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Health economic decision modelling

We develop decision analytical models in R. We have experience with all sorts of models, ranging from simple decision trees and Markov models, to sophisticated individual patient simulations. We are also happy to help you figure out what kind of model best fits your decision problem, and/or implement more advanced analytical methods, such as value of information, or calibration. (Why R?)

MS Excel → R

Do you have an old, clunky decision model in MS Excel that could do with a turbo boost? Or do you want to upgrade a model and run computationally expensive analyses (like EVPPI)? We 'translate' your model into R, make it faster, easier to use, with a clear documentation, that ensures that it can be easily maintained and updated in the future.

Interactive user-interfaces

Our particular area of expertise is in the creation of bespoke interactive user-interfaces for health economic models constructed in R and data dashboards. We work in short sprints and in close collaboration with you to develop interfaces that are intuitive and easy to use for your target audience.


The biggest barrier to adoption of R is the lack of familiarity of health economists, who have been working in Excel for years.

We provide short courses and workshops to get you up to speed with health economic modelling in R and to set up a modern, collaborative working environment. Previous courses included:

  • R for Health Research (link to online course)
  • R and R-Shiny for Health Economic Evaluation
  • Building custom state transition models in R

We adapt the sessions to meet the requirements of the group, and tailor the case studies to your interests - please get in touch to discuss your training needs.


We are keen to collaborate on interesting research projects that involve the application of data science methods to inform decision making. Previous projects range from the application of a spatial optimization algorithm and data dashboard creation, to the development of a new method of estimating the benefits of physical activity in heterogeneous populations for the WHO. For futher details, see list below.

  • Smith, R., Thomas, C. Squires, H., Götschi, T., Kahlmeier, S., Goyder, E. 2021. The price of precision: trade-offs between usability and validity in the WHO Health Economic Assessment Tool for walking and cycling. Public Health. https://doi.org/10.1016/j.puhe.2021.03.016
  • Schneider, P., 2020. Social tariffs and democratic choice–do population-based health state values reflect the will of the people? Health Economics. https://doi.org/10.1002/hec.4179
  • Smith, R and Schneider, P. 2020. Making health economic models Shiny: A tutorial. Wellcome Open Research, 5:69. https://doi.org/10.12688/wellcomeopenres.15807.2
  • Smith, R.A., Schneider, P.P., Cosulich, R., Quirk, H., Bullas, A.M., Haake, S.J. and Goyder, E., 2021. Socioeconomic inequalities in distance to and participation in a community-based running and walking activity: A longitudinal ecological study of parkrun 2010 to 2019. Health & Place, 71, p.102626. https://doi.org/10.1016/j.healthplace.2021.102626
  • Schneider, P.P., van Gool, C.J., Spreeuwenberg, P., Hooiveld, M., Donker, G.A., Barnett, D.J. and Paget, J., 2020. Using web search queries to monitor influenza-like illness: an exploratory retrospective analysis, Netherlands, 2017/18 influenza season. Eurosurveillance, 25(21), p.1900221.https://doi.org/10.2807/1560-7917.ES.2020.25.21.1900221
  • Schneider, P.P., Smith, R.A., Bullas, A.M., Bayley, T., Haake, S.S., Brennan, A. and Goyder, E. 2020. Multiple deprivation and geographic distance to community physical activity events — achieving equitable access to parkrun in England. Journal of Public Health. 48;53(189). https://doi.org/10.1016/j.puhe.2020.09.002
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  • Carr, K., Donaldson, C., Wildman, J., Smith, R., & Vernazza, C. 2021. ‘An Examination of Consistency in the Incremental Approach to Willingness to Pay: Evidence Using Societal Values for NHS Dental Services’, Medical Decision Making. https://doi.org/10.1177/0272989x21996329.
  • Schneider PP, Pouwels XG, Passos VL, Ramaekers BL, Geurts SM, Ibragimova KI, de Boer M, Erdkamp F, Vriens BE, van de Wouw AJ, den Boer MO. Variability of cost trajectories over the last year of life in patients with advanced breast cancer in the Netherlands. Plos one. 2020 Apr 9;15(4):e0230909. https://doi.org/10.1371/journal.pone.0230909
  • Smith, R., Schneider, P., Bullas, A., Haake, S., Quirk, H., Cosulich, R. and Goyder, E., 2020. Does ethnic density influence community participation in mass participation physical activity events? The case of parkrun in England. Wellcome Open Research, 5(9), p.9. https://doi.org/10.12688/wellcomeopenres.15657.2
  • Schneider PP, van Gool CJ, Spreeuwenberg P, Hooiveld M, Donker GA, Barnett DJ, Paget J. Using digital epidemiology methods to monitor influenza-like illness in the Netherlands in real-time: the 2017-2018 season. Eurosurveillance. 2020. https://doi.org/10.1101/440867
  • Bates, S., Bayley, T., Norman, P., Breeze, P. and Brennan, A., 2020. A Systematic Review of Methods to Predict Weight Trajectories in Health Economic Models of Behavioral Weight-Management Programs: The Potential Role of Psychosocial Factors. Medical Decision Making, 40(1), pp.90-105. https://doi.org/10.1177/0272989x19889897
  • Bates, S., Reeve, B. and Trevena, H., 2020. A narrative review of online food delivery in Australia: challenges and opportunities for public health nutrition policy. Public Health Nutrition, pp.1-11. http://dx.doi.org/10.1017/S1368980020000701
  • Schneider PP, Smith RA, Bullas AM, Bayley T, Haake SSJ, Brennan A, Goyder E. Identifying Optimal Locations for Maximising Access to parkrun – Interactive online map. 2019. (website)
  • Smith, R. (2018). An analysis of the HEAT tool method for valuing the benefits of physical activity. HEAT Team Internal Report. World Health Organisation Regional Office for Europe.
  • Schneider PP, Geraedts M. Staffing and the incidence of pressure ulcers in German hospitals: A multicenter cross-sectional study. Nursing Health Sciences. 2016. http://dx.doi.org/10.4126/FRL01-006402986

We are keen advocates of the Open Science Movement. Whenever projects do not involve sensitive information, we make all data and code available for reuse and modification. Our projects have been successfully replicated in RepoHack events, and won Open Science Prizes. Please see our Github accounts for details.

