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Job request: 16774

Organisation:
The London School of Hygiene & Tropical Medicine
Workspace:
healthcare_utilisation_openprompt
ID:
6djjqi35icesnepi
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Liang-Yu Lin 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: 500

actions:

  generate_long_covid_exposure_dataset:
    run: 
      databuilder:v0 generate-dataset
        analysis/dataset_definition_unmatched_exp_lc.py
        --output output/dataset_exp_lc_unmatched.csv
    outputs:
      highly_sensitive:
        cohort: output/dataset_exp_lc_unmatched.csv

  check_stp_regions:
    needs: [generate_long_covid_exposure_dataset]
    run: r:latest analysis/dm00_check_stp_regions.R
    outputs:
      moderately_sensitive: 
        stp_region: output/stp_regions_counts.csv

  generate_list_gp_use_long_covid_dx:
    run: 
      databuilder:v0 generate-dataset
        analysis/dataset_definition_lc_gp_list.py
        --output output/dataset_lc_gp_list.csv
    outputs:
      highly_sensitive:
        cohort: output/dataset_lc_gp_list.csv

  generate_dataset_comparator_exclude_gp_no_long_covid:
    needs: [generate_list_gp_use_long_covid_dx]
    run: 
      databuilder:v0 generate-dataset
        analysis/dataset_definition_unmatched_comparator.py
        --output output/dataset_comparator_unmatched.csv
    outputs:
      highly_sensitive:
        cohort: output/dataset_comparator_unmatched.csv

  # split_unmatched_data_by_stp_regions:
  #   needs: [generate_long_covid_exposure_dataset, generate_dataset_comparator_exclude_gp_no_long_covid]
  #   run: 
  #     r:latest r analysis\dm00_split_stp_for_matching.R
  #   outputs: 
  #     highly_sensitive: 


  match_comparators:
    run:
      python:latest python analysis/match.py
    needs: [generate_dataset_comparator_exclude_gp_no_long_covid, generate_long_covid_exposure_dataset]
    outputs: 
      highly_sensitive:
        matched_cases: output/matched_cases.csv
        matched_matches: output/matched_matches.csv
        matched_all: output/matched_combined.csv
      moderately_sensitive: 
        matching_report: output/matching_report.txt

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:23

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

Job information

Status
Succeeded
Backend
TPP
Workspace
healthcare_utilisation_openprompt
Requested by
Liang-Yu Lin
Branch
main
Force run dependencies
No
Git commit hash
1ef3f2c
Requested actions
  • check_stp_regions

Code comparison

Compare the code used in this Job Request