Right patient, right pathway, right time: a pilot minimum dataset, triage and early optimisation model for the Royal Melbourne Hospital pre-admission clinic

The pre-admission clinic (PAC) is a critical gateway to safe surgery, but current systems often measure appointments rather than whether patients are truly ready for surgery.

My project aims to improve perioperative readiness by redesigning the pre-admission clinic pathway at the RMH. I will test a focused, risk-based model combining a minimum referral dataset, structured pathway strea ming, targeted optimisation for common modifiable risks and patient preparation resources. If successful, the project will help RMH identify issues earlier, reduce avoidable late pathway failure and use perioperative resources more effectively.

The MacHSR Fellowship will give me the structure and methodological support to deliver this work as a rigorously evaluated health services research project. I am keen to develop my skills in implementation science, mixed-methods evaluation and health service measurement. RMH will benefit from the practical outputs, including a minimum PAC dataset, readiness measure, risk-based streaming framework and roadmap for broader implementation. More broadly, the project could help shift PAC from an appointment based-model toward a readiness-based model that better supports patients, clinicians and theatre flow.