Antonella Delmestri
PhD
Lead Health Data Scientist
- Alan Turing Fellow
- CPRD fob holder for NDORMS
- EHDEN UK data science technical lead
- EHDEN OMOP common data model specialist
I am a computer scientist and software engineer at the Centre for Statistics in Medicine at NDORMS. I am responsible for the automation of data engineering, data modelling and advanced curation of real-world data (RWD) routinely collected by GPs, hospitals and registries, and used in observational research.
My research is focussed on the impact of algorithmic automation on RWD processing, its role in the statistical pipeline and its impact on the medical research output. My main interests are:
- data engineering, data modelling and advanced curation of RWD
- evaluation and improvement of RWD quality
- assessment, measurement and enhancement of algorithmic complexity
- research quality, ethics, reproducibility, consistency and transparency
BIOGRAPHY
I graduated in Computer Science at Udine University and completed my PhD in Information and Communication Technologies at Trento University, Italy. I have worked for several years in companies developing firmware and software for electronic devices.
In 2006 I moved to the U.K. to join the Clinical Trial Service Unit (CTSU) at Oxford University. My biggest achievement in this role was the whole IT management of ATLAS (Adjuvant Tamoxifen Longer Against Shorter), a long-term early breast cancer randomised controlled clinical trial. ATLAS involved more than 15,000 women recruited from over 600 sites in more than 20 countries worldwide, and its findings on patients' survival and recurrence using 5 versus 10 years of Tamoxifen changed clinical practice in the UK and worldwide.
In 2013 I joined NDORMS to lead the big data management of the Epidemiology Unit, and I started developing Curator, a data science tool for RWD, which has allowed for the delivery of more than twenty-five observational studies so far. In 2017 I was given solo responsibility for the NDORMS CPRD fob. In 2018 I joined the European Health Data and Evidence Network (EHDEN) collaboration and in 2019 I became responsible for OHDSI UK Data Science activities. In 2021 I was awarded an Alan Turing Fellowship
Recent publications
-
The burden of long COVID: a multinational cohort analysis of Spanish and UK data including SARS-CoV-2 infections, reinfections, and matched contemporaneous test negative controls
Preprint
Prieto-Alhambra D. et al, (2023)
-
Association between outpatient follow-up and incidence of revision after knee and hip replacements: a population-based cohort study
Journal article
PINEDO VILLANUEVA R. et al, (2023), Bmc musculoskeletal disorders
-
Characterising complex health needs and the use of preventive therapies in the older population: a population-based cohort analysis of UK primary care and hospital linked data
Journal article
ELHUSSEIN L. et al, (2023), Bmc geriatrics
-
UK poSt Arthroplasty Follow-up rEcommendations (UK SAFE): What does analysis of linked, routinely collected national datasets tell us about mid-late term revision risk after knee replacement?
Journal article
Smith LK. et al, (2023), Bmj open
-
Thrombosis and thrombocytopenia after vaccination against and infection with SARS-CoV-2 in the United Kingdom.
Journal article
Burn E. et al, (2022), Nat commun, 13
-
Observational methods for COVID-19 vaccine effectiveness research: a trial emulation and empirical evaluation
Journal article
Catala Sabate M. et al, (2022), Medrxiv
-
Digital ethnicity data in population-wide electronic health records in England: a description of completeness, coverage, and granularity of diversity
Preprint
Pineda-Moncusí M. et al, (2022)
-
Comparative risk of thrombosis with thrombocytopenia syndrome or thromboembolic events associated with different covid-19 vaccines: international network cohort study from five European countries and the US.
Journal article
Li X. et al, (2022), Bmj, 379