Document Type
Article
Publication Date
6-25-2025
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.
Recommended Citation
Manchel, Alexandra; Erdemir, Ahmet; Mulugeta, Lealem; Ku, Joy; Rego, Bruno; Horner, Marc; Lytton, William; Myers, Jerry; and Vadigepalli, Rajanikanth, "A Rubric for Assessing Conformance to the Ten Rules for Credible Practice of Modeling and Simulation in Healthcare" (2025). Computational Medicine Center Faculty Papers. Paper 62.
https://jdc.jefferson.edu/tjucompmedctrfp/62
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.
PubMed ID
40560895
Language
English


Comments
This article is the author's final published version in PLOS ONE, Volume 20, Issue 6, June 2025, e0313711.
The published version is available at https://doi.org/10.1371/journal.pone.0313711.
Copyright © 2025 Manchel et a.