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A Rubric for Assessing Conformance to the Ten Rules for Credible Practice of Modeling and Simulation in HealthcareThe 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.
Document ID
20240003228
Acquisition Source
Glenn Research Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Alexandra Manchel ORCID
(Thomas Jefferson University Philadelphia, Pennsylvania, United States)
Ahmet Erdemir ORCID
(Cleveland Clinic Cleveland, Ohio, United States)
Lealem Mulugeta ORCID
(InSilico Labs LLC Houston, Texas)
Joy P Ku ORCID
(Stanford University Stanford, United States)
Bruno V Rego ORCID
(Louisiana State University Baton Rouge, United States)
Marc Horner ORCID
(Ansys (United States) Canonsburg, United States)
William W Lytton ORCID
(Kings County Hospital Center Brooklyn, New York, United States)
Jerry G Myers, Jr ORCID
(Glenn Research Center Cleveland, United States)
Rajanikanth Vadigepalli ORCID
(Thomas Jefferson University Philadelphia, Pennsylvania, United States)
Date Acquired
March 15, 2024
Publication Date
October 30, 2025
Publication Information
Publication: PLOS One
Publisher: Plos.org
ISSN: 1932-6203
URL: Plos.org
Subject Category
Aerospace Medicine
Mathematical and Computer Sciences (General)
Numerical Analysis
Funding Number(s)
CONTRACT_GRANT: U54EB020405
CONTRACT_GRANT: R01Gm12444301
CONTRACT_GRANT: P2C HD065690
CONTRACT_GRANT: R01EB024573
CONTRACT_GRANT: R01GM104139
CONTRACT_GRANT: R01EB009643
CONTRACT_GRANT: F31AA030214
CONTRACT_GRANT: OT2OD030534
CONTRACT_GRANT: R01HL161696
CONTRACT_GRANT: R01AA018873
WBS: 305041.01.02.10
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
Single Expert
Keywords
Credible Practice
Credibility
Healthcare
Models and Simulations