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Basic population definition
You specify the patients you want to include in your dataset using the
define_population() method. For example, to include all patients born
in 1950 you would write something like this:
from ehrql import create_dataset
from ehrql.tables.core import patients
dataset = create_dataset()
dataset.define_population(patients.date_of_birth.year == 1950)
Combining multiple inclusion criteria
You can combine multiple inclusion criteria using the logical operators:
&(and)|(or)~(not)
For example, to include just men born in 1950 you could use the &
operator. This says that patients must match the date of birth criterion
and the sex criterion.
dataset.define_population(
(patients.date_of_birth.year == 1950) & (patients.sex == "male")
)
And, similarly you could include just women born in 1960 using:
dataset.define_population(
(patients.date_of_birth.year == 1960) & (patients.sex == "female")
)
To combine these populations together and include both men born in 1950
and women born in 1960 you could use the | operator. This says that
patients must match either the first condition or the second:
dataset.define_population(
((patients.date_of_birth.year == 1950) & (patients.sex == "male"))
| ((patients.date_of_birth.year == 1960) & (patients.sex == "female"))
)
!!! note "What's with all the parentheses?"
ehrQL requires more parentheses around logical operators than you
may be used to from other languages. This is a side-effect of the
way the Python language (in which ehrQL is implemented) happens to
work, but it is good practice in any case to be explicit about how
you expect logical operations to be grouped together. If you miss
out any required parentheses ehrQL should give you an error message
explaining how to fix your code.
Excluding patients from your dataset
To exclude patients matching a certain condition from your dataset you
can use the "and not" pattern. That is, you can write your population
definition in the form:
inclusion_criteria & ~exclusion_criteria
For example, to include patients born in 1950 and exclude patients
who died before 2020 you could write:
dataset.define_population(
(patients.date_of_birth.year == 1950) & ~(patients.date_of_death.year < 2020)
)