HICOR_RetainDataFormatting

reformatting of HICOR claims data for the Emergency Department/Inpatient Stay project to assess risk through the retain model this currently depends on pulling data from a SQL database on a test server managed by CIT

Arguments

--dataset the dataset to reformat (1=train, 2=dev/validate, 3=test). defaults to 2

--outcome outcome variable in question (ed or ip). defaults to both

--max max number of visits to query from main DB. defaults to None

--trusted use trusted mssql connection (requires proper driver) defaults to None

--use_partials query and include partial days on event-final claimdays defaults to None

--match_num find positive instances and match with 'N' defaults to None

--day_instance make a new instance for each patient, for each new day defaults to None

Examples

in order to create the 1:10 matched controls data set for the training data in order to assess risk of Emergency Department visits and use partial data from the final day prior to ED event for all positive instances (assuming the appropriate sql server drivers are present):

python process_hicor.py --dataset 1 --outcome ed --trusted --use_partials --match_num 10

in order to create the initial dataset formatting, where all positive outcome instances were captured as well as the final negative day for all patients, for the dev/validation dataset, in order to assess the risk for Inpatient Stays but want to exclude the final outcome day entirely (assuming the user has sql server connection details in the config file):

python process_hicor.py --dataset 2 --outcome ip

in order to create the "final test set"; the dataframe where each active day of claims for each patient is a new instance for ED risk and use partial data from the final day prior to ED event (assuming the appropriate sql server drivers are present):

python process_hicor.py --dataset 3 --outcome ed --trusted --day_instance --use_partials

Notes

--max is useful for testing purposes, so that smaller data sets can be created to quickly test end to end dataset creation, and retain training and testing

'config_default.json' contains examples of variables and connection string details for sql server access. It must be replaced with a 'config.json' that contains the actual values

Dependencies

Python 3.6

external librarys: ast, pandas, sqlalchemy, tqdm