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

NIHR open research Pub Date : 2023-12-15 eCollection Date: 2023-01-01 DOI:10.3310/nihropenres.13467.1
Thomas Monks, Alison Harper
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Abstract

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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使用Python和web应用程序提高开放式医疗服务提供模拟模型的可用性。
开放科学的一个目的是增加研究的可及性。在使用离散事件模拟的医疗服务研究中,Python等自由开源软件为研究团队提供了一种与其他研究人员和NHS决策者共享模型的方式。尽管医疗保健离散事件模拟模型的代码可以与出版物一起共享,但它可能需要专业技能才能使用和运行。这阻碍了研究人员采用自由开源软件和开放科学实践。在其他健康数据科学学科的工作基础上,我们建议网络应用程序为医疗保健模型提供一个用户友好的界面,增加NHS和其他学科研究人员的研究可访问性。我们专注于用Python编码的模型,这些模型被部署为流媒体web应用程序。为了增加对这些方法的理解,我们提供了一种在Python中构建离散事件模拟模型代码的方法,以便模型可以为web应用程序做好准备。该方法在离散事件模拟Python包中是通用的,我们包括简单紧急护理呼叫中心模型的simpy和ciw实现的代码。然后,我们提供了一个循序渐进的教程,将模型链接到流媒体网络应用程序界面,使其他健康数据科学研究人员能够复制和实现我们的方法。
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