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Job request: 2625

Organisation:
Workspace:
online_consultation
ID:
e7fwrd6zhdgnufpq
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Martina Fonseca 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.

Pipeline

Show project.yaml 
version: '3.0'

expectations:
  population_size: 1000

actions:

  generate_cohorts_main:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_ori
    outputs:
      highly_sensitive:
        cohort: output/input_ori.csv

  run_model:
    run: r:latest analysis/01-createSDtables.R
    needs: [generate_cohorts_main]
    outputs:
      moderately_sensitive:
        log: logs/log-01-createSDtables.txt
        #rdata1_unlist: output/tables/gt_ocpop_unlisted.csv
        #rdata2_unlist: output/tables/gt_gpcpop_unlisted.csv
        tb04: output/tables/tb04_gpcr_agesex.csv
        gtpng1: output/tables/gt_ocpop.html
        gtpng2: output/tables/gt_gpcpop.html
        #rdata1: output/tables/gt_ocpop.RData
        #rdata2: output/tables/gt_gpcpop.RData        
        #rdata1_discl: output/tables/gt_ocpop_unformatted.csv
        #rdata2_discl: output/tables/gt_gpcpop_unformatted.csv
        #tb01: output/tables/tb01_gpcr_region.csv
        #tb02: output/tables/tb02_gpcr_stp.csv # guidance says to not output identifiable regions
        #tb05: output/tables/tb05_gpcr_ethnicity.csv
        #tb06: output/tables/tb06_gpcr_ruc.csv
        #tb07: output/tables/tb07_gpcr_care.csv
        #tb08: output/tables/tb08_gpcr_dis.csv
        #tb09: output/tables/tb09_gpcr_imd.csv

  # https://docs.opensafely.org/en/latest/measures/
  generate_cohorts_long:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_measures_bycode --index-date-range "2019-01-01 to 2020-12-01 by month" --output-dir=output/measures
    outputs:
      highly_sensitive:
        cohort: output/measures/input_measures_bycode_*.csv

  generate_measures:
    run: cohortextractor:latest generate_measures --study-definition study_definition_measures_bycode --output-dir=output/measures
    needs: [generate_cohorts_long]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measure_*.csv

  run_model_long:
    run: r:latest analysis/03-createnattrends_codes.R
    needs: [generate_cohorts_long]
    outputs:
      moderately_sensitive:
        log: logs/log-03-createnattrends.txt
        tb01: output/tables/sc03_tb01_nattrends.csv
        fig01: output/plots/sc03_fig01_nattrends.svg
        fig02: output/plots/sc03_fig02_nattrends.svg
        fig03: output/plots/sc03_fig03_pracnatcoverage.svg
        fig04: output/plots/sc03_fig04_pracbyregcoverage.svg
        fig07: output/plots/sc03_fig07_ctv3nattrends.svg
        fig08: output/plots/sc03_fig08_ctv3nattrends.svg
        fig05: output/plots/sc03_fig05_ctv3pracnatcoverage.svg
        fig06: output/plots/sc03_fig06_ctv3pracbyregcoverage.svg

  run_model_measures:
    run: r:latest analysis/02-createtemporal.R
    needs: [generate_cohorts_long,generate_measures]
    outputs:
      moderately_sensitive:
        log: logs/log-02-createtemporal.txt
        red_measures: output/tables/redacted_*.csv
        #tb01: output/measures_gpc_pop.csv # redundant into. omit output
        fig01: output/plots/plot_overall_gpc_pop.svg
        #figall: output/plots/plot_each_*_practice.svg
        figquant: output/plots/plot_quantiles_*_practice.svg
        figlogquant: output/plots/plot_logquantiles_*_practice.svg

 

#  run_model_measuresDEBUG:
#    run: r:latest analysis/02-createtemporal_debug.R
#    needs: [generate_cohorts_long,generate_measures]
#    outputs:
#      moderately_sensitive:
#        log: logs/log-02-createtemporal-debug.txt
#        #tb01: output/measures_gpc_pop_debug.csv
#        #fig01: output/plots/plot_overall_gpc_pop_debug.svg
#        #figall: output/plots/plot_each_debug_*_practice.svg
#        #figquant: output/plots/plot_quantiles_debug_*_practice.svg
#        #figquant2: output/plots/plot_quantiles2_debug_*_practice.svg

