Ben Kearns

Photograph of Ben Kearns

University of Sheffield
Regent Court, 30 Regent Street
Sheffield, S1 4DA

Office: 1012

Tel: (+44) (0)114 222 6380
Fax: (+44) (0)114 222 0749


ORCiD: 0000-0001-7730-668X

Twitter: @benjaminkearns2



I am an NIHR Doctoral Research Fellow based in the Health Economics and Decision Science section of the University of Sheffield. My academic background includes an MSc in Applied Statistics (Merit) and a BSc in Mathematics (1st) which included an "Institute for Mathematics and its Applications" prize for outstanding achievement. My research interests lie in the use of statistical methods to inform model-based economic evaluations. My fellowship shall look at producing guidance on good practice methods for predicting future outcomes in health technology assessment (HTA). This is important as HTA typically requires evidence on lifetime outcomes, but the available data only span outcomes for a limited number of years. Many different methods are available to produce extrapolations and guidance is required to help choose between these.

I have extensive experience in HTA and the use of statistical methods within this. I have led a number of projects, including: the first UK options-appraisal of screening for ovarian cancer, evaluating pathway (service) re-design options for individuals with diabetes and depression, and the cost-effectiveness of treatments for peripheral arterial disease. I have worked for a variety of decision-makers and clients including The National Institute for Health and Care Excellence, the Department of Health, NHS Cancer Screening Programmes, and pharmaceutical companies. I have also employed a number of different health economic modelling methods, including: discrete event simulation; transition state modelling; Bayesian calibration and value of information analyses. Further, I have been involved in a number of different statistical analyses. These include: time series analysis; survival analysis; prevalence modelling; mediation analysis; and statistical process control.

I have been invited to provide talks at a number of international conferences. I peer-review funding applications to the NIHR and for a number of journals, including The Lancet, BMJ, and Health Technology Assessment.

I am the Health Economics and Decision Science lead for the ScHARR Information Governance Committee, and the deputy module lead for HAR6119: Building Cost-effectiveness Models for Health Technology Assessment (online)

Research Interests

  • The use of statistics in health economics.
  • Extrapolation and time-series analyses.
  • Survival analysis and model uncertainty.
  • Vascular disease, cancer, depression.
  • Chronic diseases, mental ill health, and their interactions.
  • The use of health economics for pathway (service) re-design.
  • Mathematical modelling, including simulation.

Teaching Interests

I teach (or have taught) students on the following courses:

  • HAR6119: Building Cost-effectiveness Models for Health Technology Assessment (Deputy module leader).
  • HAR6240: Health Service Research Methods
  • HAR6059: Informatics for Public Health
  • HAR667: Cost-effectiveness Modelling for Health Technology Assessment
  • HAR672: Advanced Simulation Methods
  • HAR669: Health Research Methods

I have also supervised Masters dissertations for the MSc Health Economics and Decision Modelling, the Master of Public Health (Management and Leadership), and the MSc Statistics with Medical Applications.
My teaching interests include:

  • The use of decision-analytical models (Decision Trees and Markov Models) in technology assessment.
  • Incorporating and evaluating uncertainty within decision-analytical models.
  • Uses of observational data and alternatives to randomised controlled trials. 

Current Projects

  • Cost-effectiveness of reconfiguring vascular services.
  • Appraisal of screening options for ovarian cancer.
  • Exploratory analysis of the impact of physical and mental morbidities on uptake of colorectal cancer screening. 
  • Whole pathway modelling of interventions for patients with diabetes and depression (For EEPRU).
  • I also work for ScHARR-TAG (technology assessment group).

Key Publications

Extended list of publications

Journal articles