All we have covered in this informative blog
1- How Does Face Recognition Work?
2- Key Use Cases in Healthcare
3- The Future of Face Recognition in Healthcare
4- How to Get Started With Face Recognition?
Facial recognition, powered by deep learning, has become very reliable and accurate over the past few years. In healthcare, this has been lightening the load for workers and enhancing patient and community experiences by improving efficiency, security and reducing wait times, fundamentally reshaping the healthcare industry.
How Does Face Recognition Work?
Face recognition technology identifies or verifies individuals based on their unique facial features. This technology operates by detecting human faces in various sources, like live feeds or images, and then comparing these facial characteristics for potential matches.
XECAN has developed a specific approach to face recognition technology that relies on face templates. These templates are essentially numerical representations of facial characteristics that are unique to each individual. Importantly, this technology ensures a clear separation between biometric data and personal information, which is a crucial aspect of maintaining the highest level of privacy, especially when dealing with highly sensitive data. In other words, XECAN's technology ensures that their templates cannot be traced back to any specific individual.
Facial recognition software calculates the similarity between input face templates and stores them securely in a database that is linked to each patient's Electronic Medical Record (EMR) number. By strategically deploying facial recognition cameras in key clinic areas like reception areas, exam rooms, labs, and treatment rooms, healthcare facilities can visualize and share patient and staff workflows, automating patient clinic visits. This technology can significantly enhance the efficiency and security of healthcare operations.
Key Use Cases in Healthcare
Face recognition is finding applications across various healthcare domains, automating processes, enhancing security, aiding patients, improving care quality, and much more.
AI-assisted Clinic
Hospitals and clinics are facing a significant shortage of healthcare staff. The emergence of disruptive technologies like AI and facial recognition presents an opportunity to automate routine tasks, potentially alleviating this staffing challenge. In 2022, Berkshire Health Systems (BHS) in Massachusetts took a notable step by implementing a facial recognition system to streamline various aspects of its operations. This technology is being used to manage patient reception, optimize exam room workflows, and enhance patient identification within treatment rooms.
Patient Check-in, Direction, and Check-out
Upon a patient's arrival, the patient's face is recognized automatically and checked in on the hospital's Electronic Medical Records (EMR) system, confirming their identity without the need for repetitive paperwork or additional identification.
Additionally, it can efficiently guide patients to the appropriate waiting areas. A notable advantage of face recognition is its touchless nature; it doesn't require physical contact and can operate from a distance. This adds an extra layer of protection against infectious diseases.
In specialized departments like radiation and therapy, facial recognition can reduce front staff workload by over 60%, enhancing efficiency and the overall patient experience.
Surgical, Chemotherapy, or Radiation Therapy Time-out Process
The "time-out" procedure is a critical patient safety check performed just before starting surgical, radiation procedures, or drug administration. Hospital policies often require two forms of verification to ensure patient safety at this crucial moment. Facial recognition can serve as an effective means of verification during this process, not only improving patient safety but also streamlining the procedure.
Clinic Rooms Workflow Efficiency
Facial recognition for patient tracking can generate a real-time patient workflow whiteboard that keeps the clinical team informed about clinic room usage. This feature streamlines the process of identifying available rooms for new patients and those in use.
This precise tracking and room assignment greatly enhance efficiency, ensuring the delivery of high-quality care. It optimizes room allocation, enabling healthcare providers to streamline their workflow, minimize patient wait times, and guarantee that patients receive timely and well-organized care.
Preventing Medical Identity Theft
Medical identity theft is a fraudulent practice where an individual uses someone else's personal information, like their health insurance or social security number, without their consent. This is done to access medical services, acquire medical goods, or even gain money by submitting false claims for medical services and altering medical records to support these deceitful claims.
Patient Emotion Monitoring
Face recognition technology can be seamlessly integrated with emotion detection components to gain deeper insights into patient well-being. By doing so, it becomes possible to detect emotions such as pain, monitor the overall health status of patients, and even identify symptoms of certain illnesses. This combination of technologies holds great potential for enhancing patient care and improving healthcare outcomes.
Medical Robots with Facial Recognition
As medical robots become increasingly prevalent in hospitals for tasks like delivering medication and providing care, the integration of face recognition technology offers these robots a means to enhance their interactions with both patients and staff. By enabling the robots to "recognize" individuals, they can tailor their engagements to provide a more personalized and responsive experience.
The Future of Face Recognition in Healthcare
The introduction of face recognition technology in healthcare has brought about significant improvements across various aspects. It has bolstered security, streamlined patient identification, and enhanced monitoring and diagnosis, ultimately leading to a better patient experience and easing the workload for healthcare professionals.
Looking ahead, the future promises an even more widespread use of face recognition in healthcare. Exciting applications, such as advanced health monitoring and caregiving robots, are currently in development. The potential of face recognition in the healthcare sector is vast, and we can anticipate further innovations that will continue to improve patient care and outcomes.
How to Get Started With Face Recognition?
When integrating face recognition into your products, services, and processes, selecting the right software is a crucial first step. To ensure a robust and long-lasting solution, consider the following key factors:
Accuracy and Speed: The software should run seamlessly on your devices without compromising on both speed and accuracy.
File Format Compatibility: Look for software that can handle a variety of file formats, including images, videos, or real-time feeds.
Privacy Compliance: Ensure that the software prioritizes privacy compliance, not only to make patients and staff feel safe but also to adhere to privacy regulations.
EMR Integration: Ideally, the software should be ready to integrate with Electronic Medical Records (EMR) systems.
XECAN's facial recognition technology is specialized in the healthcare field and has a track record of successful implementation in over 100 hospitals and clinics. Over a decade of usage in hospital environments has fine-tuned the software. It seamlessly integrates with most hospital EMR systems, including EPIC.
Notably, XECAN's facial recognition algorithm has received high recognition. According to NIST (The National Institute of Standards and Technology) test evaluations, it ranks in the top 3% for accuracy both supervised (Visa Border, Border) and unsupervised (Kiosk). With 702 submissions by 255 providers, this is a testament to its performance.
If you're seeking the best healthcare face recognition solution, you can get started today by reaching out to info@xecan.com
To download the PDF version of this blog please click here