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Job request: 19282

Organisation:
Bennett Institute
Workspace:
opioids-covid-research
ID:
3gbkhfccy4ywtpx6
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Andrea Schaffer 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 
######################################
# This script defines the project pipeline - 
# it specifies the execution orders for all the code in this
# repo using a series of actions.
######################################

version: '3.0'

expectations:
  population_size: 10000

actions:

  generate_dataset_table:
    run: ehrql:v0 generate-dataset analysis/define_dataset_table.py 
      --output output/data/dataset_table.csv.gz
    outputs:
      highly_sensitive:
        cohort: output/data/dataset_table.csv.gz  

  measures_overall:
    run: ehrql:v0 generate-measures analysis/measures_overall.py 
      --output output/measures/measures_overall.csv
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_overall.csv
  
  # measures_overall_nocancer:
  #   run: ehrql:v0 generate-measures analysis/measures_overall_nocancer.py 
  #     --output output/measures/measures_overall_nocancer.csv
  #   outputs:
  #     moderately_sensitive:
  #       measure_csv: output/measures/measures_overall_nocancer.csv
    
  measures_demo:
    run: ehrql:v0 generate-measures analysis/measures_demo.py 
      --output output/measures/measures_demo.csv
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_demo.csv

  # measures_demo_nocancer:
  #   run: ehrql:v0 generate-measures analysis/measures_demo_nocancer.py 
  #     --output output/measures/measures_demo_nocancer.csv
  #   outputs:
  #     moderately_sensitive:
  #       measure_csv: output/measures/measures_demo_nocancer.csv

  measures_type:
    run: ehrql:v0 generate-measures analysis/measures_type.py 
      --output output/measures/measures_type.csv
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_type.csv

  # measures_type_nocancer:
  #   run: ehrql:v0 generate-measures analysis/measures_type_nocancer.py 
  #     --output output/measures/measures_type_nocancer.csv
  #   outputs:
  #     moderately_sensitive:
  #       measure_csv: output/measures_type_nocancer.csv

  measures_carehome:
    run: ehrql:v0 generate-measures analysis/measures_carehome.py 
      --output output/measures/measures_carehome.csv
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_carehome.csv
        
  # measures_carehome_sens:
  #   run: ehrql:v0 generate-measures analysis/measures_carehome_sens.py 
  #     --output output/measures/measures_carehome_sens.csv
  #   outputs:
  #     moderately_sensitive:
  #       measure_csv: output/measures/measures_carehome_sens.csv
        
  
  # ## Cohort data
  # generate_study_population_1:
  #   run: cohortextractor:latest generate_cohort
  #     --study-definition study_definition
  #     --index-date-range "2018-01-01 to 2018-12-01 by month" 
  #     --output-dir=output 
  #     --output-format=csv
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/input_*.csv

  # generate_study_population_2:
  #   run: cohortextractor:latest generate_cohort 
  #     --study-definition study_definition
  #     --index-date-range "2019-01-01 to 2019-12-01 by month" 
  #     --output-dir=output 
  #     --output-format=csv
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/input*.csv

  # generate_study_population_3:
  #   run: cohortextractor:latest generate_cohort 
  #     --study-definition study_definition
  #     --index-date-range "2020-01-01 to 2020-12-01 by month" 
  #     --output-dir=output 
  #     --output-format=csv
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/inpu*.csv

  # generate_study_population_4:
  #   run: cohortextractor:latest generate_cohort 
  #     --study-definition study_definition
  #     --index-date-range "2021-01-01 to 2021-12-01 by month" 
  #     --output-dir=output 
  #     --output-format=csv
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/inp*.csv
  
  # generate_study_population_5:
  #   run: cohortextractor:latest generate_cohort 
  #     --study-definition study_definition
  #     --index-date-range "2022-01-01 to 2022-03-01 by month" 
  #     --output-dir=output 
  #     --output-format=csv
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/in*.csv

  # ## Ethnicity      
  # generate_ethnicity_cohort:
  #   run: >
  #     cohortextractor:latest generate_cohort
  #       --study-definition study_definition_ethnicity
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/input_ethnicity.csv


  # # Data processing ----
  
  # ## Add ethnicity
  # join_cohorts:
  #   run: >
  #     cohort-joiner:v0.0.48
  #       --lhs output/input_*.csv
  #       --rhs output/input_ethnicity.csv
  #       --output-dir output/data
  #   needs: [generate_study_population_1,  generate_study_population_2, 
  #     generate_study_population_5, generate_study_population_3, 
  #     generate_study_population_4, generate_ethnicity_cohort]
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/data/input_*.csv 


  # ## Generate measures - full population
  # generate_measures:
  #   run: >
  #     cohortextractor:latest generate_measures 
  #       --study-definition study_definition
  #       --output-dir output/data
  #   needs: [join_cohorts]
  #   outputs:
  #     moderately_sensitive:
  #       measure_csv: output/data/measure_*.csv


  ## Process data - time series
  # process_data_ts:
  #  run: r:latest analysis/process/process_data_ts.R
  #  needs: [measures_overall, measures_demo, measures_type, measures_carehome]
  #  outputs:
  #     moderately_sensitive:
  #       timeseries_csv: output/timeseries/ts_*.csv

  # ## Time series - rates and rounding
  # rounding_ts:
  #  run: r:latest analysis/process/rounding_ts.R
  #  needs: [process_data_ts]
  #  outputs:
  #     moderately_sensitive:
  #       timeseries_csv: output/timeseries/ts*.csv

  # ## Process data - table
  # process_data_table:
  #  run: r:latest analysis/process/process_data_table.R
  #  needs: [generate_dataset_table]
  #  outputs:
  #     highly_sensitive:
  #       table_csv: output/processed/final*.csv
  #       table2_csv: output/joined/final*.csv

  # ## Results table 
  # table:
  #   run: r:latest analysis/descriptive/table_stand.R
  #   needs: [process_data_table]
  #   outputs:
  #     moderately_sensitive:
  #       table: output/tables/table_*.csv

Timeline

  • Created:

  • Runtime:

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Job information

Status
Failed
Backend
TPP
Workspace
opioids-covid-research
Requested by
Andrea Schaffer
Branch
main
Force run dependencies
No
Git commit hash
c2d9ac4
Requested actions
  • measures_demo
  • measures_type
  • measures_carehome

Code comparison

Compare the code used in this Job Request