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使用Python和网络应用程序提高开放式医疗服务提供模拟模型的可用性。

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

作者信息

Monks Thomas, Harper Alison

机构信息

University of Exeter Medical School, University of Exeter, Exeter, England, UK.

NIHR Applied Research Collaboration South West Peninsula, University of Exeter, Exeter, England, UK.

出版信息

NIHR Open Res. 2023 Dec 15;3:48. doi: 10.3310/nihropenres.13467.1. eCollection 2023.

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.

摘要

开放科学的一个目标是提高研究的可及性。在使用离散事件模拟的卫生服务研究中,诸如Python之类的免费和开源软件(FOSS)为研究团队提供了一种与其他研究人员和英国国家医疗服务体系(NHS)决策者共享其模型的方式。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,但使用和运行它可能需要专业技能。这不利于研究人员采用免费和开源软件以及开放科学实践。基于其他健康数据科学学科的工作,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,从而提高NHS以及其他学科的研究人员对研究的可及性。我们专注于部署为Streamlit网络应用程序的用Python编写的模型。为了增加这些方法的采用率,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,以便模型可以用于网络应用程序。该方法在离散事件模拟Python包中具有通用性,并且我们提供了一个简单紧急护理呼叫中心模型的simpy和ciw实现的代码。然后,我们提供了一个将模型链接到Streamlit网络应用程序界面的分步教程,以使其他健康数据科学研究人员能够重现和实施我们的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/11319905/ab4487995c36/nihropenres-3-14669-g0000.jpg

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