Job request: 23778
- Organisation:
- The London School of Hygiene & Tropical Medicine
- Workspace:
- covid_collateral_hf_update
- ID:
- sp3rinmbtfglypk2
This page shows the technical details of what happened when the authorised researcher Emily Herrett 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:
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highly_sensitive
- Researchers can never directly view these outputs
- Researchers can only request code is run against them
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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
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6wlf765s4qubk4jt
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- Job identifier:
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ljwjnofsojev6m4t - Error:
- cancelled_by_user: Cancelled by user
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- Job identifier:
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sfje5w6hrrwg6xmh - Error:
- cancelled_by_user: Cancelled by user
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kkfuit4kkqllr3oe
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kpkrh5ealuulfxtz
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- Job identifier:
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ezdcyqevcah3mjwd - Error:
- cancelled_by_user: Cancelled by user
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: 10000
actions:
generate_dataset_prepandemic:
run: ehrql:v1 generate-dataset analysis/dataset_definition_prepandemic.py --output output/dataset_prepandemic.csv
outputs:
highly_sensitive:
dataset: output/dataset_prepandemic.csv
generate_dataset_pandemic:
run: ehrql:v1 generate-dataset analysis/dataset_definition_pandemic.py --output output/dataset_pandemic.csv
outputs:
highly_sensitive:
dataset: output/dataset_pandemic.csv
generate_dataset_postpandemic:
run: ehrql:v1 generate-dataset analysis/dataset_definition_postpandemic.py --output output/dataset_postpandemic.csv
outputs:
highly_sensitive:
dataset: output/dataset_postpandemic.csv
# Generate datasets for analysis 001
generate_analysis_datasets:
run: stata-mp:latest analysis/001_cr_define_covariates_cohorts.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic]
outputs:
highly_sensitive:
log1: logs/001_cr_define_covariates_cohorts.log
data1: output/prepandemic.dta
data2: output/pandemic.dta
data3: output/postpandemic.dta
# Drug prevalence dataset: 102
generate_drugprevalence:
run: stata-mp:latest analysis/102_cr_drug_prevalence_contraind.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/102_cr_drug_prevalence.log
data1: output/tabfig/prevalences_summary_*.dta
data2: output/tabfig/prevalences_summary_redacted_rounded_overall.dta
# Drug prevalence dataset: 102A
generate_drugprevalence_coms:
run: stata-mp:latest analysis/102_A_cr_drug_prevalence_contraind_combinations.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/102_A_cr_drug_prevalence_combinations.log
data1: output/tabfig/drugcombinations.csv
# Cohort rates: 103
generate_rates:
run: stata-mp:latest analysis/103_cr_cohort_rates_repeated.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/103_cohort_rates_repeated.log
data1: output/tabfig/rates_repeated_pandemic_redacted_rounded.dta
data2: output/tabfig/rates_repeated_prepandemic_redacted_rounded.dta
data3: output/tabfig/rates_repeated_postpandemic_redacted_rounded.dta
# Cohort rates: 103A
generate_rates_A:
run: stata-mp:latest analysis/103_A_cr_cohort_rates_repeated_diabetes.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/103_A_cohort_rates_repeated_diabetes.log
data1: output/tabfig/rates_repeated_pandemic_redacted_rounded_diabetes.dta
data2: output/tabfig/rates_repeated_prepandemic_redacted_rounded_diabetes.dta
data3: output/tabfig/rates_repeated_postpandemic_redacted_rounded_diabetes.dta
# Generate table 1 :104
generate_table1:
run: stata-mp:latest analysis/104_cr_table1.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/104_cr_table1.log
data1: output/tabfig/table1_prepandemic_redacted_rounded.csv
data2: output/tabfig/table1_pandemic_redacted_rounded.csv
data3: output/tabfig/table1_postpandemic_redacted_rounded.csv
# Drug graphs: 105
generate_druggraphs:
run: stata-mp:latest analysis/105_cr_drug_prevalence_graphs.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets, generate_drugprevalence]
outputs:
highly_sensitive:
log1: logs/105_cr_graphs.log
moderately_sensitive:
Figures1: output/tabfig/*_prevalences_by_drug_*.svg
Figures2: output/tabfig/prevalences_*.svg
# Drug graphs: 106
generate_rategraphs:
run: stata-mp:latest analysis/106_cr_graphs_rates.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets, generate_rates]
outputs:
highly_sensitive:
log1: logs/106_cr_graphs_rates.log
moderately_sensitive:
Figures1: output/tabfig/rates_*.svg
# Drug graphs: 107
generate_drugescalation:
run: stata-mp:latest analysis/107_cr_cohorts_escalation.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/107_cr_cohorts_escalation.log
moderately_sensitive:
Figures1: output/tabfig/escalation_*.svg
# Drug graphs: 108
generate_30d_mort:
run: stata-mp:latest analysis/108_cr_cohorts_posthosp_mortality.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/108_cr_cohorts_posthosp_mortality.log
moderately_sensitive:
Figures1: output/tabfig/30d_mort_*.svg
generate_dataset_timeseries:
run: ehrql:v1 generate-dataset analysis/dataset_timeseries.py --output output/dataset_timeseries.csv
outputs:
highly_sensitive:
dataset: output/dataset_timeseries.csv
# Measures
measures:
run: ehrql:v1 generate-measures analysis/measures.py
--output output/measures/measures.csv
--
--start-date "2018-01-01"
--intervals 100
outputs:
moderately_sensitive:
measure_csv: output/measures/measures.csv
# Time series do file
#--dummy-data-file measures_dummy.csv
Timeline
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Created:
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Started:
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Finished:
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Runtime: 87:09:47
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job request
- Status
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Failed
- Backend
- TPP
- Workspace
- covid_collateral_hf_update
- Requested by
- Emily Herrett
- Branch
- main
- Force run dependencies
- No
- Git commit hash
- 92a5713
- Requested actions
-
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generate_dataset_postpandemic -
generate_analysis_datasets -
generate_drugprevalence -
generate_drugprevalence_coms -
generate_rates -
generate_rates_A -
generate_table1 -
generate_druggraphs -
generate_rategraphs
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Code comparison
Compare the code used in this job request