Model Transparency and Validation
By David M. Eddy, W. Hollingworth, J. Caro, J. Tsevat, Kathryn M. McDonald, John B. Wong. Medical decision making, 2012
553 citations recorded by the source corpus.
Trust and confidence are critical to the success of health care models. There are two main methods for achieving this: transparency (people can see how the model is built) and validation (how well it reproduces reality). This report describes recommendations for achieving transparency and validation, developed by a task force appointed by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM). Recommendations were developed iteratively by the authors. A nontechnical description should be made available to anyone—including model type and intended applications; funding sources; structure; inputs, outputs, other components that determine function, and their relationships; data sources; validation methods and results; and limitations. Technical documentation, written in sufficient detail to enable a reader with necessary expertise to evaluate the model and potentially reproduce it, should be made available openly or under agreements that protect intellectual property, at the discretion of the modelers. Validation involves face validity (wherein experts evaluate model structure, data sources, assumptions, and results), verification or internal validity (check accuracy of coding), cross validity (comparison of results with other models analyzing same problem), external validity (comparing model results to real-world results), and predictive validity (comparing model results with prospectively observed events). The last two are the strongest form of validation. Each section of this paper contains a number of recommendations that were iterated among the authors, as well as the wider modeling task force jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.
Subfields: Economics and Econometrics, General Health Professions
View Paper: https://www.semanticscholar.org/paper/a30de4d203da15156d565a63e6437501af9285ab
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- U. Siebert
- Andrew H. Briggs
- Karen M. Kuntz
- M. J. J. J. Jaime Caro
- PhD Alan Brennan
- MD Javier Mar
- PhD Jonathan Karnon
- MD CM Mph James Stahl
Citations in the corpus
- Modeling Using Discrete Event Simulation (2012, background): “Other articles in this series [1–6] describe best practices for conceptualizing models, building and applying other types of models, addressing uncertainty, and ensuring transparency and validity.”
- Modeling good research practices--overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--1. (2012, unknown): “[1–6] relates to the application of modeling techniques to the area”