UCF researchers have developed an automated detection system aimed at helping to prevent and reduce the number of healthcare-associated infections (HAIs) contracted during medical procedures. The new System for Detecting Sterile Field Events tracks activity during training or an actual medical procedure and identifies actions (such as contact-related events) that violate the sterile field and put patients at risk for infection. The computer-based system operates in real-time, using visual and auditory alerts to highlight potential contamination made during a procedure. For training purposes, the system can also project onto the patient/area an overlay of the surfaces that were contaminated during the procedure. According to the Centers for Disease Control and Prevention (CDC), approximately 1 in 25 U.S. patients contracts an HAI during the course of their hospitalization, indicating a need for improved infection control in U.S. healthcare facilities. Examples of HAIs are central line-associated bloodstream infections, catheter-associated urinary tract infections and ventilator-associated pneumonia. In any procedure where infection is possible, it is critical that medical personnel protect the sterile field—an area that is considered free of microorganisms, such as bacteria and viruses. However, the use of sterile techniques is limited to CDC rules or “best practices” that can be interpreted and applied in different ways, making it difficult to track and measure in training as well as clinical practice.
The system automates the job of overseeing medical procedures and providing objective visual/auditory performance indicators. Key to the system are sensors (such as cameras), processors and output devices (such as monitors and speakers)—all linked together to track, assess and respond to events that affect the sterile field. This includes objects and humans in or near the field. The system programming includes rules for maintaining the sterile field, along with contamination probability values, statistical measures and thresholds. The processors can iteratively update the contamination probability value for each surface during the procedure and can also connect to one or more output devices, which issue alerts when an event violates predefined rules for protecting the sterile field and patient safety.
- Identifies HAI risks associated with medical procedures
- Provides feedback in real-time to students and medical personnel
- Automated process is objective, controlled and repeatable
- Hospitals and medical facilities
- Sterile field training and practice
- Touch and proximity sensing for robotics