How Mobile Computer Vision Can Improve Cost and Time Efficiency in Healthcare by 95%
That amazing 95% result was at Leeds Teaching Hospital in the UK where they integrated Scandit computer vision into a mobile solution to capture vital data in a fraction of the time, in 114 departments as part of the UK Government’s Scan-4-Safety initiative.
For many healthcare enterprises, mobile computer vision technology is not a familiar term. Others are using mobile computer vision to make dramatic improvements in healthcare workflows and improve patient care. In this post, we will explain what mobile computer vision is and how the healthcare industry is using it in everyday consumer smart devices to drive up efficiency with reduced error rates and lower costs.
What is mobile computer vision?
Computer vision is a field of computer science that works on enabling camera-equipped devices to see, identify and process images in the same way that human vision does. It is closely linked with artificial intelligence, as the computer must interpret what it sees, and then perform appropriate analysis or act accordingly.
Mobile computer vision turns any smart device into a high-performance barcode and text scanner – a powerful data capture and information display tool. This changes the way people interact with objects and augments the physical world with real-time data captured by scanning barcodes and recognizing text with smartphones, tablets, wearables, drones, and robots.
Scandit mobile computer vision software scans barcodes via any smart device’s built-in camera, in most conditions such as bad light, with damaged or tiny labels, at a wide range of angles and distances, and at high speed. One of the key features of the software is MatrixScan which enables users to locate, track and decode multiple barcodes at once, using any camera-equipped device. So an entire set of barcodes is captured in a single sequence, greatly easing tasks such as search-and-find or inventory management. MatrixScan-AR (Augmented Reality) takes this a step further by overlaying real-time information onto the smart device screen. This could be patient details, drug information, stock levels or any other necessary information for the user to more quickly and accurately complete a task. See how it works in this short video.
Beyond barcodes, Scandit’s computer vision software also provides Text Recognition (OCR) for mobile apps. This enables users to capture predefined text data from sources such as forms, packages and labels via any smart device’s camera – and combine it with barcode capture if necessary. This eliminates the need for manual input and reduces the potential impact of human error. Decoding of text is fast and reliable, regardless of font, size or color. See OCR in action here.
Healthcare barcodes and familiar smart devices – a powerful solution
Mobile computer vision is a highly effective business solution for the healthcare industry. Since barcodes and alphanumeric codes are ubiquitous in pretty much all aspects of healthcare, workers are already capturing data with dedicated scanners in many workflows. Equipping smart devices with this scanning functionality brings a new level of speed, accuracy and flexibility to healthcare workflows. The smartphone is a familiar device with a familiar user interface for healthcare staff.
Software-based scanning is typically one-third the cost of hardware solutions
Compare the total cost of ownership (TCO) of dedicated scanning devices with software-based scanning on smart devices, and you’ll see the other big reason software-based scanning is replacing dedicated hardware scanners. With a Scandit-powered solution on smart devices making such big cost savings, organisations can equip more employees with the ability to perform tasks more quickly and accurately, spreading the time and cost savings across a large enterprise. And a mobile-software solution provides a robust and agile digital platform on which to build future innovation quickly, taking advantage of future software advances.
Manage patient care from anywhere
Healthcare employees can instantly access critical information such as medication, patient histories, lab workups or inventory – when they need it. This can reduce errors and increase patient safety with the highest quality of care. Scanning multiple barcodes in a single instance, quickly and reliably, is a great time-saver.
From the point of admission to discharge, caregivers can use barcode scanning-enabled smart devices to quickly identify patients. Any caregiver can identify patients by simply scanning their wristband anywhere in the hospital and connect the right patient to the right care. Since doctors, nurses, and other healthcare professionals are familiar with mobile apps in their everyday lives, they can easily use healthcare apps to perform patient care-tasks by scanning patient IDs to see patient information instantly on the device screen.
Safer medication administration
Healthcare professionals can use barcode scanning-enabled apps on smart devices to scan medication information into a record. Augmented reality (AR) overlays display critical medication information like expiration dates and patient-specific instructions such as the correct dosage or allergy information, making this process safer.
More efficient and error-proof specimen handling
MatrixScan functionality enables healthcare professionals to quickly scan multiple 1D and 2D barcodes on specimen containers simultaneously. When everybody handling the specimen containers is equipped with a barcode scanning-enabled smart device, clinicians can do more checks and further reduce the chance of errors. Augmented reality (AR) functionality enables healthcare providers to view patient information on the smart device screen in the most readable way. This ensures efficient and error-free handling of specimens.
Real-world examples of mobile computer vision improving healthcare processes
ERS Medical, a provider of specialist patient transport and courier services to the National Health Service (NHS) and the wider UK healthcare sector has replaced the traditional PDAs they used previously with Scandit-powered smart devices to increase the speed and efficiency of delivery of pathological specimen bags. ERS Medical’s drivers were able to increase scan speeds by 50%, enabling them to move more quickly through their pick-up-and-drop-off schedule. Also, instead of paying £800 for each new PDA, ERS Medical spends just £100 for each smartphone. They also report the cost to repair or replace broken smartphones is much lower. The cost savings here can be applied to improving patient care.
Leeds Teaching Hospital has integrated Scandit computer vision into its mobile patient safety, product accountability and location traceability solution to capture vital data in a fraction of the time. The hospital saw a 95% improvement in cost and time efficiency when it implemented Scandit software in 114 departments as part of the UK Government’s Scan-4-Safety initiative. Dr. David Berridge, Deputy Chief Medical Officer at the Leeds Teaching Hospital commented, “Scan4Safety will allow us 24/7 tracking of our patients to allow our endoscopy, radiology and theatre teams to be as efficient as possible. It allows our clinicians to manage their patients more closely and safely, including possible contribution to reduction of never events. Being able to perform patient / product recalls at the touch of a button, with greater reassurance of completeness is a tremendous facility. Reducing unnecessary waste by reducing unnecessary stock, eliminating out of date stock and being able to be open and challenging about unwarranted clinical variation is essential for an efficient hospital of the future. Scan4Safety is a real addition to good clinical practice.”
Empower Your Healthcare Teams With Mobile Scanning Today
Do call or message Scandit if you’re interested in learning more about our comprehensive healthcare solutions and how they can align your organization for long-term success. We would be happy to connect you with the resources your team needs to capitalize on mobile computer vision technology.