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Making health economic models Shiny: A tutorial

Wellcome open research, 2020, Vol.5, p.69 [Peer Reviewed Journal]

Copyright: © 2020 Smith R and Schneider P. ;2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Copyright: © 2020 Smith R and Schneider P 2020 ;ISSN: 2398-502X ;EISSN: 2398-502X ;DOI: 10.12688/wellcomeopenres.15807.2 ;PMID: 32904933

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  • Title:
    Making health economic models Shiny: A tutorial
  • Author: Smith, Robert ; Schneider, Paul
  • Subjects: Age ; Cost analysis ; Decision making ; Economic models ; Health economics ; Interfaces ; Method ; Open access ; Peer review ; Probability ; Programming languages ; Sensitivity analysis ; Simulation ; Software
  • Is Part Of: Wellcome open research, 2020, Vol.5, p.69
  • Description: 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.
  • Publisher: England: Wellcome Trust Limited
  • Language: English
  • Identifier: ISSN: 2398-502X
    EISSN: 2398-502X
    DOI: 10.12688/wellcomeopenres.15807.2
    PMID: 32904933
  • Source: Open Access: PubMed Central
    AUTh Library subscriptions: ProQuest Central
    DOAJ Directory of Open Access Journals
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