  #run_model_redactedmeasures:
  #  run: r:latest analysis/02a-createredactedmeasure.R
  #  needs: [generate_cohorts_long,generate_measures]
  #  outputs:
  #    moderately_sensitive:
  #      log: logs/log-02a-createredactedmeasure.txt
  #      red_measures: output/tables/redacted2a_*.csv

### Weekly tallies to compare with OC/VC supplier data
  generate_cohorts_weekly2021:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_measures_weekly --index-date-range "2020-01-06 to 2021-03-22 by week" --output-dir=output/measures-week
    outputs:
      highly_sensitive:
        cohort: output/measures-week/input_measures_weekly_*.csv

  generate_measures_weekly2021:
    run: cohortextractor:latest generate_measures --study-definition study_definition_measures_weekly --output-dir=output/measures-week
    needs: [generate_cohorts_weekly2021]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures-week/measure_*.csv

  run_model_weekly2021:
    run: r:latest analysis/04-weekly2021.R
    needs: [generate_cohorts_weekly2021,generate_measures_weekly2021]
    outputs:
      moderately_sensitive:
        log: logs/log-04-weekly2021.txt
        tab1: output/tables/sc04-weeklynattrend.csv

#### Clinical history
  generate_cohorts_v2:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_v2
    outputs:
      highly_sensitive:
        cohort: output/input_v2.csv

  run_model_v2:
    run: r:latest analysis/05-createClinicalConditiontables.R
    needs: [generate_cohorts_v2]
    outputs:
      moderately_sensitive:
        log: logs/log-05-createClinicalConditiontables.txt
        gthtml1: output/tables/gt_econsult_pop_pre.html
        gthtml2: output/tables/gt_econsult_pop_post.html
        gthtml3: output/tables/gt_econsult_consultpop_pre.html
        gthtml4: output/tables/gt_econsult_consultpop_post.html
        gtglm1: output/tables/pracglm_submission.html
        gtglm4: output/tables/pracglm_submission_rob_logit.html
        gtglm2: output/tables/pracglm_submission_rob.csv
        gtglm3: output/tables/pracglm_submission_rob.html

# ### SNOMED check
#   generate_cohorts_checksnomed:
#     run: cohortextractor:latest generate_cohort --study-definition study_definition_checksnomed
#     outputs:
#       highly_sensitive:
#         cohort: output/input_checksnomed.csv


#   run_model_checksnomed:
#     run: r:latest analysis/0a-snomedcheck.R
#     needs: [generate_cohorts_checksnomed]
#     outputs:
#       moderately_sensitive:
#         log: logs/log-0a-snomedcheck.txt
#         tab1: output/tables/sc0a_snomedcheck_tallies.csv

# ### SRO template pipeline
#   SROtem_generate_study_population:
#     run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to 2020-12-01 by month" --output-dir=output
#     outputs:
#       highly_sensitive:
#         cohort: output/input_*.csv

#   SROtem_generate_study_population_practice_count:
#     run: cohortextractor:latest generate_cohort --study-definition study_definition_practice_count --output-dir=output
#     outputs:
#       highly_sensitive:
#         cohort: output/input_practice_count.csv

  
#   SROtem_generate_measures:
#       run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output
#       needs: [SROtem_generate_study_population]
#       outputs:
#         moderately_sensitive:
#           measure_csv: output/measure_*.csv

#   SROtem_get_patient_count:
#     run: python:latest python analysis/SROtem_get_patients_counts.py
#     needs: [SROtem_generate_study_population]
#     outputs:
#       moderately_sensitive:
#         text: output/patient_count.json


#   generate_notebook:
#     run: jupyter:latest jupyter nbconvert /workspace/notebooks/SRO-Notebook.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
#     needs: [SROtem_generate_measures, SROtem_generate_study_population_practice_count]
#     outputs:
#       moderately_sensitive:
#         notebook: output/SRO-Notebook.html

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime:

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

Job request

Status
Failed 
JobRequestError: All requested actions were already scheduled to run
Backend
TPP
Workspace
online_consultation
Requested by
Martina Fonseca
Branch
master
Force run dependencies
No
Git commit hash
0d347dd
Requested actions
  • run_model_v2

Code comparison

Compare the code used in this job request