Artificial intelligence solutions and computer vision, in particular are accelerating the pace of change in healthcare. Best of all, the widespread adoption of visual AI strategies for healthcare has only just begun. As a subfield of artificial intelligence, visual AI enables computers to "see" and process images and videos faster, more accurately, and more cost efficiently than a highly trained medical practitioner.
Computer vision systems for healthcare are also designed with HIPAA compliance in mind. For security purposes, these systems can deploy “on the edge.” This means that they run on processors with no connectivity to the cloud—making them less vulnerable to security breaches.
Computer vision technology is quickly offering the following benefits to the healthcare industry:
We'll take a closer look at each of these benefits and also touch on ROI opportunities.
Computer vision can improve both speed and accuracy when analyzing medical imaging: recognizing hidden patterns and making diagnoses with fewer errors than human professionals. A study in Nature found that visual AI systems were more accurate than human radiologists when analyzing mammograms for signs of breast cancer, reducing both false positives and false negatives. What's more, workloads were reduced by 88% when the AI system and providers worked together.
This technology can also act as another pair of “eyes” to support accurate diagnoses. This will be especially critical in the coming years as demand for medical image analysis continues to outpace the number of skilled human workers capable of providing these services. The U.S. Bureau of Labor Statistics projects a 9% increase in the number of radiologic and MRI technicians in the United States by 2028, but analysts expect that the digital pathology market will grow by 11.8% before 2027. As we face the increasing shortage of radiologic and MRI technicians, this technology can 1) reduce your medical imaging workloads, 2) reduce labor costs, and 3) ease your staffing shortages despite this explosive growth in demand.
A typical EHR system may require surgical nurses to make up to 100 clicks to document a surgical procedure. Computer vision systems can eliminate the need for this manual effort through direct observation and documentation, reducing or eliminating the need for human input. This advancement lets doctors and nurses spend more time on patient care, helping reduce stress for providers and improving outcomes for patients.
Smart operating rooms with this technology can also prevent errors. An estimated 1,500 surgeries every year result in a foreign object being left in a patient. Computer vision systems can keep track of surgical supplies and tools to protect against injuries caused by so-called "retained surgical bodies" (RSBs). By warning providers of RSBs, computer vision systems for healthcare help ease a significant source of stress during the operation while significantly improving patient care and surgical outcomes.
Cases of mistaken patient identity are unfortunately all too common in healthcare. A study by the Ponemon Institute found that 86% of nurses, physicians, and IT practitioners have personally seen or known of a patient being mistaken for someone else. While these errors are usually caught early, they can be dangerous or even deadly: If not corrected, patients can end up taking the wrong medications, receiving the wrong tests or treatments, or undergoing the wrong surgery. The Ponemon study also estimated that the average hospital risks $17.4 million in losses per year because of patient identification errors, including personal injury or malpractice claims.
That's exactly where computer vision comes in, helping prevent these cases of mistaken identity. Fully HIPAA-compliant, AI-powered facial authentication systems can recognize patients with an extremely high degree of accuracy in just a fraction of a second. Identification avoids patient misidentification while allowing providers access to correct medical records. These systems offer multiple layers of security for patient identity and access.
In 2019, U.S. hospitals recorded 221,400 work-related injuries and illnesses and a rate of 5.5 work-related injuries and illnesses for every 100 full-time employees. This is almost twice the normal rate for private industry as a whole. While many of these accidents and injuries are unavoidable, this technology can prevent many common worker injuries at medical facilities. They can reduce patient injuries as well. Moreover, when unavoidable injuries do occur, visual AI systems can send immediate alerts to appropriate personnel for faster response times.
The vast majority of worker and patient injuries at medical facilities happen when staff members fail to use required safety equipment, or when they fail to comply with safety protocols related to sterile processing. Here’s how this technology can dramatically reduce injuries related to these failures:
Injuries related to smoke and fire are also important concerns at medical facilities. With the ability to immediately identify the subtle signs of smoke and fire, computer vision systems can trigger evacuation alarms and notify emergency response teams earlier than traditional detection systems. Beyond smoke and fire, computer vision for fall detection can identify when a worker or patient falls, instantly notifying medical teams, and record the instance for legal and insurance purposes.
Last but not least, computer vision for medical research helps healthcare organizations speed up the process of investigating and testing new treatments and technologies. Here are a couple of examples to illustrate how visual AI can assist with medical research:
These are just two examples applying this technology in medical research. Ultimately, this advanced AI technology can perform virtually any task that would normally require human vision, human analysis, and understanding in a research or laboratory setting.
Leveraging computer vision solutions for these healthcare use cases offers ROI benefits for doctor’s offices, hospitals, outpatient surgical centers, medical labs, medical research centers and other healthcare-related facilities. These ROI benefits include:
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