  • 7th Sept 2022 - EARL Conference - Living HTA: Automating HTA with R. Slides here
  • 21st May 2022 - R-HTA Conference - Living HTA: Automating HTA with R R for HTA 2022 Workshop - Rob Smith Full talk
  • 18th May 2022 - University of Sheffield Guest Talk - Living HTA: Automating HTA with R Slides here
  • 23rd February 2022 R-HTA LMIC Conference - The potential of RShiny User Interfaces to Support Health Economic Decision Making Slides here
  • 10 February 2022 Erasmus MC, Netherlands - Making Erasmus MC Shiny Slides here
  • 1st July 2021 - R-HTA Conference - Rise and Shiny: A new dawn for HTA. Slides here
  • 25th June 2021 - University of Sheffield - Shiny for HTA. Slides here
  • 17th June 2021 - University of Leeds - The greatest possible impact: The Wellcome Trust and open research.Slides here
  • 10th March 2021 - World Health Organization - HEAT EAG - Valuing premature deaths averted vs life years saved.
  • 20th November 2020- Wellcome blog. Ready to run: Community participation in parkrun. Blog here
  • 11th November 2020 - NHS-R Virtual Conference. Making Health Economics Shiny - Slides here.
  • 20th October 2020 - Sheffield University Library. Open Research with the Wellcome Trust. Slides here. Slides here
  • 27th August 2020 - 'Free Weekly Timed' podcast - parkrun research collaboration. podcast link (Rob is at 22:45-40:00)
  • 10th August 2020 - ScHARR, University of Sheffield - Use of R for Health Research. course website here
  • 26th June 2020 - R-HTA (UCL) - Markov Models in Shiny. webpage here
  • 28th February 2020 - University of Sheffield - Making Health Economic Evaluation Models Shiny (workshop). Slides here
  • 4th February 2020 - Sheffield-R group- R for decision science (presentation). Slides here
  • 24th January 2020 - Market Access Consultancy - Use of R-Shiny for HTA applications (workshop).


Shiny UI and R Model Review

"I am not sure I can think of anything that we could have done better in this project – to be honest it went remarkably smoothly from the outset and you were very responsive to all our queries. Given the overall outcome for [the client], the project was a barnstorming success – so thank you for your support!".

Bespoke R for HTA Online Course

"I very much enjoyed the course and really appreciated the efforts of the leaders to look into questions/add in extra material in between sessions to make the course as tailored and relevant to us as possible - you definitely exceeded expectations in this respect. Thank you!"

Individual patient simulation with UI

"[The client] was very impressed and liked it ! There are a couple of things arising, one being that they liked it so much they were wondering about converting the other model(s) into a similar format. [...]"

"They were super impressed !"

R4ScHARR online course

"Really accessible, loved the format of the website with practice questions. This made it far less daunting for a complete beginner like myself".

"The examples were very good to work through. Clear explanation. Lots of chances to ask questions. Really very well run".


Dr Paul Schneider

Paul is a health scientist based in Bochum, Germany. Trained as a medical doctor and epidemiologist, he combines a deep domain knowledge with strong technical skills in data science, programming, and decision modelling. His main research interest is currently in the valuation of health benefits for economic evaluations and the interpersonal comparability of preferences. He is a keen advocate of open science practices.

Robert Smith

Rob is a health economist based in Sheffield, UK. His research focuses on the methods used to estimate the costs and benefits of public health interventions, with a specific interest in microsimulation modelling in R. He is a expert advisor in Public Health Economics & Decision Science to the WHO-HEAT project. He is currently working at the Joint Biosecurity Centre to help inform the UK government response to the pandemic.

Dr Sarah Bates

Sarah is a health economist with a background in health psychology based in Sheffield, UK . Her research focuses on the inclusion of psychological indicators within complex health economic models. She has experience working with a wide range of stakeholders and building complex microsimulation models in R.

Shangshang Gu

Shang joined Dark Peak Analytics in 2022. She has a MSc in Health Economics from the University of York, and has previously worked as a Health Economics Consultant for Amaris Consulting in Shanghai, MSD in Budapest and The University of Sheffield. Shang is currently building an Agent Based Model to better understand the role of social networks on alcohol drinking behaviour.

Wael Mohammed

Wael is a health economist with a background in pharmacy and public health. In addition, he has experience in decision-analytic modelling, econometrics, and data science. He is currently pursuing a PhD in public health, economics and decision science at the University of Sheffield.



Dark Peak Analytics Limited
Sheffield, England

The Dark Peak is the higher and wilder part of the Peak District near Sheffield in England. It is famed for its desolate and exposed tracts of moorland top, and the open undulating high gritstone plateau with extensive blanket peat covered by cottongrass bog and heather moorland.