This research uses machine learning to predict trauma demand and optimise hospital scheduling. By forecasting patient volume and dynamically allocating operating rooms, it reduces cancellations, improves efficiency, and lowers costs. The system has the potential to transform healthcare delivery by balancing emergency and elective care more effectively.

This research measures efficiency in Irish public acute hospitals using an efficiency frontier model. Results show significant cost, technical, and allocative inefficiencies, indicating billions in potential savings. Even a 1% improvement in efficiency could save €70 million annually while maintaining patient care levels.

This PhD developed a remote postoperative wound-monitoring pathway to replace dangerous, costly hospital journeys for patients in low-resource settings. Using a culturally adaptable questionnaire and phone/video follow-up, the method proved feasible, reliable, accurate, economical, and scalable. It could save the NHS £500 million annually while improving global surgical safety.