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Job request: 23747

Organisation:
Bennett Institute
Workspace:
pharmacy-first-data-development
ID:
yi2wkktuismgdl7j
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Viveck Kingsley 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'

# Ignore this`expectation` block. It is required but not used, and will be removed in future versions.
expectations:
  population_size: 1000

actions:
  generate_pf_codes_data_development:
    run: >
      ehrql:v1 generate-dataset analysis/dataset_definition_pf_data_development.py
        --test-data-file analysis/test_dataset_definition_pf_data_development.py
        --output output/data_development/pf_codes_data_development.arrow
    outputs:
      highly_sensitive:
        dataset: output/data_development/pf_codes_data_development.arrow

  generate_med_status_data_development:
    run: >
      ehrql:v1 generate-dataset analysis/dataset_definition_med_status_data_development.py
        --output output/data_development/med_status_data_development.arrow
    outputs:
      highly_sensitive:
        dataset: output/data_development/med_status_data_development.arrow

  generate_measures_pf_codes:
    run: > 
      ehrql:v1 generate-measures analysis/measures_definition_clinical_codes.py
      --output output/clinical_codes/code_counts_measures.csv
    outputs:
      moderately_sensitive:
        measure: output/clinical_codes/code_counts_measures.csv

  data_development_med_status_pre:
     run: r:latest analysis/data_development_med_status_pre_counts.R
     needs: [generate_med_status_data_development]
     outputs:
       moderately_sensitive:
         dataset: output/data_development/med_status_pre_counts.csv
  
  data_development_med_status_post:
     run: r:latest analysis/data_development_med_status_post_counts.R
     needs: [generate_med_status_data_development]
     outputs:
       moderately_sensitive:
         dataset: output/data_development/med_status_post_counts.csv

  data_development_med_status_combine:
     run: r:latest analysis/data_development_med_status_combine.R
     needs: [data_development_med_status_pre, data_development_med_status_post]
     outputs:
       moderately_sensitive:
         dataset: output/data_development/med_status_counts.csv

  data_development_pf_code_distinct:
    run: r:latest analysis/data_development_pf_code_count_distinct.R
    needs: [generate_pf_codes_data_development]
    outputs:
      moderately_sensitive:
        dataset: output/data_development/pf_codes_count_distinct.csv

  data_development_pf_code_events:
    run: r:latest analysis/data_development_pf_code_count_events.R
    needs: [generate_pf_codes_data_development]
    outputs:
      moderately_sensitive:
        dataset: output/data_development/pf_codes_count_events.csv

  data_development_pf_codes_pathways:
    run: r:latest analysis/data_development_pf_code_count_pathways.R
    needs: [generate_pf_codes_data_development]
    outputs:
      moderately_sensitive:
        dataset: output/data_development/pf_codes_count_pathways.csv

  data_development_pf_codes_combine:
    run: r:latest analysis/data_development_pf_code_count_combine.R
    needs: [data_development_pf_code_distinct, data_development_pf_code_events, data_development_pf_codes_pathways]
    outputs:
      moderately_sensitive:
        dataset: output/data_development/pf_codes_count_summary.csv

  generate_pf_med_counts_measures:
    run: >
      ehrql:v1 generate-measures analysis/measures_definition_pf_consultation_med_counts.py
      --dummy-tables dummy_tables
      --output output/measures/consultation_med_counts_measures.csv
    outputs:
      moderately_sensitive:
        measure: output/measures/consultation_med_counts_measures.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:05:31

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

Job information

Status
Succeeded
Backend
TPP
Workspace
pharmacy-first-data-development
Requested by
Viveck Kingsley
Branch
main
Force run dependencies
No
Git commit hash
dce0cca
Requested actions
  • generate_pf_med_counts_measures

Code comparison

Compare the code used in this Job Request