Staff Profile
Dr Mike Allen
Senior Research Fellow in Applied Healthcare Modelling and Data Science
My main interests are the application of modelling and machine learning to understanding and improving clinical pathways. Work, for example, includes modelling of the acute stroke pathway, with machine learning being used to understand and predict clinical decision making, allowing us to ask questions such as “what treatment would this patient receive if they went to another hospital?”.
I also have a general interest in how ‘deep reinforcement learning’ may be applied to healthcare. Can, for example, the Deep Mind agents that learned to play Go and Chess learn how to manage escalation/de-escalation policies in a hospital?
Contact by phone
01392 726080
Employed by
University of Exeter
Areas of expertise
Modelling, Data Science, Machine Learning
Projects
PenCHORD - Scheduling Community Mental Health Assessment in Devon
PenCHORD - NeoNet: Providing a national demand/capacity model for neonatal care in England PenCHORD - STEMI: Appropriate treatment for ST-elevation heart attacks PenCHORD - Plymouth Community Nursing PenCHORD - Neonatal PenCHORD - Doctor First PenCHORD - 18 week R2T PenCHORD - Cornwall acute and community stroke bed capacity modelling PenCHORD - Torbay and South Devon stroke care SW AHSN/PenCHORD project - Achieving step change in the emergency stroke pathway across the South West peninsula PenCHORD - Maximising access to thrombectomy services for stroke in England PenCHORD - Mapping and reconfiguration of hyperacute stroke services in Wales PenCHORD - SCN urgent care review: Modelling provision for stroke and cardiac services in the South West region Dialysis Service Modelling in Portsmouth Supporting the NHS through Operational Research SAMueL – Stroke Audit Machine LearningPublications
Right cot, right place, right time: improving the design and organisation of neonatal care networksFeasibility of a hyper-acute stroke unit model of care across England: a modelling analysisMaximising access to thrombectomy services for stroke in England: A modelling studyCan clinical audits be enhanced by pathway simulation and machine learning? An example from the acute stroke pathway.Planning and providing acute stroke care in England: the effect of planning footprint sizeInvolving patients and the public in healthcare operational research - the challenges and opportunitiesExploring the cost-effectiveness of mechanical thrombectomy beyond six hours following advanced imaging in the UKInvolving patients and the public in healthcare operational researchA framework to accelerate simulation studies of hyperacute stroke systemsA framework to accelerate simulation studies of hyperacute stroke systemsHow can frontline expertise and new models of care best contribute to safely reducing avoidable acute admissions? A mixed-methods study of four acute hospitals.Upcoming Events
Jan
21
PPI Advice Clinic
Online
Patient and Public Involvement Advice Clinics Whatever your query,
from finding out more about Patient and...
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Jan
26
Searching and Review Clinic
Online
COVID-19 update: As a result of the pandemic, all PenARC staff are
currently working remotely. While...
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News
Could physical activity help minimise drug and alcohol use?
17 December 2020
Figures and surveys have shown that high-risk alcohol consumption
increased during lockdown periods, while exercise...
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£300,000 from NIHR to investigate the views of older adults on strategies to improve recovery from planned surgery
10 December 2020
A team of researchers from across the University of Exeter Medical
School, Royal Devon &...
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'Why physical activity matters more than ever'
01 December 2020
Professor of Health Service Research, Adrian Taylor, discusses
motivation, exercise schemes, and the future impact on...
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Research Projects
Police Service Modelling Associates (PSMA) Programme
Theme: ARC - Methods for Research & Improvement
The PSMA Programme is a pilot programme which supports analytical
staff working in policing to...
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Remote-by-Default Care in the COVID-19 Pandemic
Theme: ARC - Public Health
A research project to investigate how to ensure the delivery of
effective care accessed remotely...
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