Richard Croker
BSc MSc
Honorary Research Fellow
Richard is an honorary research fellow in the Bennett Institute for Applied Data Science, focusing on the OpenPrescribing project.
He qualified as a pharmacist in 1996, and has worked as a pharmaceutical adviser for the NHS for over 20 years. He is currently also the Deputy Director for Medicines Optimisation at NHS Devon.
Richard has a BSc in Pharmacy from the University of Portsmouth, where his final year dissertation was on the use of computer-aided learning in stereochemistry, and an MSc in Health Informatics from Swansea University, where his dissertation centred on the validity of prescribing denominators.
He also spends his time applying medicines optimisation principles to improving pathology services in the NHS.
Key publications
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New mechanism to identify cost savings in English NHS prescribing: Minimising 'price per unit', a cross-sectional study
Journal article
Croker R. et al, (2018), BMJ Open, 8
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The clinician impact and financial cost to the NHS of litigation over pregabalin: A cohort study in English primary care
Journal article
Croker R. et al, (2018), BMJ Open, 8
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Pregabalin: What the patent litigation means for doctors and drug companies
Journal article
Smyth D. et al, (2018), BMJ (Online), 361
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Trends and variation in prescribing of low-priority treatments identified by NHS England: a cross-sectional study and interactive data tool in English primary care
Journal article
Walker AJ. et al, (2018), Journal of the Royal Society of Medicine, 111, 203 - 213
Recent publications
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The impact of lidocaine plaster prescribing reduction strategies: a comparison of two national health services in Europe
Preprint
Mattsson M. et al, (2023)
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The impact of the COVID-19 pandemic on Antipsychotic Prescribing in individuals with autism, dementia, learning disability, serious mental illness or living in a care home: A federated analysis of 59 million patients’ primary care records in situ using OpenSAFELY
Preprint
Macdonald O. et al, (2023)
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Identifying Patterns of Clinical Interest in Clinicians' Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review.
Journal article
MacKenna B. et al, (2022), JMIR Med Inform, 10
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Recording of ’COVID-19 vaccine declined‘: a cohort study on 57.9 million National Health Service patients’ records in situ using OpenSAFELY, England, 8 December 2020 to 25 May 2021
Journal article
Curtis HJ. et al, (2022), Eurosurveillance, 27
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A hypothesis-free data science approach to identifying novel patterns of clinical interest in clinicians' treatment preferences: clusters of high Pericyazine and Promazine use in England (Preprint)
Preprint
MacKenna B. et al, (2022)