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Time Spent on Floor After Falls of Frailty People Overnight (NoDelayFall)

Primary Purpose

Dependence, Fall From Bed, Fall Injury

Status
Withdrawn
Phase
Not Applicable
Locations
France
Study Type
Interventional
Intervention
run-in period
Control period
Etolya-F ® devices
Sponsored by
Centre Hospitalier Annecy Genevois
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional device feasibility trial for Dependence

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

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

Sites / Locations

  • Résidence St François CH ANNECY-GENEVOIS

Arms of the Study

Arm 1

Arm 2

Arm 3

Arm Type

Other

Sham Comparator

Experimental

Arm Label

run-in period

control period

Etolya-F ® devices

Arm Description

In order to improve the precision of data, the run-in period is dedicated to sensitize the caregivers about the importance of reporting all the falls occurring during the night tracking in each resident's file, all informations about the estimate length of time spent on floor after a fall occurring during the night and also reporting every other events occuring at night as wandering. All the beds will progressively equipped with the Etolya-F ® devices but the Etolya-F ® ddevices will stay off.

We expect 30 falls will occurr at night during this 6 months period. Etolya-F ® devices will be installed on the bed of all participant residents but with limited fonctionnalities i.e. only the length of absence in the bed will be recorded (difference between time of detection of the beginning of absence in the bed and time where the resident will be found by the caregivers out of his bed).

We also expect 30 falls will occur at night during this 6-month period. Etolya-F ® devices will be used with all their functionalities i.e. 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

Outcomes

Primary Outcome Measures

Time for caregivers to find a resident who falls at night, before and after use of the Etolya-F® device
Delay 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 Outcome Measures

Diagnostic performance of the Etolya-F® device in the detection of night falls
sensitivity and specificity of Etolya-F®
Traumatic consequences of falls
Number of night falls resulting in hospitalization, fracture (s) or wound (s) requiring suture (s) or death

Full Information

First Posted
April 6, 2017
Last Updated
April 8, 2018
Sponsor
Centre Hospitalier Annecy Genevois
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1. Study Identification

Unique Protocol Identification Number
NCT03116386
Brief Title
Time Spent on Floor After Falls of Frailty People Overnight
Acronym
NoDelayFall
Official Title
Reduced Time on Floor After Falls at Night of People Living in Long Term Care Facilities - NoDelayFall Study
Study Type
Interventional

2. Study Status

Record Verification Date
April 2017
Overall Recruitment Status
Withdrawn
Why Stopped
Inability of the ETOLYA®'s manufacturer to furnish the promised functionalities as those which had to be recorded for assessment of the study's end points
Study Start Date
January 20, 2017 (Actual)
Primary Completion Date
May 2018 (Anticipated)
Study Completion Date
May 2019 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Centre Hospitalier Annecy Genevois

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No

5. Study Description

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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Dependence, Fall From Bed, Fall Injury, Fall in Nursing Home, Cognition Disorders

7. Study Design

Primary Purpose
Device Feasibility
Study Phase
Not Applicable
Interventional Study Model
Sequential Assignment
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)
Masking
None (Open Label)
Allocation
Non-Randomized
Enrollment
0 (Actual)

8. Arms, Groups, and Interventions

Arm Title
run-in period
Arm Type
Other
Arm Description
In order to improve the precision of data, the run-in period is dedicated to sensitize the caregivers about the importance of reporting all the falls occurring during the night tracking in each resident's file, all informations about the estimate length of time spent on floor after a fall occurring during the night and also reporting every other events occuring at night as wandering. All the beds will progressively equipped with the Etolya-F ® devices but the Etolya-F ® ddevices will stay off.
Arm Title
control period
Arm Type
Sham Comparator
Arm Description
We expect 30 falls will occurr at night during this 6 months period. Etolya-F ® devices will be installed on the bed of all participant residents but with limited fonctionnalities i.e. only the length of absence in the bed will be recorded (difference between time of detection of the beginning of absence in the bed and time where the resident will be found by the caregivers out of his bed).
Arm Title
Etolya-F ® devices
Arm Type
Experimental
Arm Description
We also expect 30 falls will occur at night during this 6-month period. Etolya-F ® devices will be used with all their functionalities i.e. 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
Intervention Type
Other
Intervention Name(s)
run-in period
Intervention Description
observational time i.e. baseline situation
Intervention Type
Device
Intervention Name(s)
Control period
Intervention Description
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
Intervention Type
Device
Intervention Name(s)
Etolya-F ® devices
Intervention Description
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
Primary Outcome Measure Information:
Title
Time for caregivers to find a resident who falls at night, before and after use of the Etolya-F® device
Description
Delay 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
Time Frame
2 periods of 6 months
Secondary Outcome Measure Information:
Title
Diagnostic performance of the Etolya-F® device in the detection of night falls
Description
sensitivity and specificity of Etolya-F®
Time Frame
2 periods of 6 months
Title
Traumatic consequences of falls
Description
Number of night falls resulting in hospitalization, fracture (s) or wound (s) requiring suture (s) or death
Time Frame
2 periods of 6 months
Other Pre-specified Outcome Measures:
Title
Number of night falls
Description
Number of actual falls occurring at night during each of the two study periods
Time Frame
2 periods of 6 months
Title
Number of night wandering
Description
Number of actual wandering occurring at night during each of the two study periods
Time Frame
2 periods of 6 months

