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A Study on the Application of Smart Bed-Exit Alert Assistive Devices for Detecting Preoperative Bed Exits in Ophthalmic Surgery Patients in the Operating Room

A Study on the Application of Smart Bed-Exit Alert Assistive Devices for Detecting Preoperative Bed Exits in Ophthalmic Surgery Patients in the Operating Room

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07693829
Enrollment
160
Registered
2026-07-09
Start date
2026-04-23
Completion date
2026-12-31
Last updated
2026-07-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Cataract

Keywords

Smart Bed-Exit Alert System, Patient Safety, Pressure Sensor, Nursing Efficiency, Cataract Surgery

Brief summary

This prospective, randomized interventional study aims to evaluate the effectiveness of a smart bed-exit alert system for patients undergoing cataract surgery during the preoperative waiting period. Participants will be randomly assigned to either the smart bed-exit alert system group or the standard care group. The study will compare nurse bedside visit frequency and nursing care time during the preoperative waiting period to evaluate whether the smart bed-exit alert system improves patient safety and nursing care efficiency.

Detailed description

Patients undergoing cataract surgery remain on a stretcher in the operating room holding area for approximately 30-60 minutes while awaiting adequate pupil dilation. During this period, patients may attempt to leave the bed because of physiological needs (e.g., toileting) or psychological factors (e.g., anxiety or seeking family members), increasing the risk of falls and compromising patient safety. This prospective, randomized interventional study will enroll 160 adult cataract surgery patients. Participants will be randomly assigned in a 1:1 ratio to either the intervention group (smart bed-exit alert system) or the control group (standard nursing care). The intervention group will be monitored using the UNEO smart bed-exit alert system, which consists of a pressure-sensing mattress capable of detecting body position and bed-exit attempts. When a predefined bed-exit threshold is reached, the system immediately notifies nursing staff through audible and tablet alerts. The control group will receive routine nursing observation according to standard clinical practice. The study will compare patient care requests, attempted bed exits, nurse bedside visit frequency, and direct nursing care time between the two groups to evaluate whether the smart bed-exit alert system improves nursing workflow and enhances patient safety.

Interventions

DEVICESmart Bed-Exit Alert System

Participants assigned to the intervention group will receive standard nursing care supplemented by the smart bed-exit alert system. The pressure-sensing mattress continuously monitors patient position and generates real-time alerts when predefined bed-exit criteria are met, allowing nurses to provide timely assistance.

Sponsors

National Taiwan University Hospital
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* Patients undergoing cataract surgery.

Exclusion criteria

* Age under 18 years. * Unable to follow verbal instructions.

Design outcomes

Primary

MeasureTime frameDescription
Frequency of nurse bedside visitsDuring the preoperative waiting period before entering the operating room (approximately 30-60 minutes).Number of nurse bedside visits during the preoperative waiting period.
Nursing care timeDuring the preoperative waiting period before entering the operating room.Total nursing care time provided during the preoperative waiting period.

Countries

Taiwan

Contacts

CONTACTChing-Yu Yang
ycyyang@ntuh.gov.tw+886972652407
CONTACTShang-Ping Yang
spy201211@gmail.com+886910859033

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Jul 10, 2026