Dr Kym Snell PhD Department of Applied Health SciencesAssociate Professor in Biostatistics Contact details Emailk.snell@bham.ac.ukTwitter AddressDepartment of Applied Health SciencesPublic Health BuildingºÚÁϳԹÏÍø Edgbaston Birmingham B15 2TT UK Dr Kym Snell is an Associate Professor in Biostatistics and works within the Department of Applied Health Sciences. 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. Qualifications Graduate Statistician (GradStat), Royal Statistical Society, 2015 PhD Biostatistics, ºÚÁϳԹÏÍø, 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 ºÚÁϳԹÏÍø 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 ºÚÁϳԹÏÍø 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.