One thought that I have often had about prescription claims databases is that we often can't do anything with missing data. If a patient in such a database has undiagnosed hypertension, for example, it's unclear how to handle it. This is in stark contrast to cohort studies where a missing blood pressure reading is a clear case of missing data and straightforward multiple imputation may do wonders.
So I wonder if Andrew Gelman's idea for count data could be adapted for this purpose?
Or would we be buried by an excessive number of assumptions that might be required to make it work in these settings?