Maxine is a Research Associate and Fellow working between The Alan Turing Institute, The Health Foundation and the University of Oxford where she primarily works with Prof Chris Holmes. Her work has looked at applying machine learning to health, care and life science challenges, and to date has been particularly focused on NHS data. She is currently working on exploring the boundaries of what we define as health data, and how we can infer how healthy or sick people are, based on their financial, geospatial, social or transactional consumer data. Prior to this she completed a PhD at UCL on early signs of dementia in electronic health records, an MSc in Health Policy, Planning and Financing (LSE & LSHTM) and a BSc in Biomedical Sciences, Neuroscience & Pharamcology (UCL). 

She is also an advocate for inclusion in technology and co-founded One HealthTech, an international, grassroots, federated community of healthtechnologists which exists to support individuals from under-represented groups to be future leaders in health innovation. She's had the good fortunate to have worked across a number of public and private organisations including L'Oreal, Roche, the Royal Society, the NHS and the World Health Organisation, and has been involved in a number of communities and committees including serving as a NED for the Eastern Academic Health Science Network, sitting on the DeepMind Independent Review Board the NHS technology review, and is a member of the World Economic Forum's Global Shapers. She is also really into fancy dress.  


Research interests

Healthcare makes up on ~10% of our health, with the other 90% being genetic, behavioural and social factors. Despite this, much of the health data research is dominated by healthcare data only, such as a clinical trials, physiological measures or electronic health record data, or makes use of only a narrow set of other determinants, like genetic factors of self-reported by behaviours. If we are to realise the hype and hope of advance analytics and AI for personalised, predictive and preventative healthcare, we need a better understanding of the causes of disease, and how different determinants of health interact. Citizens’ digital footprints are increasingly being captured as a by-product of daily living activities in consumer data companies, yet there is currently no way by which to make use of these data, in combination with other sources, for health and care purposes at scale. 

Maxine’s work focuses on understanding how we can re-draw the boundaries of what we define as “health data” by making use of financial, geospatial, social or transactional consumer data to infer the health status of populations, and find scalable ways to use existing datasets to better understand social determinants of health. Much of this work involves collaborating with large private companies to understand how to safely, ethically and openly repurpose consumer data for public health research.