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2) Computational Phenotypes: We have previously found that half of patients with an ICD-9 or ICD-10 diagnosis code in the electronic health record (EHR) for Type 2 Diabetes (T2DM) do not actually have the disease. The code for T2DM thus has low "precision" for predicting the patient's true condition or "phenotype". Most diagnosis codes have this problem to varying degrees. One consequence of this is that clinical trials overestimate the number of eligible patients from the EHR. As a result, the trials have low yield in recruiting patients and are slow or unable to meet enrollment targets.

Installation: 

The Digital Twin tools are in the i2b2-digitaltwin repository: https://github.com/i2b2/i2b2-digitaltwin. Steps for installation:

1) Download a copy of the repository. In the Release_1-8/NewInstall/Crcdata directory, edit the db.properties file as is done to install other i2b2 data components. Note that the project should be set to act, as some components require the ENACT ontology.

2) Run the following ant targets to install both loyalty cohorts and computational phenotypes.

Linux Run Command
ant -f data_build.xml create_crcdata_digitaltwin_tables_release_1-8
ant -f data_build.xml db_digitaltwin_load_data

Windows Run Command
%ANT_HOME%\bin\ant.bat -f data_build.xml create_crcdata_digitaltwin_tables_release_1-8
%ANT_HOME%\bin\ant.bat -f data_build.xml db_digitaltwin_load_data