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Job request: 21015

Organisation:
Bennett Institute
Workspace:
waiting-list
ID:
y6ogii5egtaidlpg
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 
version: '3.0'

expectations:
  population_size: 1000

actions:

  ##### Dataset definitions #####

  # Closed (completed) RTT pathways
  generate_dataset_clockstops:
    run: ehrql:v0 generate-dataset analysis/dataset_definition_clockstops.py 
      --output output/data/dataset_clockstops.csv.gz
    outputs:
      highly_sensitive:
        cohort: output/data/dataset_clockstops.csv.gz  

  # Open (incomplete) RTT pathways
  # generate_dataset_openpathways:
  #   run: ehrql:v0 generate-dataset analysis/dataset_definition_openpathways.py 
  #     --output output/data/dataset_openpathways.csv.gz
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/data/dataset_openpathways.csv.gz  
  
  ##### Opioid measures - closed pathways #####
  
  measures_any_opioid:
    run: ehrql:v0 generate-measures analysis/measures_any_opioid.py 
      --output output/measures/measures_any_opioid.csv
      --dummy-data-file dummy/dummy_any_opioid.csv
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_any_opioid.csv

  measures_hi_opioid:
    run: ehrql:v0 generate-measures analysis/measures_hi_opioid.py 
      --output output/measures/measures_hi_opioid.csv
      --dummy-data-file dummy/dummy_hi_opioid.csv
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_hi_opioid.csv
      
  # opioids_by_week:
  #  run: r:latest analysis/clockstops/opioids_by_week.R
  #  needs: [measures_any_opioid, measures_hi_opioid]
  #  outputs:
  #     moderately_sensitive:
  #       data: output/clockstops/opioid*.csv
  #       plots: output/clockstops/plo*.png
        
  ##### Analysis - closed pathways #####
  
  checks_clockstops:
   run: r:latest analysis/clockstops/checks_clockstops.R
   needs: [generate_dataset_clockstops]
   outputs:
      moderately_sensitive:
        data: output/clockstops/check*.csv

  # final_cohort_clockstops:
  #  run: r:latest analysis/clockstops/final_cohort_clockstops.R
  #  needs: [generate_dataset_clockstops]
  #  outputs:
  #     highly_sensitive:
  #       cohort: output/data/cohort*.csv.gz

  # full_stats_clockstops:
  #  run: r:latest analysis/clockstops/full_stats_clockstops.R
  #  needs: [final_cohort_clockstops]
  #  outputs:
  #     moderately_sensitive:
  #       data1: output/clockstops/rtt_dates.csv
  #       data2: output/clockstops/cat_var_dist.csv
  #       data3: output/clockstops/wait_time_pcent.csv
  #       data4: output/clockstops/wait_time.csv
  #       data5: output/clockstops/med_counts_by_period.csv
  #       plots: output/clockstops/plot_*.png

  # ortho_stats_clockstops:
  #  run: r:latest analysis/clockstops/ortho_stats_clockstops.R
  #  needs: [final_cohort_clockstops]
  #  outputs:
  #     moderately_sensitive:
  #       data1: output/clockstops/rtt_dates_ortho.csv
  #       data2: output/clockstops/cat_var_dist_ortho.csv
  #       data3: output/clockstops/wait_time_pcent_ortho.csv
  #       data4: output/clockstops/wait_time_ortho.csv
  #       data5: output/clockstops/med_counts_by_period_ortho.csv
  #       plots: output/clockstops/plot*.png  


  ##### Analysis - open pathways #####

  # checks_openpathways:
  #  run: r:latest analysis/openpathways/checks_openpathways.R
  #  needs: [generate_dataset_openpathways]
  #  outputs:
  #     moderately_sensitive:
  #       data: output/openpathways/*.csv

  # final_cohort_openpathways:
  #  run: r:latest analysis/openpathways/final_cohort_openpathways.R
  #  needs: [generate_dataset_openpathways]
  #  outputs:
  #     highly_sensitive:
  #       cohort: output/data/cohor*.csv.gz

  # full_stats_openpathways:
  #  run: r:latest analysis/openpathways/full_stats_openpathways.R
  #  needs: [final_cohort_openpathways]
  #  outputs:
  #     moderately_sensitive:
  #       data1: output/openpathways/rtt_dates_open.csv
  #       data2: output/openpathways/cat_var_dist_open.csv
  #       data3: output/openpathways/wait_time_pcent_open.csv
  #       data4: output/openpathways/wait_time_open.csv
  #       data5: output/openpathways/med_counts_by_period_open.csv
  #       plots: output/openpathways/plot_*.png

  # ortho_stats_openpathways:
  #  run: r:latest analysis/openpathways/ortho_stats_openpathways.R
  #  needs: [final_cohort_openpathways]
  #  outputs:
  #     moderately_sensitive:
  #       data1: output/openpathways/rtt_dates_ortho_open.csv
  #       data2: output/openpathways/cat_var_dist_ortho_open.csv
  #       data3: output/openpathways/wait_time_pcent_ortho_open.csv
  #       data4: output/openpathways/wait_time_ortho_open.csv
  #       data5: output/openpathways/med_counts_by_period_ortho_open.csv
  #       plots: output/openpathways/plot*.png

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 02:01:07

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

Job information

Status
Succeeded
Backend
TPP
Workspace
waiting-list
Requested by
Andrea Schaffer
Branch
main
Force run dependencies
No
Git commit hash
3002c9f
Requested actions
  • generate_dataset_clockstops
  • checks_clockstops

Code comparison

Compare the code used in this Job Request