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Job request: 2919

Organisation:
Workspace:
antipsychotics-prescribing-during-covid-19-master
ID:
dt4cdym7vt6x2nk7
View repo View project.yaml

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

By cross-referencing the indicated Requested Actions with the Pipeline section below, you can infer what security level various outputs were written to. Outputs marked as highly_sensitive can never be viewed directly by a researcher; 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 
######################################

# 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: 10:19:45

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

Job information

Status
Succeeded
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
  • generate_cohort_3

Code comparison

Compare the code used in this Job Request