Dr Luke Budworth
- Position: Senior Research Data Analyst (Bradford Institute for Health Research) | Visiting Senior Research Fellow (University of Leeds)
- Areas of expertise: patient safety; health informatics; medical statistics; health psychology
- Email: L.W.Budworth@leeds.ac.uk
- Website: LinkedIn | Googlescholar
Profile
I'm a senior data analyst based at Bradford Institute for Health Research. I work within one of six NIHR funded patient safety research centres where I provide data science support to all research teams and themes.
I also have my own portfolio of patient safety research and much of my time is spent developing a patient safety cohort using data from the Connected Bradford data warehouse. With this data I am:
- Using cutting edge statistical methods (MAIHDA) to study intersectionality (e.g. being low SES and an ethnic minority) and patient safety indicators (e.g. infection);
- Training machine learning classifiers to accurately predict patient-level risk of acute deterioration in primary care;
- Working towards using causal inference methods and theory to study co-produced questions and hypotheses around safety
I also work on various projects across medicine and psychology. To name a few I am:
- Working with clinical staff to develop maternal morbidity risk prediction models from maternal data taken from across the whole of Yorkshire (MEaCC)
- Trial statistician on an upcoming MPS funded RCT to assess a psychological intervention on staff burnout (REBOOT)
- Developing resources and materials to help future researchers interested in patient safety informatics
...and always much more!
Research interests
Broadly, I have expertise in statistical programming and analysis, data visualisation, and research design. I have experience leading complex research projects in healthcare settings and am active in academia, routinely presenting, publishing, applying for research funding, and peer reviewing.
I have much hands on experience building cohorts from electronic health record data, but also working with research data including from observational studies, experiments, and trials. I’m experienced in applying advanced statistical and machine learning methods including Bayesian and frequentist multilevel, general(ised) (non-)linear modelling; causal inference theory and methods; risk prediction modelling; survival and time-to-event modelling; meta-analysis; and missing data theory and imputation methods.
Qualifications
- BSc | Psychology | University of Liverpool
- MSc | Health Psychology | University of Leeds
- MSc | Health Data Analytics | University College London
- PhD | University of Leeds
Professional memberships
- Royal Statistical Society (Fellow)