i2b2 Community Wiki
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  • i2b2 is an open-source clinical data warehousing and analytics research platform used at over 250 locations worldwide. i2b2 enables sharing, integration, standardization, and analysis of heterogenous data from healthcare and research.
  • The i2b2 Community is a life-sciences-focused open-source, open-data community. This wiki is the central place for the i2b2 Community to communicate and share projects with other users. Here you will find the latest information on the i2b2 Software, what others in the community are doing, and find resources to help answer any questions you may have about the i2b2. 
  • i2b2 is part of the i2b2 tranSMART Foundation, which brings together an NIH-funded enterprise clinical research platform (i2b2) and pharma-developed software for translational research studies (tranSMART).




Older, unsupported add-ons are on the Archived Optional Components page.
  • i2b2 Web Client
  • The i2b2 Web Client is a collection of client-side components designed as an YUI AJAX-based plug-ins that communicate with i2b2 Cells and allow the investigator to query and display the data of the hive.
  • Install Guide
  • Project Request Guide
  • Go to Download


Documentation

Get Software

Current Announcements


Software

Version


i2b2 Binary Download 1.8.1a (September 2024)

Download Upgrade

i2b2 Core Server Source Code

1.8.1a (September 2024)

i2b2 Core Data Source Code

1.8.1a (September 2024)

i2b2 Web Client

1.8.1a (September 2024)

i2b2 Documentation

1.8.1a (September 2024)

i2b2 VMWare Server/Client Demo

1.8.1a

i2b2 Docker Demo (unofficial)1.8.0 

i2b2 Workbench

2.0.01 (October 17, 2017)



06/2024:



Newest i2b2 Community Projects

Links and Older Announcements


Accrual to Clinical Trials
The Accrual to Clinical Trials (ACT) project goal is to create a federated network of National Clinical and Translational Science Award (CTSA) Consortium institutions to significantly increase participant accrual to the nation's highest priority clinical trials.
Multi-fact Table
The multi-fact table project is a new feature introduced in 1.7.09 that enables the i2b2 to query more than one fact table. This new feature empowers the i2b2 to adapt to the needs of such projects as the Patient Centered Outcome Research Institute (PCORI) network and the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). It can also be used for sites that want to be able to query both genomic and phenotype data but don't want the data to reside in a single table.
OMOP
The legacy i2b2 data model is comprised of a central fact table (observation_fact) surrounded by multiple dimension tables (star schema). In the Observation Medical Outcomes Partnership (OMOP) Clinical Data Model (CDM) rather than a central fact table, we have a collection of them distinguished by domain: procedures, condition, drug, measurement, observation, etc. In this project, we modify the CRC to run queries against multiple domain fact tables as dictated by the metadata.
RDF to i2b2 Conversion
Synthea data in i2b2
Synthea synthetic data can now be loaded into i2b2 for testing. A 63k sample of SyntheticMass patients is available for download.
i2b2 on Genomics Data
This community project extends the current i2b2 query functionality by providing the ability to query for genotyped subjects by specific annotations related to genetic variants. Also, new query widgets have been built in the i2b2 web client that leverages existing i2b2 infrastructure for querying large strings of text stored in the observation_blob field of the observation_fact table.

See All Community Projects

Important links:

Older Announcements:

i2b2 Log4j Vulnerability Update

None of the versions of i2b2 are using the affected (vulnerable) version of Log4j. For versions prior to 1.7.13, a patch is available to remove the features in Log4j with security flaws. i2b2 1.7.13 has been upgraded to the latest version of Log4J.

Consortium for Clinical Characterization of Covid-19 by EHR (4CE)

4CE is an international consortium for electronic health record (EHR) data-driven studies of the COVID-19 pandemic. The goal of this effort—led by the i2b2 international academics users group—is to inform doctors, epidemiologists and the public about COVID-19 patients with data acquired through the health care process.

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