Dr Thomas Cowling
BSc MPH PhD
in Clinical Epidemiology
15-17 Tavistock Place
I am Assistant Professor in Clinical Epidemiology in the Department of Health Services Research and Policy, Faculty of Public Health and Policy.
I am currently supported by a Medical Research Council (MRC) Skills Development Fellowship (2018-2021). The aim of my research is to use linked, routine national health datasets to generate information that can be used to improve the delivery of healthcare. I currently focus on care for cancer patients (see 'Research' below).
I joined LSHTM in 2017 from Imperial College London where I completed degrees in Biomedical Sciences (BSc 2011), Public Health (MPH 2012), and Health Services Research (PhD 2016). My PhD was funded by an NIHR Doctoral Research Fellowship. I remain attached to Imperial as an Honorary Lecturer (profile).
I am a personal tutee for MSc Public Health students and am a seminar leader and marker for the Health Care Evaluation module; I also mark assignments and exams for the corresponding distance learning module.
I supervise three PhD students:
- Mr Matthew Parry (Specialist Registar in Urology) 'Multimodal treatment for patients with prostate cancer: a national study using existing electronic data'
- Ms Jemma Boyle (Specialist Registrar in General Surgery) 'Using national registry data to describe current practices and outcomes in the use of systemic anti-cancer therapy in the management of colorectal cancer in England'
- Mr David Wallace (Specialist Registrar in General Surgery) 'Liver transplantation as treatment for hepatocellular carcinoma'
I also contribute to teaching and marking on the MSc in Health Policy and Master of Public Health (MPH) degrees at Imperial College London.
I work as part of the Clinical Effectiveness Unit, a collaboration between LSHTM and the Royal College of Surgeons of England. The Unit, led by Prof David Cromwell, runs several national clinical audits in England funded by the NHS, including those for five major cancers: breast, colorectal, gastric, oesophageal, and prostate. The Unit holds complex national datasets of administrative, clinical, and organisational data linked for patients newly diagnosed with each of these cancers.
I am currently conducting a research programme that uses these datasets to develop prediction algorithms for important patient outcomes, such as use of emergency hospital services and survival. I am first examining the performance of more conventional statistical methods, such as regression analysis, before using statistical machine learning methods, such as boosted decision trees. I aim to develop actionable prediction tools for use in clinical cancer care.