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Job request: 24809

Organisation:
NHS England
Workspace:
adhd-pre-and-post-covid
ID:
bfm72bozho47wdnz
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Kin Quan requested one or more actions to be run against real patient data within a secure environment.

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level the outputs were written to.

The output security levels are:

  • highly_sensitive
    • Researchers can never directly view these outputs
    • Researchers can only request code is run against them
  • moderately_sensitive
    • Can be viewed by an approved researcher by logging into a highly secure environment
    • These are the only outputs that can be requested for public release via a controlled output review service.

Jobs

Pipeline

Show project.yaml 
version: '3.0'

# Ignore this`expectation` block. It is required but not used, and will be removed in future versions.
expectations:
  population_size: 5000

actions:
#   generate_dataset:
#     run: > 
#       ehrql:v1 generate-dataset analysis/dataset_definition_dx_to_med_time.py
#       --output output/adhd_dataset.csv.gz
#     outputs:
#       highly_sensitive:
#         adhd_dataset: output/adhd_dataset.csv.gz

#   generate_output_table:
#     run: python:v2 python analysis/calculate_time_diff_from_dx_to_med.py
#     needs: [generate_dataset]
#     outputs:
#       moderately_sensitive:
#         table1: output/adhd_dia_med_gap_weeks.csv
  
#   generate_adhd_prevalence:
#     run: > 
#       ehrql:v1 generate-measures analysis/measures_definition.py 
#       --output output/adhd_prevalence.csv
#     outputs:
#       moderately_sensitive:
#         measure: output/adhd_prevalence.csv

#   thin_slice_medication: 
#     run: > 
#       ehrql:v1 generate-measures analysis/medication_thin_slice_measures.py
#       --output output/thin_slice_medication_measures.csv 
#     outputs:
#       moderately_sensitive:
#         measure: output/thin_slice_medication_measures.csv

  Table_2_Prevalence_of_ADHD_Diagnosis:
    run: > 
      ehrql:v1 generate-measures analysis/Table_2_Prevalence_of_ADHD_Diagnosis.py
      --output output/Table_2_Prevalence_of_ADHD_Diagnosis.csv
    outputs:
      moderately_sensitive:
        measure: output/Table_2_Prevalence_of_ADHD_Diagnosis.csv

  # Table_2_Prevalence_of_ADHD_Remission:
  #   run: > 
  #     ehrql:v1 generate-measures analysis/Table_2_Prevalence_of_ADHD_Remission.py 
  #     --output output/Table_2_Prevalence_of_ADHD_Remission.csv
  #   outputs:
  #     moderately_sensitive:
  #       measure: output/Table_2_Prevalence_of_ADHD_Remission.csv

  Patient_table_3_rolling_6month_incident:
    run: > 
      ehrql:v1 generate-dataset analysis/Patient_table_3_rolling_6month_incident.py
      --output output/Patient_table_3_rolling_6month_incident.csv.gz
    outputs:
      highly_sensitive:
        measure: output/Patient_table_3_rolling_6month_incident.csv.gz

  Table_3_rolling_6_month_medication:
    run: python:v2 python analysis/Table_3_rolling_6_month_medication.py
    needs: [Patient_table_3_rolling_6month_incident]
    outputs:
      moderately_sensitive:
        table1: output/Table_3_rolling_6_month_medication.csv

  Table_3_with_ADHD_that_are_prescribed_ADHD_medication:
    run: > 
      ehrql:v1 generate-measures analysis/Table_3_with_ADHD_that_are_prescribed_ADHD_medication.py
      --output output/Table_3_with_ADHD_that_are_prescribed_ADHD_medication.csv 
    outputs:
      moderately_sensitive:
        measure: output/Table_3_with_ADHD_that_are_prescribed_ADHD_medication.csv
  
  Table_3_without_ADHD_that_are_prescribed_ADHD_medication:
    run: > 
      ehrql:v1 generate-measures analysis/Table_3_without_ADHD_that_are_prescribed_ADHD_medication.py
      --output output/Table_3_without_ADHD_that_are_prescribed_ADHD_medication.csv 
    outputs:
      moderately_sensitive:
        measure: output/Table_3_without_ADHD_that_are_prescribed_ADHD_medication.csv

  Table_3_are_prescribed_ADHD_medication_in_ADHD_group:
    run: > 
      ehrql:v1 generate-measures analysis/Table_3_are_prescribed_ADHD_medication_in_ADHD_group.py
      --output output/Table_3_are_prescribed_ADHD_medication_in_ADHD_group.csv 
    outputs:
      moderately_sensitive:
        measure: output/Table_3_are_prescribed_ADHD_medication_in_ADHD_group.csv

  # Table_3_with_ADHD_that_are_NOT_prescribed_ADHD_medication:
  #   run: > 
  #     ehrql:v1 generate-measures analysis/Table_3_with_ADHD_that_are_NOT_prescribed_ADHD_medication.py
  #     --output output/Table_3_with_ADHD_that_are_NOT_prescribed_ADHD_medication.csv 
  #   outputs:
  #     moderately_sensitive:
  #       measure: output/Table_3_with_ADHD_that_are_NOT_prescribed_ADHD_medication.csv

  # Table_3_NOT_prescribed_ADHD_medication_in_ADHD_group:
  #   run: > 
  #     ehrql:v1 generate-measures analysis/Table_3_NOT_prescribed_ADHD_medication_in_ADHD_group.py
  #     --output output/Table_3_NOT_prescribed_ADHD_medication_in_ADHD_group.csv 
  #   outputs:
  #     moderately_sensitive:
  #       measure: output/Table_3_NOT_prescribed_ADHD_medication_in_ADHD_group.csv

  Patient_table_5_dia_to_med:
    run: > 
      ehrql:v1 generate-dataset analysis/Patient_table_5_dia_to_med.py
      --output output/Patient_table_5_dia_to_med.csv.gz
    outputs:
      highly_sensitive:
        measure: output/Patient_table_5_dia_to_med.csv.gz

  Table_5_time_from_diagnosis_to_treatment:
    run: python:v2 python analysis/Table_5_time_from_diagnosis_to_treatment.py
    needs: [Patient_table_5_dia_to_med]
    outputs:
      moderately_sensitive:
        table1: output/Table_5_time_from_diagnosis_to_treatment.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:01:56

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job request

Status
Succeeded
Backend
TPP
Workspace
adhd-pre-and-post-covid
Requested by
Kin Quan
Branch
main
Force run dependencies
Yes
Git commit hash
9e45d6e
Requested actions
  • Patient_table_5_dia_to_med
  • Table_5_time_from_diagnosis_to_treatment

Code comparison

Compare the code used in this job request