Cargando…
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...
Autores principales: | , |
---|---|
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 |
_version_ | 1785124428262146048 |
---|---|
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. |
format | Online Article Text |
id | pubmed-10593330 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT monksthomas improvingtheusabilityofopenhealthservicedeliverysimulationmodelsusingpythonandwebapps AT harperalison improvingtheusabilityofopenhealthservicedeliverysimulationmodelsusingpythonandwebapps |