Created 2 data set definition (1 to add specific variables and 2 to a…

…dd a group of variables) + added actions to the project pipeline to add both case definitions

analysis/dataset_definition_all_var.py

@@ -0,0 +1,37 @@
+from ehrql import create_dataset
+from ehrql.tables.tpp import patients, practice_registrations
+
+#import function for clinical variables
+from variables_function import *
+
+# initialise dataset
+
+dataset = create_dataset()
+
+# Index date (choose a date)
+index_date = "2020-03-31"
+#Dummy data
+dataset.configure_dummy_data(population_size=1000)
+
+#Data set definition
+registered_patients = practice_registrations.for_patient_on(index_date)
+registered = registered_patients.exists_for_patient()
+
+alive = (patients.date_of_death> index_date) | patients.date_of_death.is_null()
+
+# define dataset poppulation
+dataset.define_population(
+  registered 
+  & alive
+)
+
+# Add groups of variables
+#Demographic
+demographic_variables(dataset = dataset, index_date = index_date)
+
+#Primis variables
+primis_variables(dataset = dataset, index_date = index_date)
+
+#Clinical variables
+other_cx_variables(dataset = dataset, index_date = index_date)
+

analysis/dataset_definition_spec_var.py

@@ -0,0 +1,63 @@
+
+from ehrql import create_dataset
+from ehrql.tables.tpp import patients, practice_registrations
+
+#import function for clinical variables
+from variables_function import *
+
+#Import codelists
+from codelists import *
+
+# initialise dataset
+
+dataset = create_dataset()
+
+# Index date (choose a date)
+index_date = "2020-03-31"
+
+#Dummy data
+dataset.configure_dummy_data(population_size=1000)
+
+#Data set definition
+registered_patients = practice_registrations.for_patient_on(index_date)
+registered = registered_patients.exists_for_patient()
+
+alive = (patients.date_of_death> index_date) | patients.date_of_death.is_null()
+
+# define dataset poppulation
+dataset.define_population(
+  registered 
+  & alive
+)
+
+
+# Add specific variables
+
+# demographic variables
+dataset.age= patients.age_on(index_date)
+dataset.region= registered_patients.practice_nuts1_region_name
+dataset.stp= registered_patients.practice_stp
+dataset.imd= addresses.for_patient_on(index_date).imd_rounded
+dataset.ethn_16= last_prior_event(ethnicity_codelist16, index_date).snomedct_code.to_category(ethnicity_codelist16)
+dataset.ethn_5= last_prior_event(ethnicity_codelist5, index_date).snomedct_code.to_category(ethnicity_codelist5)
+
+# PRIMIS variables:
+dataset.crd= has_prior_event(resp_cov, index_date) #chronic respiratory disease
+dataset.ast= has_asthma(index_date) #asthma
+dataset.chd= has_prior_event(chd_cov, index_date) #chronic heart disease
+dataset.ckd= has_ckd(index_date) #chronic kidney disease
+dataset.cld= has_prior_event(cld, index_date) # chronic liver disease
+dataset.cns= has_prior_event(cns_cov, index_date) # chronic neurological disease
+dataset.learndis= has_prior_event(learndis, index_date) # learning Disability
+dataset.diab= has_diab(index_date) #diabetes
+dataset.immuno= is_immunosuppressed(index_date) #immunosuppress grouped
+dataset.asplen= has_prior_event(spln_cov, index_date) # asplenia or dysfunction of the Spleen
+dataset.obes= has_sev_obes(index_date) #immunosuppress grouped
+dataset.sev_ment= has_sev_mental(index_date) #severe mental illness
+dataset.one_primis= at_least_one_primis(index_date) #at least one primis
+
+## others cx variables of interest
+dataset.sol_org_trans= has_prior_event(solid_organ_transplant, index_date) # Organs transplant
+dataset.hiv= has_prior_event(hiv_aids, index_date) #HIV/AIDS
+dataset.cancer= has_prior_event(cancer_nonhaem_snomed, index_date, where=clinical_events.date.is_after(index_date - days(int(3 * 365.25))))|has_prior_event(cancer_haem_snomed, index_date, where=clinical_events.date.is_after(index_date - days(int(3 * 365.25))))
+

project.yaml

@@ -1,8 +1,14 @@
 version: '4.0'
 
 actions:
-  generate_dataset:
-    run: ehrql:v1 generate-dataset analysis/dataset_definition.py --output output/dataset.csv.gz
+  generate_dataset_all_var:
+    run: ehrql:v1 generate-dataset analysis/dataset_definition_all_var.py --output output/dataset_all.csv.gz
     outputs:
       highly_sensitive:
-        dataset: output/dataset.csv.gz
+        dataset: output/dataset_all.csv.gz
+
+  generate_dataset_spec_var:
+    run: ehrql:v1 generate-dataset analysis/dataset_definition_spec_var.py --output output/dataset_spec.csv.gz
+    outputs:
+      highly_sensitive:
+        dataset: output/dataset_spec.csv.gz