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Job request: 15716

Organisation:
Bennett Institute
Workspace:
opensafely-internal-interactive
ID:
llrbsih3jpri5hgs
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher George Hickman 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: 1000

actions:

  generate_study_population_ethnicity:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition_ethnicity 
      --param end_date="2023-02-15"
      --output-dir output/01GSZAAE74D9JCAT24AEHQ9P7K --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/01GSZAAE74D9JCAT24AEHQ9P7K/input_ethnicity.csv.gz


  generate_study_population:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition
      --param codelist_1_path="codelists/codelist_1.csv"
      --param codelist_1_system="snomed"
      --param codelist_1_type="medication"
      --param codelist_2_path="codelists/codelist_2.csv"
      --param codelist_2_system="snomed"
      --param codelist_2_type="event"
      --param codelist_1_frequency="monthly"
      --param time_value="5"
      --param time_scale="years"
      --param time_event="before"
      --param codelist_2_comparison_date="event_1_date"
      --param operator="AND"
      --param population="all"
      --param breakdowns="age,sex"
      --index-date-range="2019-09-01 to 2023-02-15 by month"
      --output-dir=output/01GSZAAE74D9JCAT24AEHQ9P7K
      --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/01GSZAAE74D9JCAT24AEHQ9P7K/input_*.csv.gz

  join_cohorts:
    run: >
      cohort-joiner:v0.0.38
        --lhs output/01GSZAAE74D9JCAT24AEHQ9P7K/input_20*.csv.gz
        --rhs output/01GSZAAE74D9JCAT24AEHQ9P7K/input_ethnicity.csv.gz
        --output-dir output/01GSZAAE74D9JCAT24AEHQ9P7K/joined
    needs: [generate_study_population, generate_study_population_ethnicity]
    outputs:
      highly_sensitive:
        cohort: output/01GSZAAE74D9JCAT24AEHQ9P7K/joined/input_20*.csv.gz

  generate_measures:
    run: >
      python:latest python analysis/measures.py
        --breakdowns="age,sex"
        --input_dir="output/01GSZAAE74D9JCAT24AEHQ9P7K/joined"
        --measure="med_review"

    needs: [join_cohorts]
    outputs:
      moderately_sensitive:
        measure: output/01GSZAAE74D9JCAT24AEHQ9P7K/joined/measure*rate.csv
        decile_measure: output/01GSZAAE74D9JCAT24AEHQ9P7K/joined/measure*rate_deciles.csv

  top_5_table:
    run: >
      python:latest python analysis/top_5.py
      --codelist-1-path="codelists/codelist_1.csv"
      --codelist-2-path="codelists/codelist_2.csv"
      --output-dir="output/01GSZAAE74D9JCAT24AEHQ9P7K"
    needs: [generate_measures]
    outputs:
      moderately_sensitive:
        tables: output/01GSZAAE74D9JCAT24AEHQ9P7K/joined/top_5*.csv

  deciles_chart:
    run: >
      deciles-charts:v0.0.33
        --input-files output/01GSZAAE74D9JCAT24AEHQ9P7K/joined/measure_practice_rate_deciles.csv
        --output-dir output/01GSZAAE74D9JCAT24AEHQ9P7K/joined
    config:
      show_outer_percentiles: true
      tables:
        output: true
      charts:
        output: true
    needs: [generate_measures]
    outputs:
      moderately_sensitive:
        deciles_charts: output/01GSZAAE74D9JCAT24AEHQ9P7K/joined/deciles_*.*

  plot_measure:
    run: >
      python:latest python analysis/plot_measures.py
        --breakdowns="age,sex"
        --output-dir output/01GSZAAE74D9JCAT24AEHQ9P7K
    needs: [generate_measures]
    outputs:
      moderately_sensitive:
        measure: output/01GSZAAE74D9JCAT24AEHQ9P7K/plot_measure*.png

  event_counts:
    run: >
      python:latest python analysis/event_counts.py --input_dir="output/01GSZAAE74D9JCAT24AEHQ9P7K/joined" --output_dir="output/01GSZAAE74D9JCAT24AEHQ9P7K"
    needs: [join_cohorts]
    outputs:
      moderately_sensitive:
        measure: output/01GSZAAE74D9JCAT24AEHQ9P7K/event_counts.json

  create_notebook:
    run: >
      python:latest python analysis/create_notebook.py
      --output-dir "output/01GSZAAE74D9JCAT24AEHQ9P7K"
      --codelist-1-description="None"
      --codelist-2-description="None"
      --codelist-1-link="https://codelists.opensafely.org/codelist/opensafely/asthma-inhaler-salbutamol-medication/2020-04-15"
      --codelist-2-link="https://codelists.opensafely.org/codelist/pincer/ast/v1.8"
      --report-title="Medication Review Report"
      --measure-description="Medication Review"
      --population="all"
      --breakdowns="age,sex"
    outputs:
      moderately_sensitive:
        notebook: output/01GSZAAE74D9JCAT24AEHQ9P7K/report.ipynb

  generate_notebook:
    run: jupyter:latest jupyter nbconvert /workspace/output/01GSZAAE74D9JCAT24AEHQ9P7K/report.ipynb --execute --to html --output-dir=/workspace/output/01GSZAAE74D9JCAT24AEHQ9P7K --ExecutePreprocessor.timeout=86400 --no-input
    needs: [create_notebook, event_counts, deciles_chart, top_5_table, plot_measure]
    outputs:
      moderately_sensitive:
        notebook: output/01GSZAAE74D9JCAT24AEHQ9P7K/report.html

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 01:50:56

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

Job information

Status
Failed
Backend
TPP
Workspace
opensafely-internal-interactive
Requested by
George Hickman
Branch
main
Force run dependencies
Yes
Git commit hash
9309344
Requested actions
  • run_all

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