Post-operative surgical site infections (SSIs) pose a significant healthcare challenge, with a 1% to 3% incidence rate and potential for severe complications if not detected early. Current monitoring methods, which rely heavily on patient self-reporting and scheduled clinical visits, often lead to delayed diagnosis and treatment, in turn leading to severe complications, rehospitalization, and substantial healthcare costs. Also, traditional methods do not provide continuous monitoring, leaving significant gaps between scheduled post-operative visits. These gaps can result in missed early warning signs of infection. There is a clear need for an objective, continuous, and reliable method to monitor surgical wounds remotely. Such a solution would ensure early detection and treatment of infections, improving patient outcomes and reducing healthcare costs.
The “Infection Detective” is an innovative microneedle patch embedded in a waterproof bandage designed by UT researchers for post-operative surgical wound monitoring. This monitoring device integrates three key components:
These measurements, which indicate infection-related changes in pH and temperature, are transmitted in real-time to a smartphone application. The app uses machine learning to analyze the data, categorizes the wound condition, and providing healthcare professionals with timely alerts to potential infections.