Skip to content

Job request: 3167

Organisation:
Workspace:
antipsychotics-prescribing-during-covid-19-master
ID:
oz4xn3vel6vfhrhp
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Millie Green 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

  • Action:
    extract_ethnicity
    Status:
    Status: Failed
    Job identifier:
    iok7yzjvwt2y4keg
    Error:
    nonzero_exit: Job exited with an error code

Pipeline

Show project.yaml 
######################################

# This script defines the project pipeline - it specifys the execution orders for all the code in this
# repo using a series of actions.

######################################

version: '3.0'

expectations:
  population_size: 100000

actions:

  # Extract data ----
  
  ## study population flow chart
  generate_study_population_flow_chart_data:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_flow_chart --index-date-range "2019-01-01 to 2021-04-01 by month" --output-dir=output/data --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/data/input_flow_chart_*.feather
  
  ## Cohort data
  generate_cohort_1:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to 2019-06-01 by month" --output-dir=output/data --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/data/input_*.feather
        
  generate_cohort_2:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-07-01 to 2019-12-01 by month" --output-dir=output/data --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/data/input*.feather
  
  generate_cohort_3:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2020-01-01 to 2020-06-01 by month" --output-dir=output/data --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/data/inpu*.feather
        
  generate_cohort_4:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2020-07-01 to 2020-12-01 by month" --output-dir=output/data --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/data/inp*.feather
        
  generate_cohort_5:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-01-01 to 2021-04-01 by month" --output-dir=output/data --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/data/in*.feather
  
  ## Ethnicity      
  extract_ethnicity:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-dir=output/data --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/data/input_ethnicity.feather
        
  # ## Patient to practice lookup
  # patient_practice_lookup:
  #   run: cohortextractor:latest generate_cohort --study-definition study_definition_practice_count --output-dir=output/data --output-format=feather
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/data/input_practice_count.feather
        
  
  # Data processing ----

  # ## Patient counts
  # get_patient_count:
  #   run: python:latest python analysis/get_patient_counts.py --output-dir=output/data
  #   needs: [extract_data]
  #   outputs:
  #      moderately_sensitive:
  #        text: output/data/patient_count.json
         
  # ## Practice count
  # get_practice_count:
  #   run: python:latest python analysis/get_practice_count.py --output-dir=output/data
  #   needs: [patient_practice_lookup]
  #   outputs:
  #     moderately_sensitive:
  #       text: output/data/practice_count.json
  
  ## Add ethnicity
  join_ethnicity:
    run: python:latest python analysis/join_ethnicity.py
    needs: [generate_cohort_1, generate_cohort_2, generate_cohort_3, generate_cohort_4, generate_cohort_5, extract_ethnicity]
    outputs:
      highly_sensitive:
        cohort: output/data/i*.feather
  
  ## Process data
  data_process:
    run: r:latest analysis/process_data.R
    needs: [generate_study_population_flow_chart_data, join_ethnicity]
    outputs:
      moderately_sensitive:
        data: output/data/data_*.rds
        # tables: output/data/custom_measures_*.csv
        
  # ## Generate measures
  # generate_measures:
  #     run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output/data
  #     needs: [join_ethnicity]
  #     outputs:
  #       moderately_sensitive:
  #         measure_csv: output/data/measure_*.csv
  
  # ### Generate measures, by group
  # generate_measures_demographics:
  #   run: python:latest python analysis/calculate_measures.py
  #   needs: [join_ethnicity]
  #   outputs:
  #     moderately_sensitive:
  #       measure: output/combined_measure_*.csv
  # 
  #   ### Generate measures, by group and demographic
  # generate_measures_demographics:
  #   run: python:latest python analysis/calculate_measures.py
  #   needs: [join_ethnicity]
  #   outputs:
  #     moderately_sensitive:
  #       measure: output/combined_measure_*.csv
  
  

  # Results ----
  
  ## Calculate numbers for study population flow chart
  flow_chart:
    run: r:latest -e 'rmarkdown::render("analysis/study_definition_flow_chart.rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
    needs: [data_process]
    outputs:
      moderately_sensitive:
        html: output/study_definition_flow_chart.html
  
  ## Figures
  summary_figures:
    run: r:latest analysis/summary_plots.R
    needs: [data_process]
    outputs:
      moderately_sensitive:
        plots: output/figures/plot_*.svg
  
  summary_figures_redacted:
    run: r:latest analysis/summary_plots_redacted.R
    needs: [data_process]
    outputs:
      moderately_sensitive:
        plots: output/figures/plot*.svg
        
  ## Table 1
  table_1:
    run: r:latest analysis/table_1.R
    needs: [join_ethnicity]
    outputs:
      moderately_sensitive:
        plots: output/tables/table1.html
  
  # ## Whole population notebook
  # generate_notebook:
  #   run: jupyter:latest jupyter nbconvert /workspace/notebooks/antipsychotic_measures.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
  #   needs: [generate_measures, get_practice_count, get_patient_count]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/antipsychotic_measures.html

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:06

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

Job request

Status
Failed
Backend
EMIS
Workspace
antipsychotics-prescribing-during-covid-19-master
Requested by
Millie Green
Branch
master
Force run dependencies
No
Git commit hash
80fa5e3
Requested actions
  • extract_ethnicity

Code comparison

Compare the code used in this job request