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Raph Goldacre

Raph Goldacre

Raph Goldacre

Senior Data Scientist, Health Data Epidemiology Group

Raph Goldacre is a Senior Data Scientist in the Health Data Epidemiology Group. Underpinned by strong clinical-academic networks across Oxford University Hospitals (OUH) and beyond, Raph's research collaborations aim to join the dots between health data science, epidemiological methods, and clinically-informed translational research output, by maximising the use of NHS health data to answer epidemiological questions that are the most relevant to specialist clinicians, patients, public health policy, and population health intelligence.

Raph has undertaken published studies of long-term time trends in hospitalisation and mortality (distinguishing epidemiological burden of disease, healthcare burden of disease and artefact caused by, for example, changes in coding methods), in relation to acute and chronic non-communicable diseases, hospital-recorded infections, common surgical procedures, clinical and public health interventions, and shifts in healthcare delivery.

Other research collaborations include longitudinal studies of patient populations (such as case fatality, short/long-term hospital outcomes); studies of record-linked parent-child data to investigate associations between perinatal factors and maternal/paediatric disease; and studies of variation in mortality/morbidity by geographic region, reported ethnicity, and area-level deprivation. Much of this work feeds into cross-departmental collaborations with other research groups and projects where linkage to hospitalisation and other routine clinical data is required (such as the Million Women Study, UK Biobank, National Perinatal Epidemiology Unit, and large clinical trials including RECOVERY).

Raph holds an MSc in Epidemiology from the London School of Hygiene & Tropical Medicine, enjoys participating in knowledge-sharing networks in the BDI/Oxford Population Health, and teaches on the Oxford Population Health MSc course in Global Health Science & Epidemiology and the BDI course in Hospital Episode Statistics.