| Author: | Fok, See Kee |
| Title: | Infrared bed exit sensor with voice prompt messages (Luna Cat) to prevent inpatient falling : a quasi-experimental study |
| Advisors: | Qin, Harry (SN) |
| Degree: | DHSc |
| Year: | 2024 |
| Department: | Faculty of Health and Social Sciences |
| Pages: | 89 pages : color illustrations |
| Language: | English |
| Abstract: | Background Many falls in healthcare settings occur when patients attempt to leave their beds without seeking assistance. While several sensor technologies exist, there is a lack of substantial evidence to support their effectiveness in reducing inpatient falls. To address this gap, a novel solution has been introduced: the Luna Cat, an infrared bed exit sensor device equipped with voice prompts. This innovative device is specifically designed to prevent falls among high-risk patients by detecting and alerting HCPs when patients attempt to exit their beds unassisted. Objectives The primary objective of this study is to investigate the accuracy of the Luna Cat system in detecting bed exits among high fall-risk patients without the need for assistance. Additionally, the study aims to assess the effectiveness of the Luna Cat system in preventing inpatient falls by promptly alerting healthcare providers (HCPs) when patients attempt to exit their beds unassisted. Study Design This quasi-experimental study was conducted in a hospital setting from May to July 2023. A total of 60 high-risk fall patients were recruited for this study. The intervention involved the use of a sensor that detected when a patient attempted to leave the bed, triggering a voice prompt message to remind them to stay in bed and await assistance. The message was sent to an iPad placed at the nurses' station, alerting healthcare professionals to provide help. Standard fall prevention measures were implemented in both groups as per usual practice. Demographic data of patients in the interventional and control groups were collected for comparative analysis. HCPs labelled the alarms as 'true positive', 'false positive', or 'false negative' to calculate the sensitivity and specificity of the Luna Cat system. Results A total of 60 patients were recruited. The Luna Cat system exhibited a high sensitivity of 98.6% and specificity of 88%. Notably, no falls were reported in either group. In the intervention group, the system successfully detected 73 true positive alarms. Both the patient/relative and HCP groups expressed satisfaction with the system, giving it a rating of 3.4 out of 4, and expressed their willingness to recommend the Luna Cat system for fall prevention purposes. Conclusion The Luna Cat system has demonstrated accurate detection of bed exits among high fall-risk patients in a real hospital setting, without the need for assistance. These findings make a valuable contribution to the expanding body of knowledge on fall prevention in healthcare settings. By highlighting the effectiveness of the Luna Cat system, this study emphasizes the importance of implementing innovative solutions to enhance patient safety and prevent falls in healthcare environments. This Luna Cat system was designed by engineering and hospital staff, unlike previous studies that were only designed by engineers. Hence, the design was more suitable for the hospital setting and patient usage. The result was encouraging, and the acceptance was high among patients, relatives, and HCPs. As this is a newly invented system, there is room for improvement, such as using a Lidar camera to enhance the accuracy of the sensor and protect patient privacy, as well as using an individual panel as the receptor in the nurses’ station to ensure signals can be transmitted and received. The technology is not a substitute for staff; adequate staff availability is still necessary when the patients need or wish to leave the bed. A bed exit alarm, such as Luna Cat, is only one intervention within a comprehensive, more critical, multi-component fall-prevention programme that addresses patients’ unique needs. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 7994.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.88 MB | Adobe PDF | View/Open |
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