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一份用于评估是否符合医疗保健领域建模与仿真可信实践十条规则的评分标准。

A rubric for assessing conformance to the Ten Rules for credible practice of modeling and simulation in healthcare.

作者信息

Manchel Alexandra, Erdemir Ahmet, Mulugeta Lealem, Ku Joy P, Rego Bruno V, Horner Marc, Lytton William W, Myers Jerry G, Vadigepalli Rajanikanth

机构信息

Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America.

Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, Maryland United States of America.

出版信息

PLoS One. 2025 Jun 25;20(6):e0313711. doi: 10.1371/journal.pone.0313711. eCollection 2025.

Abstract

The power of computational modeling and simulation (M&S) is realized when the results are credible, and the workflow generates evidence that supports credibility for the context of use. The Committee on Credible Practice of Modeling & Simulation in Healthcare was established to help address the need for processes and procedures to support the credible use of M&S in healthcare and biomedical research. Our community efforts have led to the Ten Rules (TR) for Credible Practice of M&S in life sciences and healthcare. This framework is an outcome of a multidisciplinary investigation from a wide range of stakeholders beginning in 2012. Here, we present a pragmatic rubric for assessing the conformance of an M&S activity to the TR. This rubric considers the ability of an M&S study to communicate how well the study conforms to the Ten Rules for credible practice and facilitate outreach to a wide range of stakeholders from context-specific M&S practitioners to policymakers. It uses an ordinal scale ranging from Insufficient (zero) to Comprehensive (four) that is applicable to each rule, providing a uniform approach for comparing assessments across different reviewers and different modeling studies. We used the rubric to evaluate the conformance of two computational modeling activities: 1. six viral disease (COVID-19) propagation models, and 2. a model of hepatic glycogenolysis with neural innervation and calcium signaling. These examples were used to evaluate the applicability of the rubric and illustrate rubric usage in real-world M&S scenarios including those that bridge scientific M&S with policymaking. The COVID-19 M&S studies were of particular interest because they needed to be quickly operationalized by government and private decision-makers early in the COVID-19 pandemic and were accessible as open-source tools. Our findings demonstrate that the TR rubric represents a systematic tool for assessing the conformance of an M&S activity to codified good practices and enhances the value of the TR for supporting real-world decision-making.

摘要

当计算建模与仿真(M&S)的结果可信,且其工作流程能产生支持在使用场景中可信度的证据时,其强大作用才能得以实现。医疗保健领域建模与仿真可信实践委员会的成立,旨在满足对支持在医疗保健和生物医学研究中可信使用M&S的流程和程序的需求。我们的社区努力促成了生命科学和医疗保健领域M&S可信实践的十条规则(TR)。该框架是始于2012年众多利益相关者进行多学科调查的成果。在此,我们提出一个实用的评分标准,用于评估M&S活动与TR的符合程度。该评分标准考虑了M&S研究传达其符合可信实践十条规则程度的能力,并促进与从特定场景的M&S从业者到政策制定者等广泛利益相关者的沟通。它使用从不足(零分)到全面(四分)的序数尺度,适用于每条规则,为比较不同评审人员和不同建模研究的评估提供了统一方法。我们使用该评分标准评估了两个计算建模活动:1. 六个病毒性疾病(COVID-19)传播模型,以及2. 一个具有神经支配和钙信号传导的肝糖原分解模型。这些例子用于评估评分标准的适用性,并说明在包括将科学M&S与政策制定相联系的实际M&S场景中评分标准的使用。COVID-19的M&S研究尤其受关注,因为在COVID-19大流行初期,政府和私营决策者需要迅速将其投入使用,并且这些研究可作为开源工具获取。我们的研究结果表明,TR评分标准是评估M&S活动符合编纂的良好实践程度的系统工具,并提高了TR在支持实际决策方面的价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5324/12192136/ccc0f09a9ab9/pone.0313711.g001.jpg

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