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Job request: 26388

Organisation:
Bennett Institute
Workspace:
pifu-data-exploration
ID:
v7walysyasavdwkc
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 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:
    generate_dataset_rheum
    Status:
    Succeeded
    Job identifier:
    7kzbzzpza3jpeks5
  • Action:
    generate_dataset_everyone
    Status:
    Succeeded
    Job identifier:
    auixqb7w34qgqfap
  • Action:
    generate_dataset_derm
    Status:
    Succeeded
    Job identifier:
    li5v5rn2ikce3q5w
  • Action:
    generate_dataset_gastro
    Status:
    Succeeded
    Job identifier:
    jfqgs4276rpprfai
  • Action:
    measures_everyone
    Status:
    Succeeded
    Job identifier:
    pbwzwykws4m3sd2y
  • Action:
    measures_rheum
    Status:
    Succeeded
    Job identifier:
    7m3tiado2r2fzw4j
  • Action:
    measures_gastro
    Status:
    Succeeded
    Job identifier:
    pztwdlb4mdxfyfmf
  • Action:
    measures_derm
    Status:
    Succeeded
    Job identifier:
    lp6opklnz7o42rjy
  • Action:
    measures_time_rheum
    Status:
    Succeeded
    Job identifier:
    rhkvlfmdiskmmfe3
  • Action:
    measures_time_gastro
    Status:
    Succeeded
    Job identifier:
    frxslrmbfb5gzgbl
  • Action:
    measures_time_derm
    Status:
    Succeeded
    Job identifier:
    w4z4duz3ua27jcbt

Pipeline

Show project.yaml 
version: '5.0'

actions:
  # generate_dataset_explore:
  #   run: ehrql:v1 generate-dataset analysis/dataset_definition_explore.py --output output/dataset_explore.csv.gz
  #   outputs:
  #     highly_sensitive:
  #       dataset: output/dataset_explore.csv.gz

  # table_explore:
  #   run: r:v2 analysis/process/data_exploration.R
  #   needs: [generate_dataset_explore]
  #   outputs:
  #     moderately_sensitive:
  #       table1: output/processed/table_explore.csv
  #       #table2: output/processed/table_pfu_explore.csv
  #       table3: output/processed/counts_explore.csv

  generate_dataset_everyone:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_everyone.py --output output/dataset_everyone.csv.gz
    outputs:
      highly_sensitive:
        dataset: output/dataset_everyone.csv.gz

  generate_dataset_rheum:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_specialty.py --output output/dataset_rheumatology.csv.gz
      --
      --trt_func_code 410
    outputs:
      highly_sensitive:
        dataset: output/dataset_rheumatology.csv.gz
  
  generate_dataset_derm:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_specialty.py --output output/dataset_dermatology.csv.gz
      --
      --trt_func_code 330
    outputs:
      highly_sensitive:
        dataset: output/dataset_dermatology.csv.gz

  generate_dataset_gastro:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_specialty.py --output output/dataset_gastroenterology.csv.gz
      --
      --trt_func_code 301
    outputs:
      highly_sensitive:
        dataset: output/dataset_gastroenterology.csv.gz

  measures_everyone:
    run: ehrql:v1 generate-measures analysis/measures_everyone.py --output output/measures/measures_everyone.csv
    outputs:
      moderately_sensitive:
        dataset: output/measures/measures_everyone.csv
    
  measures_rheum:
    run: ehrql:v1 generate-measures analysis/measures_specialty.py --output output/measures/measures_rheum.csv
      --
      --trt_func_code 410
    outputs:
      moderately_sensitive:
        dataset: output/measures/measures_rheum.csv
  
  measures_gastro:
    run: ehrql:v1 generate-measures analysis/measures_specialty.py --output output/measures/measures_gastro.csv
      --
      --trt_func_code 301
    outputs:
      moderately_sensitive:
        dataset: output/measures/measures_gastro.csv
  
  measures_derm:
    run: ehrql:v1 generate-measures analysis/measures_specialty.py --output output/measures/measures_derm.csv
      --
      --trt_func_code 330
    outputs:
      moderately_sensitive:
        dataset: output/measures/measures_derm.csv

  measures_time_rheum:
    run: ehrql:v1 generate-measures analysis/measures_time_specialty.py --output output/measures/measures_time_rheum.csv
      --
      --trt_func_code 410
    outputs:
      moderately_sensitive:
        dataset: output/measures/measures_time_rheum.csv

  measures_time_gastro:
    run: ehrql:v1 generate-measures analysis/measures_time_specialty.py --output output/measures/measures_time_gastro.csv
      --
      --trt_func_code 301
    outputs:
      moderately_sensitive:
        dataset: output/measures/measures_time_gastro.csv

  measures_time_derm:
    run: ehrql:v1 generate-measures analysis/measures_time_specialty.py --output output/measures/measures_time_derm.csv
      --
      --trt_func_code 330
    outputs:
      moderately_sensitive:
        dataset: output/measures/measures_time_derm.csv

  # table:
  #   run: r:v2 analysis/process/pop_characteristics.R
  #   needs: [generate_dataset_everyone, generate_dataset_rheum, generate_dataset_gastro, generate_dataset_derm]
  #   outputs:
  #     moderately_sensitive:
  #       table1: output/processed/table.csv
  #       table2: output/processed/table_pfu.csv
  #       table3: output/processed/table_rheum.csv

  # time_series:
  #   run: r:v2 analysis/process/measures_process.R
  #   needs: [measures_everyone, measures_rheum, measures_gastro, measures_derm]
  #   outputs:
  #     moderately_sensitive:
  #       timeseries1: output/processed/time_series_overall.csv
  #       timeseries2: output/processed/time_series_specialty.csv

  # opa_time:
  #   run: r:v2 analysis/process/measures_time_process.R
  #   needs: [measures_time_rheum, measures_time_gastro, measure_time_derm]
  #   outputs:
  #     moderately_sensitive:
  #       table: output/processed/outpatient_time.csv

Job statistics

Status Count Percentage
Pending 0 0%
Running 0 0%
Succeeded 11 100%
Failed 0 0%

11 / 11 (100%) complete

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 21:00:38

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

Job request

Status
Succeeded
Backend
TPP
Workspace
pifu-data-exploration
Requested by
Andrea Schaffer
Branch
main
Force run dependencies
No
Git commit hash
4bd2123
Requested actions
  • generate_dataset_everyone
  • generate_dataset_rheum
  • generate_dataset_derm
  • generate_dataset_gastro
  • measures_everyone
  • measures_rheum
  • measures_gastro
  • measures_derm
  • measures_time_rheum
  • measures_time_gastro
  • measures_time_derm

Code comparison

Compare the code used in this job request