John Palmer (MEng., MSc.)

Thesis title: Developing Data Science Approaches to Improve Paediatric Critical Care Patient Flow and its Related Health Economics Benefits in Scotland

Research summary

My research interests revolve around the development and application of data science methodologies in understanding and improving patient flow within hospitals. This includes the development of care pathway models for patients requiring hospital admission from routinely collected clinical data, development of hospital simulations which can be used to identify and solve patient flow bottlenecks, and the development/application of machine learning methods to predict future patient flow metrics.

Current research interests

Current research domains include the improvement of patient flow for patients requiring Paediatric Critical Care (PCC). This specifically includes the development of novel Long-Short Term Memory (LSTM) models for the extraction of PCC patient care pathways, the development of hybrid discrete event/agent based simulation methods to evaluate patient flow and the application of machine learning methods for patients in PCC which are able to predict key patient flow care metrics such as length of stay, readmission risk and future care units using routinely collected clinical and high frequency physiological data.
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