Optimizing patient flows in emergency healthcare with AI

Purpose and goal:

The project aims to investigate whether a tool developed by the Clinical Operational Research Unit (CORU) at University College London, based on machine learning to optimize patient flows in emergency healthcare can be used in the Sahlgrenska environment. We aim to evaluate its potential, increase collaboration with CORU through joint evaluation of the transferability and possible further development of the tool, and collect insights for AI-projects at Sahlgrenska.

Expected results and effects:

The expected result of the project is a strengthened relationship between the two parties, where the transferability of the tool is tested and evaluated. If necessary and time permits, we hope that improvements to the tool will be considered and possibly implemented. We hope this will result in a more robust and improved tool.

Approach and implementation:

A longer trip (approximately 4 weeks) would be scheduled in the first half of 2025. Exact dates are to be determined. After the first trip continued work with the implementation in Sahlgrenska will be done from Sweden. Then, after this, a shorter trip (approximately 2 weeks) will take place for follow-up on technical aspects and results. Collaboration before, between the visits, and after the project will primarily occur digitally.