Smith, R. and Schneider, P. orcid.org/0000-0003-3552-1087 (2020) Making health economic models Shiny: A tutorial. Wellcome Open Research, 5. 69. ISSN 2398-502X
Abstract
Health economic evaluation models have traditionally been built in Microsoft Excel, but more sophisticated tools are increasingly being used as model complexity and computational requirements increase. Of all the programming languages, R is most popular amongst health economists because it has a plethora of user created packages and is highly flexible. However, even with an integrated development environment such as R Studio, R lacks a simple point and click user interface and therefore requires some programming ability. This might make the switch from Microsoft Excel to R seem daunting, and it might make it difficult to directly communicate results with decisions makers and other stakeholders.
The R package Shiny has the potential to resolve this limitation. It allows programmers to embed health economic models developed in R into interactive web browser based user interfaces. Users can specify their own assumptions about model parameters and run different scenario analyses, which, in the case of regular a Markov model, can be computed within seconds. This paper provides a tutorial on how to wrap a health economic model built in R into a Shiny application. We use a four-state Markov model developed by the Decision Analysis in R for Technologies in Health (DARTH) group as a case-study to demonstrate main principles and basic functionality.
A more extensive tutorial, all code, and data are provided in a GitHub repository.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Smith R and Schneider P. This is an open access article distributed under the terms of the Creative Commons Attribution License, (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Health Economics; R; RShiny; Decision Science |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) |
Funding Information: | Funder Grant number Wellcome Trust 108903/B/15/Z |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Aug 2020 13:10 |
Last Modified: | 14 Aug 2020 13:10 |
Status: | Published |
Publisher: | F1000 Research Ltd |
Refereed: | Yes |
Identification Number: | 10.12688/wellcomeopenres.15807.2 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:164413 |
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