For Topic #1 and #3, I’d like to offer a Option 4 (which I am not
necessarily endorsing but want to put it on the table, as I have reviewed
with @schuemie, @Rijnbeek, @mdewilde in discussions about the IPCI
database):
-
continue to preserve ‘observation period’ under its current definition of
the spans of time that a data source is expected to capture data about an
individual, such that the logic continues to hold that presence of a record
indicates its occurrence, and absence of a record can be inferred to
indicate that it did not occur (subject to misclassification error). -
change the existing convention that data that has timestamps falling
outside of an observation period should be removed from the CDM,
effectively allowing any data source to make their own decision about
whether or not to maintain data that occurs before or after the observation
period start and end dates.
This would represent a non-breaking change to any of the current OHDSI
tools, since all respect the observation period time when conducting
analyses. But it opens up the opportunity to expand options for applying
inclusion criteria and building covariates by looking back in the time
outside of observation period, under the revised logic that presence of a
record may indicate its occurrence (subject to misclassification) but
absence of a record tells you nothing about the presence or absence of its
occurrence in the time outside of the observation period. Under this
logic, data outside of an observation period should continue to not be
allowed to define initial events to define cohorts, and all
incidence/prevalence estimates should continue to be limited to observation
period time.
This proposal would mean we wouldn’t need new observation period types or
to create breaking changes with overlapping periods (option 3). It also
would mean ETLs would be easier because data outside period would not
longer require being transformed into ‘history of’ observation records
(option1/2).