
Julian Matthewman
Research Fellow · Electronic health records
Institute of Hygiene and Tropical MedicineAbout
Dr. Julian Matthewman is a Research Fellow in the Department of Non-communicable Disease Epidemiology within the Faculty of Epidemiology and Population Health at the London School of Hygiene & Tropical Medicine (LSHTM). He is also an academic liaison for the Alan Turing Institute, the UK's national institute for data science and artificial intelligence, and serves as a theme lead for LSHTM's Centre for Data and Statistical Science for Health (DASH).
Dr. Matthewman completed his medical degree at the Medical University of Vienna, followed by an MSc and PhD in Epidemiology at LSHTM. His educational background reflects a strong foundation in both clinical medicine and epidemiological research methods.
As a clinically-trained epidemiologist, Dr. Matthewman focuses on electronic health records research related to non-communicable diseases, with particular emphasis on skin and inflammatory conditions including eczema and psoriasis. His work spans multiple areas including pharmacoepidemiology, mental health comorbidities in dermatological conditions, and methodological research for electronic health record analysis. His research often involves large-scale population studies using UK primary care data.
His publication record demonstrates a consistent focus on methodological rigor in electronic health record research, with recent work examining comorbidities in atopic eczema, developing codelists for routine health data research, and investigating medication safety. His articles frequently address the intersection of dermatology, epidemiology, and data science, with notable contributions to understanding the broader health implications of skin conditions.
Dr. Matthewman actively contributes to education by organizing the short course "Introduction to Pharmacoepidemiology" and teaching on courses including "Analysis of Electronic Health Records" and "Data Challenge". He supervises summer projects for MSc Epidemiology and MSc Health Data Science students and organizes LSHTM's R user group, supporting computational skills development within the institution.
His work spans multiple collaborative projects, particularly those involving the Alan Turing Institute and LSHTM's Centre for Data and Statistical Science for Health. He has developed numerous codelists and computational tools that support reproducible research in electronic health records, contributing significantly to methodological standards in the field.
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