Cost-effectiveness, Incontinence, Incontinence-associated Dermatitis, Urinary Tract Infection
Conditions
Brief summary
The AI Supporter, an intelligent excretion management robot, leverages artificial intelligence-based vision recognition to autonomously detect and cleanse affected areas, followed by drying and changing the diaper, thereby reducing caregiver strain and enhancing care quality. This study aims to assess the efficacy of the AI Supporter in decreasing the incidence of urinary tract infections and incontinence-associated dermatitis among incontinent patients, in addition to exploring its cost-effectiveness. Adopting an experimental (two groups) and longitudinal design, this research utilizes both convenience and random sampling strategies. The study anticipates recruiting 60 female subjects who have been confined to bed for more than three months with urinary and/or fecal incontinence. Participants will intermittently use the AI Supporter over a 14-day period. Measurement tools include routine urine analysis.
Detailed description
Background: As Taiwan progresses medically, the aging demographic has become a significant challenge, leading to an escalation in the disabled population. The lack of caregiving manpower represents a critical bottleneck in the provision of long-term care. Diaper changing, a daily and labor-intensive task for caregivers, involves bending motions that pose a risk of musculoskeletal injuries. Consequently, the imperative development of automated caregiving technologies has emerged. The AI Supporter, an intelligent excretion management robot, leverages artificial intelligence-based vision recognition to autonomously detect and cleanse affected areas, followed by drying and changing the diaper, thereby reducing caregiver strain and enhancing care quality. Objective: This study aims to assess the efficacy of the AI Supporter in decreasing the incidence of urinary tract infections and incontinence-associated dermatitis among incontinent patients, in addition to exploring its cost-effectiveness. Methods: Adopting an experimental (two groups) and longitudinal design, this research utilizes both convenience and random sampling strategies. Scheduled from November 2024 to October 2025 at a residential long-term care facility in Central Taiwan, the study anticipates recruiting 60 female subjects who have been confined to bed for more than three months with urinary and/or fecal incontinence. Participants will intermittently use the AI Supporter over a 14-day period. Measurement tools include routine urine analysis, incontinence-associated dermatitis rating scales, pressure sore assessments, skin pH measurements, caregiver hours, and cost analyses pertaining to diapers and the AI Supporter. The principal analytical method employed will be Generalized Estimating Equations (GEE), with statistical significance defined at p \< 0.05. Expected Outcomes: The AI Supporter is expected to significantly reduce the occurrence of urinary tract infections and incontinance-associated dermatitis in patients, concurrently alleviating caregiver workload and diminishing associated costs.
Interventions
DEVICEAI-supporter
rticipants in the experimental group will use the AI-supporter, an intelligent excretion management robot. This device utilizes AI-driven visual recognition technology to automatically detect urine and feces, followed by a cleaning and drying process. When the AI-supporter detects excretion, it activates an automated sequence that washes, dries, and sanitizes the perineal area without requiring the caregiver to remove the diaper. The AI-supporter also records relevant data, such as the time, frequency, and weight of excretion, for further analysis. This intervention is designed to reduce the incidence of urinary tract infections (UTIs) and incontinence-associated dermatitis (IAD), as well as lessen the workload for caregivers
Sponsors
China Medical University Hospital
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE (Outcomes Assessor)
Intervention model description
Model Description: In this clinical trial, a parallel design is employed, where participants are randomly assigned to one of two groups: an experimental group and a control group. The experimental group will use the AI-supporter for excretion detection, cleaning, and drying processes, while the control group will use traditional diapers for care. The two groups will not cross over during the trial, meaning participants will remain in their assigned group throughout the study. This design allows for a direct comparison of the intervention's efficacy, with each group receiving a distinct form of care. The primary objective is to assess the effectiveness of the AI-supporter in reducing urinary tract infections and incontinence-associated dermatitis
Eligibility
Sex/Gender
FEMALE
Age
20 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Participants must have been bedridden for at least 3 months and have urinary and/or fecal incontinence. * Female participants aged over 20 years old. * Participants must be capable of wearing the AI-supporter device during the study period.
Exclusion criteria
* Participants with severe skin conditions unrelated to incontinence. * Participants with current urinary tract infections or incontinence-associated dermatitis at the time of enrollment. * Participants who are unable to provide informed consent or have a legal representative to do so.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| white blood cells | 14 days after intervention | urine analysis |
| Bacterial count | 14 days after intervention | urine analysis |
Countries
Taiwan
Contacts
Primary ContactKwo-Chen Lee, ph.D
Backup ContactJing-ya Fu
Outcome results
None listed