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

被引:200
|
作者
Eddy, David M. [1 ]
Hollingworth, William [2 ]
Caro, J. Jaime [3 ,4 ]
Tsevat, Joel [5 ,6 ]
McDonald, Kathryn M. [7 ]
Wong, John B. [8 ,9 ]
机构
[1] Archimedes Inc, San Francisco, CA 94105 USA
[2] Univ Bristol, Sch Social & Community Med, Bristol, Avon, England
[3] United BioSource Corp, Lexington, MA USA
[4] McGill Univ, Fac Med, Montreal, PQ, Canada
[5] Univ Cincinnati, Coll Med, Cincinnati, OH USA
[6] Cincinnati Vet Affairs Med Ctr, Cincinnati, OH USA
[7] Ctr Primary Care & Outcomes Res, Ctr Hlth Policy, Stanford, CA USA
[8] Tufts Med Ctr, Div Clin Decis Making Informat & Telemed, Boston, MA USA
[9] Tufts Univ, Sch Med, Boston, MA 02111 USA
关键词
decision making; best practices; modeling; simulation; transparency; validation; OPTIMAL SEARCH STRATEGIES; RETRIEVING SCIENTIFICALLY STRONG; COST-EFFECTIVENESS; REPRODUCIBLE RESEARCH; ANTIRETROVIRAL THERAPY; SIMULATION-MODELS; HIV; CANCER; ARCHIMEDES; DISEASE;
D O I
10.1016/j.jval.2012.04.012
中图分类号
F [经济];
学科分类号
02 ;
摘要
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 the model reproduces reality). This report describes recommendations for achieving transparency and validation developed by a taskforce appointed by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making. Recommendations were developed iteratively by the authors. A nontechnical description-including model type, intended applications, funding sources, structure, intended uses, inputs, outputs, other components that determine function, and their relationships, data sources, validation methods, results, and limitations-should be made available to anyone. 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 the same problem), external validity (comparing model results with 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 article contains a number of recommendations that were iterated among the authors, as well as among the wider modeling taskforce, jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.
引用
收藏
页码:843 / 850
页数:8
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