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Model Transparency and Validation: A Report of the ISPOR-SMDM Modeling Task Force-7

2012

This paper discusses how to improve trust in the use of health care models through validation and transparency.  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).

Recommendations are provided for nontechnical description (model type, intended applications, funding sources, structure, inputs, outputs, data sources, validation methods, results, and limitations) as well as technical documentation, which should be written in sufficient detail to enable a reader with necessary expertise to evaluate the model and potentially reproduce it.

This paper is one of a 7-part series of articles on modeling good research practices based on a collaboration between the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM).

The other articles include:

 

Source:

Eddy DM, Hollingworth W, Caro JJ et al. Model Transparency and Validation: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-7. Value in Health 2012; 15: 843-850. https://doi.org/10.1177/0272989X12454579