OBJECTIVES: Performing face validation and internal validation of health economic models is recommended by various guidelines, including ISPOR, in model development and is essential in determining a model’s credibility.  Using third parties – individuals outside of the model building process with no stake in model results – is considered a best practice when conducting these validations.  Yet the rate at which published models follow this practice is unknown.  This study reviews the extent to which third parties were reported used to conduct face and internal validity in published literature. METHODS: The study reviewed 100 health economic models chosen randomly from published peer-reviewed health economic literature within the last eight years.  Decision analysis, Markov models, and discrete event simulation models were included in the review.   Each model was reviewed to determine the extent to which face validation and internal validation were performed.  Next, it was noted if these validations were performed by third parties.  Surveys were conducted with a subsample of models not reporting validation to determine if: 1) validation was performed but not reported; 2) if unreported validation was performed by a third party; 3) any reason(s ) for not performing validation; and 4) reasons for not using third parties. RESULTS:   Third party face validation and internal validation were each reported in less than one-third of the studies reviewed.  Survey results also found that third party validation was seldom performed.  Reasons for not performing third party validations included:  believing that third party validation was not necessary, time constraints, and budget constraints. CONCLUSIONS: While considered a best practice, third party face and internal validations are seldom performed on published economic models.  Creating more awareness regarding this best practice may increase utilization of third parties.  Finding ways to perform these validations in a less costly and more timely manner may increase usage as well.