AI brings real-time data-driven risk evaluation to the operating room
Photo: Caresyntax
Traditional surgical risk calculators and assessment methods can struggle to account for a patient’s unique health situation, making accurate risk prediction a major challenge and increasing the possibility of complications throughout surgery. The consequences for surgeons, patients and healthcare systems can be significant: patient distress, poor outcomes and increased healthcare expenses.
So, it is no coincidence that AI has emerged as a crucial tool for evaluating risks in the operating room. The Caresyntax surgical intelligence platform combines the benefits of predictive data analytics and machine learning in an advanced solution, capable of tailoring risk evaluation to the specific health backgrounds of individuals, ensuring better patient safety and more efficient healthcare.
Harnessing the power of operating room data
Caresyntax's vendor-neutral surgery platform uses AI to analyse the vast amounts of data generated in modern operating rooms to improve patient outcomes, enhance surgical efficiency, and reduce healthcare costs. By enabling better decision-making and resource allocation, Caresyntax helps hospitals reduce clinical waste, optimise the use of scarce surgical resources, and significantly lower costs associated with surgical operations.
The platform analyses data from all sources in the operating room – video, audio, images, devices, clinical and operational – and can draw on more than three million surgical records to provide the surgical team with actionable insights before, during and after surgery. This is a good example of how AI-driven models can use predictive analytics to mine past data and identify future outcomes, while those models also learn and adapt continuously to understand complex relationships and patterns within the data.
Insights on the go
"Our platform addresses the pressing need for data-driven insights in the operating room, where even small improvements can have a profound impact on patient safety and hospital efficiency," says Björn von Siemens co-founder of Caresyntax.
Caresyntax software is already delivering the benefits of AI-powered risk mitigation in key surgical settings. It is being used to predict surgical site infections, achieving up to 80% sensitivity in identifying patients at high risk of infection. Elsewhere, its ClipAssistNet tool is providing surgeons with real-time feedback during laparoscopic and robotic surgeries. In cholecystectomies (gallbladder removal) for example, it analyses video data to ensure that the clip applier is visible and alerts the surgeon when visibility is poor.
Putting patient safety first
The use of AI in clinical settings demands ethical implementation, and Caresyntax software is compliant with multiple regulatory patient privacy and data protection mandates, including GDPR in the EU and HIPAA in the US, where it is also registered as a Patient Safety Organisation (PSO).
“Looking ahead, the impact of AI in predicting surgical risk extends far beyond immediate advancements,” says von Siemens. “The integration of AI has the potential to reshape the surgical care continuum, driving a shift towards more proactive and patient-centered care.
“As Caresyntax continues to innovate, the future holds immense promise for further advancements, including enhanced predictive capabilities, broader applications, and increased accessibility of this life-saving technology.”
The company was recently awarded the German AI prize, sponsored by Axel Springer/Bild. The prize is one of the largest AI awards in Europe and recognises outstanding achievements in the development and application of artificial intelligence across all industries. Von Siemens says the award validates the company’s progress so far in its mission to make surgery smarter and safer.