Efficacy of Bed Mattress Sensor for Detecting Pre-fall Activities and Preventing Bedside Falls in Elderly in Residential Setting

NCT ID: NCT05490368

Last Updated: 2023-03-06

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 26 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-08-16
• Study Completion Date: 2023-02-28

Brief Summary

The study has 1 primary research question and 5 auxiliary research questions regarding the use of bed mattress sensor for detecting pre-fall activities in elderly residents in old-age home setting:

Primary research question:

1. Can bedside fall incidents per 1000 bed-days be reduced comparing the 6 months before and after the installation of the bed mattress sensor system, and compared to control group?

Auxiliary research questions:

2. Can the length of fall-related hospital stay shortens comparing the 6 months before and after the installation of the system and compared to control group?

3. What are the differences in fall characteristics comparing the 6 months before and after the installation of the system and compared to control group?

4. What is the number of different types of alerts and average time to turn off the alerts of the system (proxy measure of response time of the care staff), and how are they different to bed-exit alarm system?

5. What are the immediate care delivery of the staff upon the alert of the system, and how are they different to bed-exit alarm system?

6. What are the views and comments from the operation staff, residents and/or their family members on the usage of the bed mattress sensor?

Detailed Description

Study design

This is a 2-group quasi-experimental trial of comparing the outcome indicators between using the bed mattress sensor system and not using any bedside fall-prevention tools except restraints in residents living in Haven of Hope Woo Ping Care & Attention Home. Residents with moderate to high fall risk in one floor will be allocated to the experimental group and use the bed mattress sensor system for 6 months. Concurrently, residents with moderate to high fall risk in the other floors who do not use bedside fall-prevention tools including bed-exit alarm system, and ultra low bed will join the study as control group. We will also assess how the workflow and manpower changes due to the use of the sensor.

Subjects

Residents of 4 different floors in Haven of Hope Woo Ping Care & Attention Home will be recruited for the main analysis.

Procedures

System Installation

The system installation includes the dashboard shown in the monitor in the nursing station, sensor pad on the residents' bed, control box on the residents' bedside wall and mobile devices. The service unit and the product supplier shall discuss the installation plan.

Operation protocol preparation

A protocol including the dashboard control and related operations will be prepared for the staff.

Pilot run

The service unit will invite one eligible resident to participate in the pilot run. His/her bed will have the sensor pad installed. A designated staff in the nursing station will use the new system to get alert of pre-fall activities of the resident and provide early support of mobility. The experience will be used to revise the operation protocol.

Participants' selection

The care staff of the home will screen all residents for eligible residents with fall history in the past 12 months or with eligible Morse Fall Scale score. If the potential residents were assessed with Morse Fall Scale before 1 May 2022, Morse Fall Scale will be conducted again to update the score. In the experimental group, recruitment priority starts from those with a highest score in Morse Fall Scale until 10 participants are recruited. In recruiting suitable residents of the control group, the potential residents with similar Morse Fall Scale scores and similar profiles including gender, age, and fall history in the past 12 months to those of experimental group will be recruited. They and their family caregivers will be notified about the utilization about their fall records, and that the existing practice in fall prevention for them will not be altered during the trial. If they do not want to participate, they can notify the care staff (Opt-out participation).

Implementation

Operation

In the experimental group, the new sensor pad can detect any bed-exit activities, including stirring, sitting up, leaving, and out-of-bed. Audible message and alert to care staff can be customised in each participant. Whenever the system detects a change of bed-exit activity, an audible message will be played in the control box next to the resident's bed reminding the resident not to leave and that a care staff shall arrive shortly. Care staff at the nurse station will simultaneously receive the alert, as a sound and a visual figure on the dashboard, with the location and body position of the resident, and be prompted for a rapid and appropriate response. Care staff are allowed to customise each resident's alert settings, including time to alert and notification method.

In the control group, participants do not use any of the following bedside fall-prevention tools: bed-exit alarm system, ultra low bed, and ripple bed. The bed-exit alarm system only gives a sound alert to nurses' call-bell system when the participant completely leaves the bed. Ultra low bed reduces the fall distance and the consequent damage to the participants. Ripple bed prevents pressure ulcer.

Data collection

The University of Hong Kong (HKU) research staff who are blinded to the group allocation will search documents and coding, followed by collecting data on fall incidents and the total number of resident-bed days, 6 months before and after the adoption of the new system.

Five data sources will be accessed by the research staff before and after the system installation, including: (1) fall reports (including all fall characteristics), (2) residency reports to check the days stayed in the care home pre- and post-period for calculation of falls per 1000 bed-days; (3) hospital-stay reports including type of medical consultation and days of hospitalization; (4) the data retrieved from the bed mattress sensor system , including time in seconds for turning off the alert and number of alarms made by the system during the test period; and (5) designated log sheet for documenting immediate care delivery.

