Dr Kym Snell PhD

Institute of Applied Health Research
Associate Professor in Biostatistics

Contact details

Email: k.snell@bham.ac.uk
Twitter: @Kym_Snell

Address: Institute of Applied Health Research
Public Health Building
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Kym Snell is an Associate Professor in Biostatistics and works within the Institute of Applied Health Research. She is a member of the Biostatistics, Evidence Synthesis, Test Evaluation and prediction Modelling (BESTEAM) research group.

Kym’s interest is in applied and methodology research relating to risk prediction models. This includes development, validation and updating of risk prediction models and in the use of individual participant data (IPD) for prediction modelling.

Kym also leads the 3-day CPD course “Statistical Methods for Risk Prediction and Prognostic Models” and is an associate editor for the BMC Journal Diagnostic and Prognostic Research.

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Qualifications

Graduate Statistician (GradStat), Royal Statistical Society, 2015

PhD Biostatistics, University of Birmingham, 2015

MSc Medical Statistics with specialisation in Modern Epidemiology, University of Leicester, 2010

BSc (Hons) Statistics, University of Reading, 2009

Biography

Kym graduated with a BSc (Hons) in Statistics from the University of Reading in 2009, following which she gained her MSc in Medical Statistics from the University of Leicester in 2010. She then worked as a biostatistician in cardiovascular research at the University of Leicester for a year where she had her first taste of prognosis research and risk prediction. This led to Kym doing a PhD at the University of Birmingham on statistical methods for prognosis research, awarded in 2015. Kym moved to Keele University in 2016 to work within the Centre for Prognosis Research. In 2018 Kym was awarded an NIHR School for Primary Care Research launching fellowship which enabled her to continue her research on using individual participant data to develop and validate risk prediction models for primary care.

In 2023, Kym moved back to the University of Birmingham where she continues to work on both methodology and applied research, primarily relating to risk prediction models.

Teaching

3-day online CPD course: Statistical Methods for Risk Prediction and Prognostic Models

Research

Kym is interested in both methodology and applied research in risk prediction and prognostic modelling.

Kym's methodology interests are in methods for developing and validating reliable risk prediction models, including calculating appropriate sample sizes. She is also interested in the use of individual participant data (IPD) from multiple sources and electronic health records (EHR) for the purpose of prediction modelling. Kym is also involved in developing reporting guidelines for different types of prognosis studies and led the development of TRIPOD-SRMA for systematic reviews and meta-analyses of prediction model studies.

Kym’s applied research covers a broad range of clinical areas, but she has a particular interest and is keen to collaborate on prediction projects relating to diabetes or maternal health.

Other activities

Associate Editor for BMC Diagnostic and Prognostic Research since 2017.