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

April 8, 2018 updated by: Centre Hospitalier Annecy Genevois

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

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.

Study Overview

Status

Withdrawn

Conditions

Intervention / Treatment

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.

Study Type

Interventional

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • France
      • Annecy, France, 74000
        • Résidence St François CH ANNECY-GENEVOIS

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Device Feasibility
  • Allocation: Non-Randomized
  • Interventional Model: Sequential Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Other: run-in period

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.
Other: run-in period
observational time i.e. baseline situation
Sham Comparator: control period
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).
Device: Control period
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
Experimental: Etolya-F ® devices
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
Device: Etolya-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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Time for caregivers to find a resident who falls at night, before and after use of the Etolya-F® device
Time Frame: 2 periods of 6 months
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
2 periods of 6 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Diagnostic performance of the Etolya-F® device in the detection of night falls
Time Frame: 2 periods of 6 months
sensitivity and specificity of Etolya-F®
2 periods of 6 months
Traumatic consequences of falls
Time Frame: 2 periods of 6 months
Number of night falls resulting in hospitalization, fracture (s) or wound (s) requiring suture (s) or death
2 periods of 6 months

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
Number of night falls
Time Frame: 2 periods of 6 months
Number of actual falls occurring at night during each of the two study periods
2 periods of 6 months
Number of night wandering
Time Frame: 2 periods of 6 months
Number of actual wandering occurring at night during each of the two study periods
2 periods of 6 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Centre Hospitalier Annecy Genevois

Investigators

  • Study Director: Dr Matthieu DEBRAY, MD, CH Annecy Genevois
  • Principal Investigator: Dr Nathalie RUEL, MD, CH Annecy Genevois

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Helpful Links

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 20, 2017

Primary Completion (Anticipated)

May 1, 2018

Study Completion (Anticipated)

May 1, 2019

Study Registration Dates

First Submitted

April 6, 2017

First Submitted That Met QC Criteria

April 11, 2017

First Posted (Actual)

April 17, 2017

Study Record Updates

Last Update Posted (Actual)

April 10, 2018

Last Update Submitted That Met QC Criteria

April 8, 2018

Last Verified

April 1, 2017

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2016-A01799-42

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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