Voxela VCare
:Case Studies

Azalee Group
Social Welfare Corporation Ejyukai
(Operation of nursing homes and care houses)

Voxela VCare enables monitoring with no blind spots.
Identification of high-risk areas and targeted intervention.

Azalee Group Ejyukai has introduced Voxera VCare, a next-generation monitoring system that effectively identifies the cause of accidents to solve problems with conventional fall detection methods (mat sensors and bed sensors).

The Azalee Group was established in 2009. It operates essential services of “welfare, education, and medical care” through three corporations: Tokyo Heiseikai, a medical corporation; Azalee Gakuen, a school corporation; and Ejyukai, a social welfare corporation.
We provide high-quality “welfare, medical, and educational” services to the local community, based on the brand concept of providing “can do, live, and be inspired,” the elements necessary to make life colorful throughout the lifecycle with local residents.

Challenges in the nursing home before the introduction of VCare

  • Step-type “mat sensors” and “Bed exit sensors” placed under the bed frequently misinterpret a resident’s movements or attempts to get in and out of bed as a “fall”.

  • The cause and reason for fall accidents can only be determined through interviews. This means that preventive measures can only be taken after the accident has occurred, by identifying the behaviors that led to the fall.

  • Conventional sensors have limitations in accurately detecting falls in common areas where residents gather. These sensors are typically confined to individual rooms and cannot effectively monitor falls in shared spaces.

“Voxela VCare” detects falls in all rooms and common areas without any blind spots.
Confirmation of video data enables analysis of the root cause of the fall and reduces the number of emergency medical services.

  • Industry-leading detection accuracy (99% or higher)
    Fewer false alarms
    Contributes to reducing the burden on nursing staff

    Voxela VCare automatically creates a video as soon as it detects a fall, allowing the user to easily check the situation on site through the management screen or application.
    Since its introduction, Voxela VCare has been able to detect falls with a high accuracy rate of over 99%, significantly improving operational efficiency.

  • Video data enhanced the accuracy of root cause analyses and decreased unnecessary emergency transports.

    Video data analysis enabled accurate identification of the root cause of falls, allowing for targeted preventative measures. Additionally, it facilitated precise determination of the necessity for Emergency Transport, thereby reducing unnecessary emergency responses and enhancing operational efficiency.

  • Remote monitoring improves the efficiency of nighttime monitoring

    Residents’ conditions can be monitored remotely, and sleep is no longer disturbed by only entering the room when necessary. Falls in common areas are also detected, while maintaining the privacy of residents’ rooms.

A fall distribution map is created based on the number of falls by 36 cameras. This helps to identify high-risk areas, improve the efficiency of nighttime monitoring, and improve quality of life.

The Azalee Group utilized graphing to pinpoint high-risk areas, which showed a significantly higher number of falls than others. This allowed them to implement targeted interventions in these specific zones, such as environmental adjustments and increased staffing. By focusing on fall-prone zones, the company was able to increase resident safety, reduce the total number of falls, and demonstrate the effectiveness of its fall prevention system. Additionally, this data-driven approach improves the efficiency of nighttime monitoring and quality of life.

Staff’s voice

  • By utilizing Voxela VCare, we are now able to effectively handle fall incidents.
    Explanations to family members have also been clarified, reducing the burden on caregiving staff.

  • A resident attempted to get out of bed and fell between the bed and the wall. Conventional sensors were unable to detect the issue. Voxela VCare’s AI, however, captured the incident and alerted staff. This allowed nursing staff to respond within a minute and identify the root cause. The video was instrumental in reducing the risk of similar accidents in the future.

Voxela VCare” helps nursing homes to reduce irregular costs (i.e., accidents, etc.), stabilize management, and improve profitability.
Please feel free to contact us for more information.

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