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Job request: 829

Organisation:
The London School of Hygiene & Tropical Medicine
Workspace:
t1dm_covid_sample
ID:
gvvkesuvpbghhhqe
View repo View project.yaml

This page shows the technical details of what happened when authorised researcher Rohini Mathur requested one or more actions to be run against real patient data in the project, within a secure environment.

By cross-referencing the indicated Requested Actions with the Pipeline section below, you can infer what security level various outputs were written to. Outputs marked as highly_sensitive can never be viewed directly by a researcher; 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: 10000

actions:
  generate_covid_cohort:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_covid
    outputs:
      highly_sensitive:
        cohort: output/input_covid.csv

  generate_covid_community_cohort:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_covid_community
    outputs:
      highly_sensitive:
        cohort: output/input_covid_community.csv

  generate_pneumonia_cohort:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_pneumonia
    outputs:
      highly_sensitive:
        cohort: output/input_pneumonia.csv
  
  matching_pneumonia:
    run: python:latest python analysis/match_running.py "input_pneumonia"
    needs: [generate_covid_cohort, generate_pneumonia_cohort]
    outputs:
      moderately_sensitive:
        matching_report: output/matching_report.txt
      highly_sensitive:
        combined: output/matched_combined.csv

 # matching_data_management:
 #   run: stata-mp:latest analysis/300_cr_data_management_matching.do 
 #   needs: [generate_covid_cohort, generate_pneumonia_cohort]
 #   outputs:
 #     highly_sensitive:
 #       combined3: output/matched_combined_pneumonia.dta

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:27

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

Job information

Status
Succeeded
Backend
TPP
Workspace
t1dm_covid_sample
Requested by
Rohini Mathur
Branch
python-matching
Force run dependencies
No
Git commit hash
9e7963f
Requested actions
  • matching_pneumonia

Code comparison

Compare the code used in this Job Request