Claire Ainsworth, MSc

Senior Statistician

MSc, Statistics with Medical Applications
University of Sheffield, Sheffield, UK

BSc (Hons), Mathematics
University of Manchester, Manchester, UK

Claire Ainsworth, MSc, is a Senior Statistician in the Data Analytics and Design Strategy team at RTI-HS in the Manchester, UK office. Ms. Ainsworth has more than 7 years of experience in health outcomes research and data analytics and has worked on a range of projects. Specifically, Ms. Ainsworth has experience undertaking projects involving systematic and strategic literature reviews, network meta-analysis, global value dossiers, survey development, medical record reviews, and retrospective data analysis (such as structural equation modelling and analysis of heterogeneity). She has experience working in a range of therapeutic areas, including cardiology, gastroenterology, oncology, pain/analgesia, psychiatry, and respiratory. Ms. Ainsworth’s key roles include data analysis support and development of protocols, case report forms, statistical analysis plans, reports, slide sets, posters, and manuscripts. Her work has led to publications in journals such as Clinical Therapeutics, Value in Health, Journal of Medical Economics, and Expert Review of Pharmacoeconomics and Outcomes Research, alongside presentations at conferences such as the American Society of Clinical Oncology (ASCO) Annual Meeting, Digestive Disease Week (DDW), the congress of the European Crohn's and Colitis Organization (ECCO), the Congress of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR), and the International Association for the Study of Lung Cancer World Conference on Lung Cancer (IASCLC-WCLC). Ms. Ainsworth is also an experienced project manager and has experience in various statistical packages including R, Stata, and MPlus.

Ms. Ainsworth holds an MSc in Statistics with Medical Applications from the University of Sheffield. For her MSc dissertation, Ms. Ainsworth conducted a research project assessing the robustness of meta-analysis in the presence of heterogeneity, the findings of which were recently published in the Journal of Comparative Effectiveness Research.