External validation is the action of testing the original prediction model in a set of new patients to determine whether the model works to a satisfactory degree.
To assess whether a prediction model is accurate, demonstrating that it predicts the outcome in patients on whom the model was developed is not sufficient. As the prediction formula is tailored to the development data, a model may show excellent performance in the development population but perform poorly in an external cohort
External validation mainly provides evidence on the generalizability to various different patient populations. … It entails validating the model on new patients who were included in the same study as patients from the development cohort but sampled at an earlier or later time point.
For relatively small data sets, internal validation of prediction models by bootstrapping may not be sufficient and indicative for the model's performance in future patients. External validation is essential before implementing prediction models in clinical practice.