AI-Powered Surgery Scheduler

This project was developed in AI Hack Melb 2023 competition. We were placed top 5 (finalists).

Overview

Problem: Australian Surgical waitlist times for elective procedures are often between 1-3 years. In that time, the patient’s condition often deteriorates and they are left in-active and dependent on others (increasing tax payer spend). The main issues that cause this are: inefficiently scheduled surgical lists, delays between patient surgeries, lack of staff skill level to match the procedure and lack of incentive for more efficient list times for nursing staff.

Solution: Create a predictive analytical model for scheduling cases that will predict the length of cases and assist with planning lists that optimise surgery throughput with skill level. This would include data like surgeon and nursing team experience, patient medical history and case complexity. Nursing teams would be incentivised to increase turnover time by being aware of their score and competing against other teams. Cases would be matched to surgeon and Nursing skill level. Cases would be timed and analysed against similar cases noting the differences staffing and patient data make to a case. Model would plan best possible list with patients and teams for maximum efficiency.

Application Walkthrough

Watch a video demonstration of our AI-powered surgery scheduling platform:

Website

Experience our AI Surgery Scheduler platform: View Website.