Use Case - Operating Theatre Booking Optimisation
The theatre booking use case employs an AI model to optimise operating schedules, aiming to cut overtime, decrease cancellations, and improve theatre use. The anticipated outcomes are greater efficiency, better staff morale, and enhanced patient satisfaction with timely care.
The initiative aims to streamline operating theatre schedules, substantially curtailing patient wait times and bolstering theatre occupancy. It seeks to harness predictive analytics for precise resource allocation, accommodating both planned surgeries and emergent cases. The end goal is a robust, data-driven system that enhances hospital efficiency and patient care while providing a flexible, adaptive scheduling tool for healthcare providers.
The AI solution employs predictive machine learning to optimise operating theatre schedules, reducing the likelihood of late-running cases that incur overtime costs and impact staff morale. By forecasting case durations, the model prevents underutilisation of OR time, ensuring resources are efficiently allocated. The resulting streamlined operations not only minimise the need for cancellations but also create an environment where urgent procedures can be accommodated promptly, thereby enhancing overall patient satisfaction.
Optimised Theatre Utilisation
The AI model enhances theatre occupancy rates, allowing for more surgeries to be conducted and reducing idle time.
Streamlined scheduling leads to reduced waiting times for surgeries, enhancing overall patient satisfaction and health outcomes.
Improved scheduling efficiency translates into cost savings for the hospital by optimising staff deployment and reducing overtime expenses.