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Effectiveness of the AI-Supporter in Reducing Urinary Tract Infections

C

China Medical University

Status

Enrolling

Conditions

Urinary Tract Infection
Incontinence-associated Dermatitis
Cost-effectiveness
Incontinence

Treatments

Device: AI-supporter

Study type

Interventional

Funder types

Other

Identifiers

NCT06613503
CMUH113-REC3-109

Details and patient eligibility

About

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.

Full 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.

Enrollment

60 estimated patients

Sex

Female

Ages

20+ years old

Volunteers

No Healthy Volunteers

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.

Trial design

Primary purpose

Health Services Research

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Single Blind

60 participants in 2 patient groups

AI-supporter
Experimental group
Description:
Participants will use the AI-supporter for excretion detection, cleaning, and drying processes.
Treatment:
Device: AI-supporter
Traditional Diapers
No Intervention group
Description:
Participants will use theTraditional Diapers for excretion detection, cleaning, and drying processes

Trial contacts and locations

1

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Central trial contact

Kwo-Chen Lee, ph.D; Jing-ya Fu

Data sourced from clinicaltrials.gov

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