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Job request: 24034

Organisation:
Bennett Institute
Workspace:
wp-work-package-1
ID:
ybl6vweoumfnkdkq
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Arina Tamborska 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"

expectations:
  population_size: 1000

actions:
  generate_patient_measures:
    run: ehrql:v1 generate-measures --output output/patient_measures/patient_measures.csv.gz analysis/wp_patient_measures_def.py -- --drop_reason --drop_prescriptions --drop_indicat_prescript
    outputs:
       highly_sensitive:
         dataset: output/patient_measures/patient_measures.csv.gz
  #generate_practice_measures_keep_follow_up:
  #  run: ehrql:v1 generate-measures --output output/practice_measures/practice_measures_keep_follow_up.csv.gz analysis/wp_practice_measures_def.py -- --drop_reason --drop_prescriptions --drop_indicat_prescript
  #  outputs:
  #    highly_sensitive:
  #      dataset: output/practice_measures/practice_measures_keep_follow_up.csv.gz
  #generate_practice_measures_keep_reason:
  #  run: ehrql:v1 generate-measures --output output/practice_measures/practice_measures_keep_reason.csv.gz analysis/wp_practice_measures_def.py -- --drop_follow_up --drop_prescriptions --drop_indicat_prescript
  #  outputs:
  #    highly_sensitive:
  #      dataset: output/practice_measures/practice_measures_keep_reason.csv.gz
  #generate_practice_measures_keep_prescriptions:
  #  run: ehrql:v1 generate-measures --output output/practice_measures/practice_measures_keep_prescriptions.csv.gz analysis/wp_practice_measures_def.py -- --drop_follow_up --drop_reason --drop_indicat_prescript
  #  outputs:
  #    highly_sensitive:
  #      dataset: output/practice_measures/practice_measures_keep_prescriptions.csv.gz
  #generate_practice_measures_keep_indicat_prescript:
  #  run: ehrql:v1 generate-measures --output output/practice_measures/practice_measures_keep_indicat_prescript.csv.gz analysis/wp_practice_measures_def.py -- --drop_follow_up --drop_reason --drop_prescriptions
  #  outputs:
  #    highly_sensitive:
  #      dataset: output/practice_measures/practice_measures_keep_indicat_prescript.csv.gz
  generate_practice_measures:
    run: ehrql:v1 generate-measures --output output/practice_measures/practice_measures.csv.gz analysis/wp_practice_measures_def.py -- --drop_reason --drop_prescriptions --drop_indicat_prescript
    outputs:
      highly_sensitive:
        dataset: output/practice_measures/practice_measures.csv.gz
  # generate_app_measures:
  #   run: ehrql:v1 generate-measures --output output/appointments/app_measures.csv analysis/appointments/app_measures.py
  #   outputs:
  #     moderately_sensitive:
  #       dataset: output/appointments/app_measures.csv
  # generate_app_viz:
  #   run: r:latest analysis/appointments/app_viz.r
  #   needs: [generate_app_measures]
  #   outputs:
  #     moderately_sensitive:
  #       app_figures: output/appointments/*.png
  # generate_app_summary:
  #   run: python:latest analysis/appointments/app_summary.py
  #   needs: [generate_app_measures]
  #   outputs:
  #     moderately_sensitive:
  #       app_table: output/appointments/app_summary.csv
  # generate_pre_processing:
  #   run: python:latest analysis/pre_processing.py 
  #       --output output/practice_measures/processed_practice_measures.csv.gz
  #       --output output/patient_measures/processed_patient_measures.csv.gz
  #       --output output/patient_measures/frequency_table.csv
  #   needs: [generate_patient_measures, generate_practice_measures]
  #   outputs:
  #     highly_sensitive:
  #       practice_measure: output/practice_measures/processed_practice_measures.csv.gz
  #       patient_measure: output/patient_measures/processed_patient_measures.csv.gz
  #     moderately_sensitive:
  #       frequency_table: output/patient_measures/frequency_table.csv
  # generate_measures_viz:
  #   run: r:latest analysis/viz_measures.r
  #   needs: [generate_pre_processing]
  #   outputs:
  #     moderately_sensitive:
  #       app_figures: output/*/*.png
  #       total_measures: output/total_measures/*.csv
  # generate_test_data:
  #   run: ehrql:v1 generate-dataset analysis/dataset.py --output output/patient_measures/test.csv --test-data-file analysis/test_dataset.py
  #   outputs:
  #     highly_sensitive:
  #       dataset: output/patient_measures/test.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 01:05:46

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

Job request

Status
Succeeded
Backend
TPP
Workspace
wp-work-package-1
Requested by
Arina Tamborska
Branch
main
Force run dependencies
No
Git commit hash
72b7556
Requested actions
  • generate_practice_measures

Code comparison

Compare the code used in this job request