1 more surgery per day = more $$$

Artificial intelligence (AI) and computer vision have been making significant strides in the healthcare industry, revolutionising the way healthcare providers operate. One area that has seen a significant impact is surgical process value chain in hospitals. In this short post, we will explore the power of AI and computer vision in this field and how it can streamline operations, reduce costs, and ultimately, improve patient outcomes.

The surgical process value chain in hospitals involves a complex and highly coordinated set of activities, from scheduling and patient preparation to the surgical procedure itself and postoperative care. However, there are numerous inefficiencies that plague this process, resulting in lost time, increased costs, and lower patient satisfaction.

According to a study published in the Journal of the American Medical Association (JAMA), surgical delays and cancellations cost hospitals approximately $62 billion annually in lost revenue and increased expenses. The study found that 17% of surgeries are delayed, with the average delay lasting over an hour. These delays result in increased costs, decreased patient satisfaction, and in some cases, even harm to patients.

This is where AI and computer vision come in. By leveraging these technologies, healthcare providers can improve the efficiency and accuracy of the surgical process value chain, reducing the number of delays, minimising costs, and improving patient outcomes.

One example of this is the platform built by DARVIS, OmniRoom. OmniRoom uses AI and computer vision to optimise healthcare logistics and increase productivity. It provides customers with a range of digital services, including OCR, inventory track and trace, object scanning at choke points, productivity monitoring, attendance scoring, productivity scoring, plan to actual space utilisation comparison, flow insights, cost model insights, spatial search capabilities, and more.

A German national hospital group utilised OmniRoom to optimise their sterilisation logistical flow and saw a significant increase in productivity, allowing them to perform one more surgery per day. This generated significant cost savings and revenue generation potential, highlighting the impact that the platform can have on operational efficiency in healthcare.

But the power of AI and computer vision in healthcare extends beyond just logistics optimisation. These technologies can also be used to improve surgical outcomes and patient safety. For example, computer vision can be used to identify potential surgical site infections (SSIs) and provide real-time feedback to the surgical team, allowing them to take corrective action before the infection becomes serious.

Additionally, AI can be used to predict patient outcomes based on a range of factors, including age, medical history, and preoperative risk factors. This information can be used to create personalised treatment plans that optimise outcomes while minimising risks.

Overall, AI and computer vision have the potential to revolutionise the surgical process value chain in hospitals, improving efficiency, reducing costs, and ultimately, improving patient outcomes. As healthcare providers continue to seek ways to improve their operations, it's likely that we will see more and more of these technologies being implemented in hospitals around the world.