Dark Peak Analytics presents…

Making Health Economic Models Shiny

A short course on building web-based user interfaces for health economic models in shiny, the popular open source R package.

Master R shiny for Health Economics

This course teaches delegates to create interactive web applications for health economic models. It shows how to develop robust and fast decision models, and deploy shiny user-interfaces written in R.

Our expert instructors will guide you through a step-by-step journey based on peer reviewed literature.

The courses consists of taught sessions, live code walkthroughs, and hands-on exercises. It comes with a detailed coursebook and an extensive code-base.

You’ll have the chance to ask questions in a friendly and supportive atmosphere throughout the course and at our dedicated drop-in code clinics.

Course content

  • Assuming no prior knowledge of shiny, these sessions guide delegates through the process of building and deploying a shiny application using R and RStudio. Delegates will be able to link user-inputs to an algorithm run on the server side and display visuals back to users. They will be able to customize the aesthetics of the application to suit their needs, and deploy their application online for others to access via URL.

  • Delegates will learn how to build a bespoke state transition model (Markov model) from scratch in R and RStudio. The course will cover matrix multiplication, iteration, custom functions, one way sensitivity analysis, probabilistic sensitivity analysis, value of information and economically justifiable pricing analysis.

  • These sessions will combine the skills learnt in the previous parts of the course to build a user-interface which allows users to interact with a health economic evaluation model written in R software environment. Delegates will be able to customize the model (four state markov model) and control what parameters (and the range) that users can see and the outputs that are generated in the user-interface.

    By the end of the course delegates will have deployed their health economic model on a remote server with a user-interface to allow stakeholders to interact with the model.

Delegates will receive our teaching materials including an online coursebook, code examples, exercises and solutions. They will be able to ask questions throughout the sessions and during the four drop-in code clinics where any R / health economics related questions will be answered by our expert team.

Course tutors

  • Dr Paul Schneider

    Paul works on conceptual and methodological problems in valuing health outcomes in economic evaluations.

  • Dr Robert Smith

    Rob works on the application of methods to improve the usability and transparency of health economic decision models.

  • Dr Sarah Bates

    Sarah works on incorporating psychological indicators into health economic decision models in diabetes.

  • Really accessible, loved the content with practice questions. This made it far less daunting for a complete beginner like myself.

    Delegate from NHS Scotland

  • The course delivery has been great! I particularly appreciate the live and updated content and the accompanying coursebook.

    Delegate from GSK

  • It was easy to follow, every material was easily accessible and it was structured in a very manageable way.

    Delegate from University of Sheffield

Dates

The online course sessions are held on four consecutive Thursdays in September and October 2024:

  1. Thursday, 12 September 2024

  2. Thursday, 19 September 2024

  3. Thursday, 26 September 2024

  4. Thursday, 03 October 2024

Each session runs from:

13:00 - 16:00 GMT (London time)
08:00 - 11:00 EST (New York time)
17:00 - 20:00 GST (Dubai time)

PLUS: optional drop-in code clinics are held on Tuesdays:

  1. Tuesday, 17 September 2024

  2. Tuesday, 24 September 2024

  3. Tuesday, 01 October 2024

  4. Tuesday, 08 October 2024

Each code clinic runs from:

13:00 - 14:30 GMT (London time)
08:00 - 09:30 EST (New York time)
17:00 - 18:30 GST (Dubai time)

Book your space now

If you have any further queries or would like to book a bespoke course for a large group please contact us at contact@darkpeakanalytics.com and we will be happy to help!