation of any lighting environment when the resident gets up from his bed nor alert if the resident did not return to bed after 15 minutes Etolya-F ® devices will only permit detection and recording of the moment of the elderlly will leave his/her bed and recording of the moment the elderly will be found by caregivers

DEVICEEtolya-F ® devices

Etolya-F ® devices will permit detection of absence in the bed, activation of a lighting environment when the resident gets up from his bed, transmission of alert to caregivers through the centralized system of sick call if the resident do not return to bed after 15 minutes and recording the time when caregivers will find the resident out of bed, distinguishing between a fall and a night wandering in the room or corridors without a fall

Sponsors

Centre Hospitalier Annecy Genevois
Lead SponsorOTHER

Study design

Allocation
NON_RANDOMIZED
Intervention model
SEQUENTIAL
Primary purpose
DEVICE_FEASIBILITY
Masking
NONE

Intervention model description

Run-in period then 6 months control period and then 6 months experimental period with activation of all the functions of Etolya-F® (the device used in the study)

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* elderly people who are resident in long term care facilities * non opposed to participate to the study or whose his/her legal representative is not opposed to the participation of the resident to the study

Exclusion criteria

* the resident's bed can not be equipped with the ETOLYA-F® device for any reason

Design outcomes

Primary

MeasureTime frameDescription
Time for caregivers to find a resident who falls at night, before and after use of the Etolya-F® device2 periods of 6 monthsDelay elapsing between the moment a resident has left his/her bed and the time he/she was found by caregivers, on floor after a fall at night

Secondary

MeasureTime frameDescription
Diagnostic performance of the Etolya-F® device in the detection of night falls2 periods of 6 monthssensitivity and specificity of Etolya-F®
Traumatic consequences of falls2 periods of 6 monthsNumber of night falls resulting in hospitalization, fracture (s) or wound (s) requiring suture (s) or death

Other

MeasureTime frameDescription
Number of night falls2 periods of 6 monthsNumber of actual falls occurring at night during each of the two study periods
Number of night wandering2 periods of 6 monthsNumber of actual wandering occurring at night during each of the two study periods

Countries

France

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026