Using complexity science to improve healthcare systems, from natural to social sciences
NetSI London talk
Paul Expert
Lecturer in Health Informatics, Global Business School for Health, University College London
Past Talk
Hybrid
Thursday
May 2, 2024
Watch video
11:00 am
EST
Virtual
177 Huntington Ave.
11th floor
11th floor
Devon House
58 St Katharine's Way
London E1W 1LP, UK
58 St Katharine's Way
London E1W 1LP, UK
The definition of complexity and complex systems is far from unique and their multiplicity increase when considering the whole spectrum of sciences, from the natural to the social. It is an opportunity for a pragmatic approach to combine concepts from the whole spectrum of complexity science to tackle societal problems. In this talk, we will present a mixed methods to conceptualise issues in the healthcare domain. In particular, we will focus on patient flow both in the hospital and the community to and show how a complexity science angle can be used to improve patient outcomes.
About the speaker
About the speaker
Paul Expert is a Lecturer in Health Informatics at the UCL Global Business School for Health. He earned his PhD in Physics in the Centre for Complexity Sciences at Imperial College London under the supervision of Profs Kim Christensen and Henrik Jensen. Previously, he obtained a BSc and MSc in Physics and an MSc in Statistics from the University of Geneva. Prior to Joining UCL, he hold post-doctoral positions in Digital Health at the Global Digital Health Unit at Imperial College London, Graph Theory and Machine Learning in the department of Mathematics also at Imperial College London, and in Neuroscience at the Centre for Neuroimaging Sciences, King’s College London. He was a visiting Associate Professor at the WRHI, Tokyo Institute of Technology 2020-2022.
His research interests are strongly anchored within complex system and complex networks theory, with applications in health systems, healthcare delivery and computational neurosciences.
Paul Expert is a Lecturer in Health Informatics at the UCL Global Business School for Health. He earned his PhD in Physics in the Centre for Complexity Sciences at Imperial College London under the supervision of Profs Kim Christensen and Henrik Jensen. Previously, he obtained a BSc and MSc in Physics and an MSc in Statistics from the University of Geneva. Prior to Joining UCL, he hold post-doctoral positions in Digital Health at the Global Digital Health Unit at Imperial College London, Graph Theory and Machine Learning in the department of Mathematics also at Imperial College London, and in Neuroscience at the Centre for Neuroimaging Sciences, King’s College London. He was a visiting Associate Professor at the WRHI, Tokyo Institute of Technology 2020-2022.
His research interests are strongly anchored within complex system and complex networks theory, with applications in health systems, healthcare delivery and computational neurosciences.
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