Job request: 20345
- Organisation:
- Bennett Institute
- Workspace:
- opioids-covid-research
- ID:
- dxdgwmzqkt5zbho4
This page shows the technical details of what happened when the authorised researcher Andrea Schaffer 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.
Jobs
-
- Job identifier:
-
rznh7wpmjchfuspp
Pipeline
Show project.yaml
######################################
# This script defines the project pipeline -
# it specifies the execution orders for all the code in this
# repo using a series of actions.
######################################
version: '3.0'
expectations:
population_size: 10000
actions:
generate_dataset_table:
run: ehrql:v0 generate-dataset analysis/define_dataset_table.py
--output output/data/dataset_table.csv.gz
outputs:
highly_sensitive:
cohort: output/data/dataset_table.csv.gz
# Measures - test
measures_test_1:
run: ehrql:v0 generate-measures analysis/measures_test_1.py
--output output/measures/measures_test_1.csv
--
--start-date "2018-01-01"
--intervals 12
outputs:
moderately_sensitive:
measure_csv: output/measures/measures_test_1.csv
# Measures - test
measures_test_2:
run: ehrql:v0 generate-measures analysis/measures_test_2.py
--output output/measures/measures_test_2.csv
--
--start-date "2018-01-01"
--intervals 12
outputs:
moderately_sensitive:
measure_csv: output/measures/measures_test_2.csv
# Measures - prevalent and new prescribing - overall
measures_overall:
run: ehrql:v0 generate-measures analysis/measures_overall.py
--output output/measures/measures_overall.csv
--
--start-date "2018-01-01"
--intervals 54
outputs:
moderately_sensitive:
measure_csv: output/measures/measures_overall.csv
# Measures - prevalent prescribing - by demographic categories
measures_demo_prev:
run: ehrql:v0 generate-measures analysis/measures_demo_prev.py
--output output/measures/measures_demo_prev.csv
--
--start-date "2018-01-01"
--intervals 54
outputs:
moderately_sensitive:
measure_csv: output/measures/measures_demo_prev.csv
# Measures - new prescribing - by demographic categories
measures_demo_new:
run: ehrql:v0 generate-measures analysis/measures_demo_new.py
--output output/measures/measures_demo_new.csv
--
--start-date "2018-01-01"
--intervals 54
outputs:
moderately_sensitive:
measure_csv: output/measures/measures_demo_new.csv
# Measures - by opioid type
measures_type:
run: ehrql:v0 generate-measures analysis/measures_type.py
--output output/measures/measures_type.csv
--
--start-date "2018-01-01"
--intervals 54
outputs:
moderately_sensitive:
measure_csv: output/measures/measures_type.csv
# Measures - in people in care home
measures_carehome:
run: ehrql:v0 generate-measures analysis/measures_carehome.py
--output output/measures/measures_carehome.csv
--
--start-date "2018-01-01"
--intervals 54
outputs:
moderately_sensitive:
measure_csv: output/measures/measures_carehome.csv
## Process data - time series
process_data_ts:
run: r:latest analysis/process/process_data_ts.R
needs: [measures_overall, measures_demo_prev, measures_demo_new, measures_type, measures_carehome]
outputs:
moderately_sensitive:
timeseries_csv: output/timeseries/ts_*.csv
## Time series - rounding
rounding_ts:
run: r:latest analysis/process/rounding_ts.R
needs: [process_data_ts]
outputs:
moderately_sensitive:
timeseries_csv: output/timeseries/ts*.csv
# ## Process data - time series
# process_data_ts_nodemo:
# run: r:latest analysis/process/process_data_ts_nodemo.R
# needs: [measures_overall, measures_type, measures_carehome]
# outputs:
# moderately_sensitive:
# timeseries_csv: output/timeseries/t*.csv
# ## Time series - rounding
# rounding_ts_nodemo:
# run: r:latest analysis/process/rounding_ts_nodemo.R
# needs: [process_data_ts_nodemo]
# outputs:
# moderately_sensitive:
# timeseries_csv: output/timeseries/*.csv
## Results table
table:
run: r:latest analysis/descriptive/table_stand.R
needs: [generate_dataset_table]
outputs:
moderately_sensitive:
table: output/tables/table_*.csv
# OLD COHORTEXTRACTOR CODE
# ## Cohort data
# generate_study_population_1:
# run: cohortextractor:latest generate_cohort
# --study-definition study_definition
# --index-date-range "2018-01-01 to 2018-12-01 by month"
# --output-dir=output
# --output-format=csv
# outputs:
# highly_sensitive:
# cohort: output/input_*.csv
# generate_study_population_2:
# run: cohortextractor:latest generate_cohort
# --study-definition study_definition
# --index-date-range "2019-01-01 to 2019-12-01 by month"
# --output-dir=output
# --output-format=csv
# outputs:
# highly_sensitive:
# cohort: output/input*.csv
# generate_study_population_3:
# run: cohortextractor:latest generate_cohort
# --study-definition study_definition
# --index-date-range "2020-01-01 to 2020-12-01 by month"
# --output-dir=output
# --output-format=csv
# outputs:
# highly_sensitive:
# cohort: output/inpu*.csv
# generate_study_population_4:
# run: cohortextractor:latest generate_cohort
# --study-definition study_definition
# --index-date-range "2021-01-01 to 2021-12-01 by month"
# --output-dir=output
# --output-format=csv
# outputs:
# highly_sensitive:
# cohort: output/inp*.csv
# generate_study_population_5:
# run: cohortextractor:latest generate_cohort
# --study-definition study_definition
# --index-date-range "2022-01-01 to 2022-03-01 by month"
# --output-dir=output
# --output-format=csv
# outputs:
# highly_sensitive:
# cohort: output/in*.csv
# ## Ethnicity
# generate_ethnicity_cohort:
# run: >
# cohortextractor:latest generate_cohort
# --study-definition study_definition_ethnicity
# outputs:
# highly_sensitive:
# cohort: output/input_ethnicity.csv
# # Data processing ----
# ## Add ethnicity
# join_cohorts:
# run: >
# cohort-joiner:v0.0.48
# --lhs output/input_*.csv
# --rhs output/input_ethnicity.csv
# --output-dir output/data
# needs: [generate_study_population_1, generate_study_population_2,
# generate_study_population_5, generate_study_population_3,
# generate_study_population_4, generate_ethnicity_cohort]
# outputs:
# highly_sensitive:
# cohort: output/data/input_*.csv
# ## Generate measures - full population
# generate_measures:
# run: >
# cohortextractor:latest generate_measures
# --study-definition study_definition
# --output-dir output/data
# needs: [join_cohorts]
# outputs:
# moderately_sensitive:
# measure_csv: output/data/measure_*.csv
Timeline
-
Created:
-
Started:
-
Finished:
-
Runtime:
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job request
- Status
-
Succeeded
- Backend
- TPP
- Workspace
- opioids-covid-research
- Requested by
- Andrea Schaffer
- Branch
- main
- Force run dependencies
- No
- Git commit hash
- 119dfa5
- Requested actions
-
-
measures_test_2
-
Code comparison
Compare the code used in this job request