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Job request: 6864

Organisation:
University of Manchester
Workspace:
hosp_pred_urti_2019
ID:
4nk3v76p4kegx5o3
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 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: 10000

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_1:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --index-date-range "2019-01-01 to 2019-03-01 by month" --output-dir=output/hospitalisation_data --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/hospitalisation_data/input_hospitalisation_*.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_measures:
  #   run: cohortextractor:latest generate_measures --study-definition study_definition --skip-existing --output-dir=output/measures
  #   needs: [generate_study_population]
  #   outputs:
  #     moderately_sensitive:
  #       measure_csv: output/measures/measure_*.csv
         
  #generate_notebook_starpu:
  #  run: jupyter:latest jupyter nbconvert /workspace/analysis/starpu.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_risk --ExecutePreprocessor.timeout=86400
  #  needs: [generate_measures]
  #  outputs:
  #    moderately_sensitive:
  #      notebook: output/hospitalisation_risk/starpu.html 
  #      figures: output/hospitalisation_risk/*
        #tables: output/tables/*
        #csvs: output/*/* # two possible subfolders
        #text: output/text/*

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

  # describe_hospitalisation_reading_csv_urti:
  #   run: r:latest analysis/hospitalisation_reading_csv_urti.R
  #   needs: [generate_study_population_hospitalisation_1, generate_study_population_hospitalisation_2, generate_study_population_hospitalisation_3, generate_study_population_hospitalisation_4]
  #   outputs:
  #      moderately_sensitive:
  #       rds1: output/hospitalisation_data/data2019.csv.gz

  generate_notebook_hospitalisation_prediction_urti:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_prediction_urti.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_prediction_urti --ExecutePreprocessor.timeout=86400
    needs: [generate_study_population_hospitalisation_1, generate_study_population_hospitalisation_2]
    outputs:
      moderately_sensitive:
        notebook: output/hospitalisation_prediction_urti/hospitalisation_prediction_urti.html 
        figures: output/hospitalisation_prediction_urti/*
  
  # generate_notebook_hospitalisation_prediction:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_prediction.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_prediction --ExecutePreprocessor.timeout=86400
  #   needs: [generate_study_population_hospitalisation]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/hospitalisation_prediction/hospitalisation_prediction.html 
  #       figures: output/hospitalisation_prediction/*

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:30:58

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

Job request

Status
Failed
Backend
TPP
Workspace
hosp_pred_urti_2019
Requested by
ali
Branch
hospitalisation
Force run dependencies
No
Git commit hash
93102d5
Requested actions
  • generate_notebook_hospitalisation_prediction_urti

Code comparison

Compare the code used in this job request