Automating Preoperative Assessments for Enhanced Patient Care and Healthcare Efficiency.

More than 13,000 patients in Catalonia (>4 million worldwide) suffer last-minute surgery cancellations (LMC) every year due to preoperative inefficiencies. As anaesthesia services struggle to meet surgery demands, covering preoperative evaluations becomes even more challenging. Actual resource-intensive pre-anaesthetic assessment is undermined by the high demand leading to inefficiency.

Yet, an adequate assessment shows low-risk patients (>70%) for surgery and ensures thorough preparation for the high-risk ones, by enacting risk profiles while iteratively examining health status, medical history, treatment, laboratory results, etc. 
We have developed a Robotic Process Automation (RPA) Medical Device Software (MDSW) tool to assess patients to improve the data collection and collection process inefficiencies by structuring, cleaning/debugging and presenting it appropriately. It interacts with patients through a WebApp personalized medical survey, asynchronously reviewing medical histories via Electronic Health Records (EHRs) and calculating patients’ presurgical risk using state-of-the-art risk tables/scores and calculators. Through these means, it flags low-risk patients from medium/high risk reporting their personalized needs to the medical team.

To our knowledge, our tool is the only fully automated one, which accesses, aggregates, and processes extensive data, using a complex rule-based symbolic AI expert system for a reliable risk score assessment.

We want to move the MDR clinical pathway by demostrating clinical performance, clinical benefit, and at the same time enhacing the medical device software by implementing better AI features.