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
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
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Dr Matthieu DEBRAY, MD
Organizational Affiliation
CH Annecy Genevois
Official's Role
Study Director
First Name & Middle Initial & Last Name & Degree
Dr Nathalie RUEL, MD
Organizational Affiliation
CH Annecy Genevois
Official's Role
Principal Investigator
Facility Information:
Facility Name
Résidence St François CH ANNECY-GENEVOIS
City
Annecy
ZIP/Postal Code
74000
Country
France

12. IPD Sharing Statement

Plan to Share IPD
No
Citations:
PubMed Identifier
21816682
Citation
Rapp K, Becker C, Cameron ID, Konig HH, Buchele G. Epidemiology of falls in residential aged care: analysis of more than 70,000 falls from residents of bavarian nursing homes. J Am Med Dir Assoc. 2012 Feb;13(2):187.e1-6. doi: 10.1016/j.jamda.2011.06.011. Epub 2011 Aug 4.
Results Reference
background
PubMed Identifier
18834557
Citation
Pellfolk T, Gustafsson T, Gustafson Y, Karlsson S. Risk factors for falls among residents with dementia living in group dwellings. Int Psychogeriatr. 2009 Feb;21(1):187-94. doi: 10.1017/S1041610208007837. Epub 2008 Oct 6.
Results Reference
background
PubMed Identifier
11928835
Citation
Jensen J, Lundin-Olsson L, Nyberg L, Gustafson Y. Falls among frail older people in residential care. Scand J Public Health. 2002;30(1):54-61.
Results Reference
background
PubMed Identifier
16500282
Citation
Vu MQ, Weintraub N, Rubenstein LZ. Falls in the nursing home: are they preventable? J Am Med Dir Assoc. 2006 Mar;7(3 Suppl):S53-8, 52. doi: 10.1016/j.jamda.2005.12.016.
Results Reference
background
PubMed Identifier
23602257
Citation
Lach HW, Parsons JL. Impact of fear of falling in long term care: an integrative review. J Am Med Dir Assoc. 2013 Aug;14(8):573-7. doi: 10.1016/j.jamda.2013.02.019. Epub 2013 Apr 16.
Results Reference
background
PubMed Identifier
19015185
Citation
Fleming J, Brayne C; Cambridge City over-75s Cohort (CC75C) study collaboration. Inability to get up after falling, subsequent time on floor, and summoning help: prospective cohort study in people over 90. BMJ. 2008 Nov 17;337:a2227. doi: 10.1136/bmj.a2227.
Results Reference
background
PubMed Identifier
16110729
Citation
Bergland A, Laake K. Concurrent and predictive validity of "getting up from lying on the floor". Aging Clin Exp Res. 2005 Jun;17(3):181-5. doi: 10.1007/BF03324594.
Results Reference
background
PubMed Identifier
18992702
Citation
Lester P, Haq M, Vadnerkar A, Feuerman M. Falls in the nursing home setting: does time matter? J Am Med Dir Assoc. 2008 Nov;9(9):684-6. doi: 10.1016/j.jamda.2008.06.007. Epub 2008 Sep 25.
Results Reference
background
PubMed Identifier
25864937
Citation
Pelissier C, Vohito M, Fort E, Sellier B, Agard JP, Fontana L, Charbotel B. Risk factors for work-related stress and subjective hardship in health-care staff in nursing homes for the elderly: A cross-sectional study. J Occup Health. 2015;57(3):285-96. doi: 10.1539/joh.14-0090-OA. Epub 2015 Apr 10.
Results Reference
background
PubMed Identifier
18508138
Citation
Capezuti E, Brush BL, Lane S, Rabinowitz HU, Secic M. Bed-exit alarm effectiveness. Arch Gerontol Geriatr. 2009 Jul-Aug;49(1):27-31. doi: 10.1016/j.archger.2008.04.007. Epub 2008 Jun 3.
Results Reference
background
PubMed Identifier
12641889
Citation
Banerjee S, Steenkeste F, Couturier P, Debray M, Franco A. Telesurveillance of elderly patients by use of passive infra-red sensors in a 'smart' room. J Telemed Telecare. 2003;9(1):23-9. doi: 10.1258/135763303321159657.
Results Reference
background
PubMed Identifier
26783046
Citation
Lipsitz LA, Tchalla AE, Iloputaife I, Gagnon M, Dole K, Su ZZ, Klickstein L. Evaluation of an Automated Falls Detection Device in Nursing Home Residents. J Am Geriatr Soc. 2016 Feb;64(2):365-8. doi: 10.1111/jgs.13708. Epub 2016 Jan 19.
Results Reference
background
PubMed Identifier
9345078
Citation
Tinetti ME, Williams CS. Falls, injuries due to falls, and the risk of admission to a nursing home. N Engl J Med. 1997 Oct 30;337(18):1279-84. doi: 10.1056/NEJM199710303371806.
Results Reference
background
PubMed Identifier
16513687
Citation
Parker MJ, Gillespie WJ, Gillespie LD. Effectiveness of hip protectors for preventing hip fractures in elderly people: systematic review. BMJ. 2006 Mar 11;332(7541):571-4. doi: 10.1136/bmj.38753.375324.7C. Epub 2006 Mar 2.
Results Reference
background
Links:
URL
http://drees.social-sante.gouv.fr/IMG/pdf/er515.pdf
Description
Diseases and loss of autonomy of residents in residential care facilities for the elderly
URL
http://drees.social-sante.gouv.fr/IMG/pdf/er899.pdf
Description
693,000 residents in residential accommodation for seniors in 2011 in France
URL
http://www.ladocumentationfrancaise.fr/var/storage/rapports-publics/074000390.pdf
Description
New technologies likely to improve gerontological practices and the daily life of elderly patients and their families

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Time Spent on Floor After Falls of Frailty People Overnight

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