To better allocate resources and plan for surgeries, Counties Manukau District Health Board (CMDHB) require data-driven analysis of their surgical scheduling. This will help them to understand the effect of re-allocating surgical sessions between surgical specialties.

The aim of this project was to develop a methodology and software tool to evaluate and improve the surgical service performance at CMDHB.

The project produced three key outputs in relation to this aim:

• A regression model to predict procedure durations,
• An optimisation model for allocating procedures to sessions, and
• A session bootstrapping tool that estimates both the number of procedures a session plan will perform, and how many additional sessions would be required to meet CMDHB’s elective targets.

Bootstrapping is a form of resampling which involves drawing randomly with replacement from an available set of data. This method was used to develop a tool that allows both the throughput of a session plan, and the number of additional sessions required to meet the elective targets.

We found that if CMDHB wanted to meet all of their elective targets they would need 112 additional sessions each month on average, however if they they only wanted to meet some of the targets then they would not need as many. In addition, it would be possible to meet some targets without additional sessions by sacrificing sessions from other specialties.

This project enables CMDHB to plan their sessions in a semi-automated, data-driven way. This tool can help hospitals to reduce costs through better planning and allocation of resources, which leads to increased efficiency.