  A large volume of research has considered the creation of predictive models
for clinical data; however, much existing literature reports results using only
a single source of data. In this work, we evaluate the performance of models
trained on the publicly-available eICU Collaborative Research Database. We show
that cross-validation using many distinct centers provides a reasonable
estimate of model performance in new centers. We further show that a single
model trained across centers transfers well to distinct hospitals, even
compared to a model retrained using hospital-specific data. Our results
motivate the use of multi-center datasets for model development and highlight
the need for data sharing among hospitals to maximize model performance.
