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Job request: 8967

Organisation:
University of Manchester
Workspace:
hosp_simple
ID:
u4ys5lgnqns4nvll
View repo View project.yaml

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

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level various outputs were written to. Researchers can never directly view outputs marked as highly_sensitive ; they can only request that code runs against them. Outputs marked as moderately_sensitive can be viewed by an approved researcher by logging into a highly secure environment. Only outputs marked as moderately_sensitive can be requested for release to the public, via a controlled output review service.

Jobs

Pipeline

Show project.yaml 
version: '3.0'

expectations:
  population_size: 200000

actions:

  # generate_study_population:
  #   run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to today by month" --skip-existing --output-dir=output/measures --output-format=csv.gz
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/measures/input_*.csv.gz

  generate_study_population_hospitalisation:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/hospitalisation_data/input_hospitalisation.csv.gz

  generate_study_population_bmi:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_bmi --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/hospitalisation_data/input_bmi.csv.gz

  # generate_study_population_hospitalisation_2:
  #   run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --index-date-range "2019-04-01 to 2019-06-01 by month" --output-dir=output/hospitalisation_data --output-format=csv.gz
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/hospitalisation_data/input_hospitalisatio*.csv.gz

  # generate_study_population_hospitalisation_3:
  #   run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --index-date-range "2019-07-01 to 2019-09-01 by month" --output-dir=output/hospitalisation_data --output-format=csv.gz
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/hospitalisation_data/input_hospitalisati*.csv.gz

  # generate_study_population_hospitalisation_4:
  #   run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --index-date-range "2019-10-01 to 2019-12-01 by month" --output-dir=output/hospitalisation_data --output-format=csv.gz
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/hospitalisation_data/input_hospitalisat*.csv.gz

  # generate_notebook_hospitalisation_analysis:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_analysis.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_risk --ExecutePreprocessor.timeout=86400
  #   needs: [generate_study_population_hospitalisation]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/hospitalisation_risk/hospitalisation_analysis.html 
  #       figures: output/hospitalisation_risk/*

  generate_notebook_hospitalisation_prediction_urti:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_prediction_urti_enc.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_prediction_urti --ExecutePreprocessor.timeout=86400
    # needs: [generate_study_population_hospitalisation,generate_study_population_bmi]
    needs: [generate_study_population_hospitalisation]
    outputs:
      moderately_sensitive:
        notebook: output/hospitalisation_prediction_urti/hospitalisation_prediction_urti_enc.html 
        figures: output/hospitalisation_prediction_urti/*


  # generate_notebook_hospitalisation_prediction_urti_lr:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_prediction_urti_lr.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_prediction_urti --ExecutePreprocessor.timeout=86400
  #   needs: [generate_study_population_hospitalisation]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/hospitalisation_prediction_urti/hospitalisation_prediction_urti_lr.html 
  #       figures: output/hospitalisation_prediction_urti/*

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 01:38:45

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

Job information

Status
Succeeded
Backend
TPP
Workspace
hosp_simple
Requested by
ali
Branch
hospitalisation_simple
Force run dependencies
No
Git commit hash
ea56bd6
Requested actions
  • generate_notebook_hospitalisation_prediction_urti

Code comparison

Compare the code used in this Job Request