Public Funding for Satalia Limited

"Satalia, an award-winning artificial intelligence (AI) company plan to transform this process through a partnership with Great Ormond Street Hospital (GOSH) NHS Trust to combine cutting-edge AI and predictive analytics to build an application that provides a near instantaneous scenario testing capability. This technology will draw data from several sources and act as a decision-support system for all key stakeholders. This project outputs will enable GOSH to conduct ~500 more operations/year without requiring any additional resources. The key objective is to develop a user-oriented product for scheduling operating theatres which then uniquely links to bed availability downstream on the ICU and wards. The product will maximise the number of treated patients by taking into account bed availability when setting up the theatre's schedule, and provide scenario testing. To achieve this, the system will provide the stakeholders with metrics, predictions and a proposed schedule that can be adjusted to include their own specialist expertise. The implicit rules that surgeons apply when making their adjustments will be learned and subsequently applied by a machine learning component - resulting in a system that improves over time.We expect three main benefits from our product. First, the coordination of theatre schedules and patient flow will result in a dramatic increase in throughput and utilisation, meaning we can treat more patients requiring the service of GOSH. Second, we expect a reduction in last minute cancellations which will dramatically increase the quality of care we give to our patients. Third, the scenario testing capability will remove the need for lengthy negotiations between teams in theatres and the wards and provide more time for delivering care. We expect the project to deliver a schedule with 5-10% higher utilisation Hospital-wide.The proposed scheduling system has several innovative aspects. This combination of machine learning, data analytics and user-centred optimisation has not been applied in hospitals before. Furthermore, the optimisation approach that calculates the optimal schedules will be a novel approach combining the theatre and bed problems (currently solved independently) minutely tailored to the hospital's requirements. Furthermore, the emphasis on usability and flexibility will result in a system that is high performing and easy for hospital staff to use. Finally, the system will reduce waste, more children will receive treatment and fewer children and their families will have to suffer the trauma and inconvenience of having their operations cancelled at the last minute."