Empowering Patients and Caregivers to Use Artificial Intelligence and Computer Vision for Wound Monitoring:...

Area of Science:

• Digital Health
• Artificial Intelligence in Healthcare
• Wound Management

Background:

• Chronic wounds affect 1-2% of the global population, presenting significant challenges.
• Artificial intelligence (AI) and computer vision (CV) offer new avenues for remote wound monitoring and patient engagement.
• A patient-facing mobile application was developed to empower patients and caregivers in managing chronic wounds.

Purpose of the Study:

• To evaluate the feasibility and usability of the Patient Connect app.
• To assess preliminary clinical outcomes of using the app for remote wound data capture and sharing.
• To determine the app's effectiveness in engaging patients and caregivers in chronic wound care.

Main Methods:

• A feasibility study involving 28 patients with chronic wounds across two Canadian outpatient clinics.
• Participants used the Patient Connect app for wound imaging and secure data sharing with healthcare providers.
• AI models analyzed wound data, and clinicians reviewed information for treatment decisions.

Main Results:

• Patients submitted a median of 13 wound images per wound, with an average submission every 8 days.
• The study included diverse wound types such as diabetic ulcers, venous ulcers, and pressure injuries.
• A median wound closure of 80% surface area was achieved, indicating clinical potential.

Conclusions:

• The Patient Connect app is feasible and engages patients/caregivers in chronic wound management.
• AI-powered remote monitoring shows promise for improving adherence and care accessibility.
• Further research is needed to explore scalability, cost-effectiveness, and broader healthcare applications.