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Improving the usability of open health service delivery simulation models using Python and web apps

One aim of Open Science is to increase the accessibility of research. Within health services research that uses discrete-event simulation, Free and Open Source Software (FOSS), such as Python, offers a way for research teams to share their models with other researchers and NHS decision makers. Altho...

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Detalles Bibliográficos
Autores principales: Monks, Thomas, Harper, Alison
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593330/
https://www.ncbi.nlm.nih.gov/pubmed/37881450
http://dx.doi.org/10.3310/nihropenres.13467.1
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author Monks, Thomas
Harper, Alison
author_facet Monks, Thomas
Harper, Alison
author_sort Monks, Thomas
collection PubMed
description One aim of Open Science is to increase the accessibility of research. Within health services research that uses discrete-event simulation, Free and Open Source Software (FOSS), such as Python, offers a way for research teams to share their models with other researchers and NHS decision makers. Although the code for healthcare discrete-event simulation models can be shared alongside publications, it may require specialist skills to use and run. This is a disincentive to researchers adopting Free and Open Source Software and open science practices. Building on work from other health data science disciplines, we propose that web apps offer a user-friendly interface for healthcare models that increase the accessibility of research to the NHS, and researchers from other disciplines. We focus on models coded in Python deployed as streamlit web apps. To increase uptake of these methods, we provide an approach to structuring discrete-event simulation model code in Python so that models are web app ready. The method is general across discrete-event simulation Python packages, and we include code for both simpy and ciw implementations of a simple urgent care call centre model. We then provide a step-by-step tutorial for linking the model to a streamlit web app interface, to enable other health data science researchers to reproduce and implement our method.
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spelling pubmed-105933302023-10-25 Improving the usability of open health service delivery simulation models using Python and web apps Monks, Thomas Harper, Alison NIHR Open Res Method Article One aim of Open Science is to increase the accessibility of research. Within health services research that uses discrete-event simulation, Free and Open Source Software (FOSS), such as Python, offers a way for research teams to share their models with other researchers and NHS decision makers. Although the code for healthcare discrete-event simulation models can be shared alongside publications, it may require specialist skills to use and run. This is a disincentive to researchers adopting Free and Open Source Software and open science practices. Building on work from other health data science disciplines, we propose that web apps offer a user-friendly interface for healthcare models that increase the accessibility of research to the NHS, and researchers from other disciplines. We focus on models coded in Python deployed as streamlit web apps. To increase uptake of these methods, we provide an approach to structuring discrete-event simulation model code in Python so that models are web app ready. The method is general across discrete-event simulation Python packages, and we include code for both simpy and ciw implementations of a simple urgent care call centre model. We then provide a step-by-step tutorial for linking the model to a streamlit web app interface, to enable other health data science researchers to reproduce and implement our method. F1000 Research Limited 2023-10-05 /pmc/articles/PMC10593330/ /pubmed/37881450 http://dx.doi.org/10.3310/nihropenres.13467.1 Text en Copyright: © 2023 Monks T and Harper A https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Method Article
Monks, Thomas
Harper, Alison
Improving the usability of open health service delivery simulation models using Python and web apps
title Improving the usability of open health service delivery simulation models using Python and web apps
title_full Improving the usability of open health service delivery simulation models using Python and web apps
title_fullStr Improving the usability of open health service delivery simulation models using Python and web apps
title_full_unstemmed Improving the usability of open health service delivery simulation models using Python and web apps
title_short Improving the usability of open health service delivery simulation models using Python and web apps
title_sort improving the usability of open health service delivery simulation models using python and web apps
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593330/
https://www.ncbi.nlm.nih.gov/pubmed/37881450
http://dx.doi.org/10.3310/nihropenres.13467.1
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