Artificial Intelligence-Assisted Clinical Decision Support System in Telemedical Wound Care: A Randomized Controlled...

Area of Science:

• Digital Health
• Artificial Intelligence in Medicine
• Wound Care Management

Background:

• Chronic wounds are a growing concern, exacerbated by an aging population and increased chronic diseases.
• Inexperienced home caregivers often lead to suboptimal chronic wound healing.
• Telemedicine offers solutions for care gaps, but manual wound assessment is burdensome; AI can enhance this process.

Purpose of the Study:

• To evaluate an AI-assisted clinical decision support system, "Ulcer Care" (UC), integrated into telemedicine for chronic wound management.
• To assess the impact of the UC system on patient and caregiver psychosocial outcomes.
• To compare the effectiveness of AI-assisted telemedical care versus conventional care for chronic ulcers.

Main Methods:

• A randomized controlled trial (RCT) involving 40 patients with chronic ulcers from July 2023 to February 2024.
• The UC system used AI for automated wound measurement, tissue classification, and deterioration alerts.
• Primary endpoint: wound healing at 12 weeks; secondary endpoints: quality of life (QoL), clinic visits, and complications.

Main Results:

• Thirty-five patients completed the study; wound healing rates were comparable between the AI-assisted telemedicine group and the control group (64.9% vs 73.4%).
• The AI-assisted group required significantly fewer clinic visits (5.5 vs 13.2, P=0.009).
• Caregiver quality of life showed greater improvement in the AI-assisted group (FDLQI improvement: 10.3 vs 5.7, P=0.08).

Conclusions:

• The "Ulcer Care" AI-assisted telemedicine platform is non-inferior to conventional care for wound healing and improves caregiver QoL.
• AI in telemedicine shows promise for reducing healthcare utilization and enhancing chronic wound management.
• Further AI accuracy and usability improvements are recommended for broader clinical adoption.