Qualitative interview will be conducted with the care staff and residents in the service units, and/or their family members to collect feedback on using the system at 2 months after the implementation and study completion.

Qualitative interview

To collect feedback towards the bed mattress sensor, the investigators will use purposive sampling to select 3-4 care staff and/or family members who witnessed the daily operation of the bed mattress sensor, and all 10 residents who will use the sensors to conduct semi-structured qualitative interviews to collect opinion on their satisfaction and perceived usability. An interview guide with open-ended and iterative questions will be used to probe for more experiences from the interviewees. Each interview will be conducted by a trained research assistant and will last about 30 minutes.

Blinding

Participants and group moderators cannot and will not be blinded to the intervention. Assessors of the follow-up outcomes and the research analysts will not be involved in the recruitment and intervention delivery, and will be blinded to the group allocation (single blindness).

Sample size determination

As 10 bed mattress sensors will be available, 10 participants will be recruited for the experimental group. To accommodate for equipment issues, all experimental group participants will reside on the same floor. To ensure that all 10 bed mattress sensors will be utilized, the floor with most potential participants will be allocated to the experimental group. All other floors will be control group. In the control group, to allow for drop-outs, a maximum of 5 more participants (i.e. 10 - 15 participants) will be recruited.

Data analyses

Main analysis

Poisson regression will be used to examine the reduction in bedside fall incidents and length of hospital stay due to the use of bed mattress sensor. Descriptive statistics will be used to analyze all other ancillary outcomes.

Qualitative interview

The interview content will be transcribed verbatim in Chinese for further analysis. The investigators will analyze the qualitative interview transcripts using framework analysis to construct a coherent and logical structure from the classification of many opinions and perceptions of the bed mattress sensor. The results will then discussed and consolidated in the panel meetings with the co-authors.

Conditions

Technology

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: PREVENTION
• Blinding Strategy: SINGLE

Study Groups

Bed mattress sensor system

The experimental group uses the new bed mattress sensor system for 6 months.

Group Type: EXPERIMENTAL

Bed mattress sensor system

Intervention Type: DEVICE

The new sensor pad can detect any bed-exit activities, including stirring, sitting up, leaving, and out-of-bed. Audible message and alert to care staff can be customised in each participant. Whenever the system detects a change of bed-exit activity, an audible message will be played in the control box next to the resident's bed reminding the resident not to leave and that a care staff shall arrive shortly. Care staff at the nurse station will simultaneously receive the alert, as a sound and a visual figure on the dashboard, with the location and body position of the resident, and be prompted for a rapid and appropriate response. Care staff are allowed to customise each resident's alert settings, including time to alert and notification method.

Control Group

In the control group, participants do not use any of the following bedside fall-prevention tools: bed-exit alarm system, ultra low bed, and ripple bed during the same 6-month period.

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

Bed mattress sensor system

The new sensor pad can detect any bed-exit activities, including stirring, sitting up, leaving, and out-of-bed. Audible message and alert to care staff can be customised in each participant. Whenever the system detects a change of bed-exit activity, an audible message will be played in the control box next to the resident's bed reminding the resident not to leave and that a care staff shall arrive shortly. Care staff at the nurse station will simultaneously receive the alert, as a sound and a visual figure on the dashboard, with the location and body position of the resident, and be prompted for a rapid and appropriate response. Care staff are allowed to customise each resident's alert settings, including time to alert and notification method.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• Residents with fall history in the past year, or
• Residents with Morse Fall Scale score of 25 or higher (moderate to high fall risk)

• Operate the bed sensor system (i.e. provide related care and assistance upon the alerts of the system)

• Having participated in the main trial
• Able to verbally communicate in Cantonese as perceived by the staff of the related home

• Having participated in the main trial

• Witnessed the daily operation of the bed mattress sensor, as advised by the participating staff

Exclusion Criteria

• Residents who are using bed-exit alarm system, ultra low beds or ripple bed (which are not suitable to use the mattress sensor)

• None

• None

• None

• None

• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Haven of Hope Hospital

OTHER

Sponsor Role: collaborator

The Social Innovation and Entrepreneurship Development Fund, Hong Kong

OTHER

Sponsor Role: collaborator

The University of Hong Kong

OTHER

Sponsor Role: lead

Responsible Party

Dr. Derek Yee-Tak Cheung

Principal Investigator, Assistant Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Yee Tak Cheung, PhD

Role: PRINCIPAL_INVESTIGATOR

The University of Hong Kong

Locations

Haven of Hope Woo Ping Care & Attention Home

Hong Kong, , Hong Kong

Countries

Hong Kong

Other Identifiers

HKU_bedsensor_protocol_v3

Identifier Type: -

Identifier Source: org_study_id