Tim Jones is a Research Fellow using quantitative methods in Applied Data Science, Epidemiology, and Health Economics. Tim's interest has always been in using knowledge to increase the common good. This has taken many forms: helping to provide internet services to schools and universities; supporting adults with learning disabilities to live independently in the community; experimental research into the powerhouse of our thinking - working memory; and epidemiological analysis of large, routinely-collected, healthcare datasets.

Tim is currently working on analysis of National Joint Registry data, focussing on outcomes following joint replacements, which are amongst the most common elective hospital procedures. This includes producing annual reports summarising the performance of different types and brands of joint replacements; identifying potential outlier surgeons and hospitals for further exploration; and producing academic research articles on this topic. Previously, at NIHR ARC West, Tim contributed to a broad range of applied health research projects in collaborations between academia, the NHS, local authorities, and third sector organisations. In health economics his focus was on using NHS resources wisely, and reducing the use of clinical procedures of limited cost effectiveness. He was involved in maintaining the university licence for primary care data (CPRD) and secondary care data (HES) and supporting other researchers at the university to use these datasets. Prior to this, Tim worked for Public Health England analysing data from the National Cancer Registry, responding to local requests in the South West of England for information about any cancers, and producing national reports about skin and urological cancers.

Tim has taught on Bristol Medical School short courses on epidemiology, survival analysis, and STATA programming; NIHR ARC West training courses on Basic Statistics and Health Economics; modules about propensity scores and health economics on the Masters courses in Epidemiology and Public Health; and modules about interrupted time series analysis on the MSc in Health Economics.