Phenotyping methods for linked EHRs - CALIBER
Primary and Secondary care records are increasingly being linked for use in research. These data, however, are collected as part of routine care or for administrative purposes and a significant amount of work is required to build robust and accurate definitions of clinical concepts that can used to identify cases for further study.
In this course we present the basic theory behind the extraction of phenotype data from combined data resources such as CALIBER.
Through this practical course, participants will:
- become familiar with two contemporary primary and secondary data sources (CPRD and HES);
- learn what types of EHR data are collected and the different ways in which data are recorded;
- understand how to combine linked EHR data sources to define disease cases.
|09:00-09:30||Registration and coffee|
|09:30-10:30||Phenotyping electronic health records for research - theory||Arturo Gonzalez-Izquierdo|
|10:30-10:45||Case study: Phenotyping Cancer||Costantinos Parisinos|
|11:00-11:45||Phenotyping Reumathoid Arthritis||Mar Pujades-Rodriguez|
|14:15-15:15||Validating phenotypes across linked data sources||Mar Pujades-Rodriguez|
|15:15-15:30||Case study: Phenotyping myocardial infarction (UK Biobank)||Ghazaleh Fatemifar|
|15:45-16:00||Case study: Symptoms and signs||Hannah Evans|
|16:00-16:45||Alternative methods - next generation phenotyping||Spiros Denaxas|
|16:45-17:00||Q&A session||Arturo Gonzalez-Izquierdo|
- Dr Arturo Gonzalez-Izquierdo (Lead Tutor)
Arturo has a background in Statistics and came to the UK to specialise in the areas of Epidemiology and Public Health (MSc) and Biostatistics (PhD).
In the course of his PhD at Imperial College London and work at UCL over the last nine years, Arturo has gained expertise in studies related to the epidemiology of disease, the identification of patient populations and definition of patient classifications, and the understanding of healthcare utilisation and provision, with particular emphasis on the curation and analysis of large collections of data generated during the delivery of healthcare at national levels.
- Dr Mar Pujades-Rodriguez (Lead Tutor)
Mar is a clinical epidemiologist working in chronic diseases and multimorbidity. Her current research interests are conducting population-based pharmaco-epidemiological studies and applied prognostic research to improve healthcare and reduce health inequalities.
Mar trained in medicine and epidemiology and completed a PhD at Nottingham University. From 2006 to 2015 she led international HIV research and monitoring activities at Epicentre, a World Health Organisation Collaborating Centre. In 2012 she joint UCL, where she led multiple CALIBER studies, and in 2015 obtained an Academic Fellowship from the University of Leeds, where she currently works. Mar is a Honorary Senior Researcher at the Farr Institute London.
- Dr Spiros Denaxas
Spiros is a Senior Lecturer in Biomedical Informatics based in the Farr Institute London.
His research focuses on Electronic Health Record (EHR) phenotyping methods for translational research. He also manages CALIBER, a linked EHR data warehouse of 2 million adults in the UK.
- Ms Hannah Evans
Hannah is a biostatistician who specializes in health delivery and services research.
She has a broad experience of utilising electronic health record data for research and also teaches on the Graduate Programme in Data Science for Research in Health & Biomedicine at UCL.
- Dr Ghazaleh Fatemifar
Ghazaleh has a background in genetic epidemiology. Her research is focused on using genome-wide association studies to identify instruments for Mendelian randomisation.
She recently moved to the Farr Institute of Health Informatics Research London in order to perform genetic analyses using electronic heath records.
- Dr Constantinos Parisinos
Costas is a Wellcome Trust Clinical Research Training Fellow (UCL) and a Specialist Registrar in Gastroenterology & Hepatology (Barts Health NHS Trust). He is interested in the integration of electronic health records with genomic data, to better understand and prevent gastrointestinal disease and malignancy.