i2b2 is an acronym for the Informatics for Integrating Biology & the Bedside (i2b2) Cohort Discovery System. UCLA i2b2 is a web-based application that enables UCLA investigators to identify potential research study cohorts using clinical data resources obtained through the UCLA Health System. Users can conduct interactive searches of data derived from patient care activities at Ronald Reagan UCLA Medical Center, Santa Monica UCLA Medical Center and other UCLA-affiliated clinics and departments.
What data is available through this tool?
Cohort counts rather than data sets are available through UCLA i2b2. These are based on de-identified data extracted from UCLA’s clinical data warehouse, transformed into a common data representation, and stored in a separate, dedicated data repository. Currently, the following search terms are available for querying: Demographics, Diagnoses, Procedures, Laboratory Tests, Area Deprivation Index (ADI), Medications, Visit Details, Vital Signs and Vital Status.
What can UCLA i2b2 not do?
UCLA i2b2 is a cohort discovery tool, meaning only patient counts can be retrieved. Individual patient-level data cannot be accessed through this tool, but it is possible to gather this information outside of i2b2. Please contact us directly at email@example.com if you would like individual patient-level data. These requests will be reviewed on a case by case basis.
Who can use the tool?
To access UCLA i2b2, researchers must be affiliated with a UCLA principal investigator and complete a training session.
If you don't have an account for UCLA i2b2, please email firstname.lastname@example.org to schedule a training session and receive additional information regarding the application.
View the UCLA i2b2 Training Webinar
Please click below to view the 15 minute training seminar.
Data is obtained from administrative records and electronic health records of patients that received care across the UCLA Health System (this does not include any of the LA County hospitals).
The time range in which data is available varies and depends on the data type. UCLA i2b2 currently has data on 4.5 million unique patients and is continually being updated. We will display a chart with data counts in the near future.
There is currently no option for patients to request that his/her information be excluded from UCLA i2b2, but all of the fields for every patient specified by HIPAA rules for safe harbor de-identification will be excluded from the data repository except for dates and zip codes.
Where do the ICD codes come from?
ICD codes are based on billing data from both inpatient and outpatient encounters.
What is the Area Deprivation Index (ADI)?
The Area Deprivation Index (ADI) score is a measure of the socioeconomic deprivation experienced in a geographic area. It was developed by Gopal Singh, PhD, MS, MSc using 17 different markers of socioeconomic status based on the 1990 Census Data. The current index score in UCLA i2b2 is based on the 2000 Census data. Some examples of the markers used to derive the ADI score include: income disparity, median home value, percent of families below federal poverty level and median family income. Higher index values represent higher levels of deprivation.
To learn more about the ADI score and the complete list of socioeconomic status markers, please review the Area Deprivation Index homepage found here.
What type of laboratory tests are in the UCLA i2b2 database?
UCLA i2b2 currently has the top 150 ordered laboratory tests from each UCLA institution with the earliest lab data going back to 1992. We are working on integrating all laboratory tests using the Logical Observation Identifiers Names and Codes (LOINC) system and hope to have this available in the near future.
If you are interested in a specific test that is not in UCLA i2b2, please contact us as we are interested in learning what researchers need.
What type of medications is in UCLA i2b2?
We have integrated both inpatient and outpatient medications using the Anatomical Therapeutic Chemical (ATC) Classification System hierarchy.
Is each patient reported by UCLA i2b2 a unique patient?
Yes, each patient reported by UCLA i2b2 is unique. Whether a query consists of multiple ICD-9 codes, demographics, date restrictions, etc., each patient is only counted once.
How can I use UCLA i2b2 to recruit patients for my study?
UCLA i2b2 is a cohort discovery tool and, thus, will only provide patient counts for a specific query. To go further and receive identified patient data, you will need to follow the steps below:
To get more information on how to access patient-level data from UCLA i2b2, please click on the link below:
How does the data compare with data available through other institutions?
We are performing a couple of initial comparisons between UCLA i2b2 data, data from UHC (university hospital consortium), and the state and the results reported from UCLA i2b2 were identical to the two other data sources.
Our next step in UCLA i2b2 is to perform more in-depth data quality checks. However, please report any query results that appear inaccurate so we can investigate right away.
Version Release: May 2016
A web browser is required to use UCLA i2b2. The following four browsers are currently supported:
New search concepts are available under the Navigate Terms pane in the Terminology Subject Areas tree. The new search concepts include:
By logging in to the Informatics for Integrating Biology & the Bedside (i2b2) Cohort Discovery System, I agree to protect the integrity and confidentiality of all information made available to me from the use of this system and to comply with limitations on the use of this system as stated below.
1. COHORT DISCOVERY SYSTEM SCOPE AND PURPOSE
- I agree to conduct queries only for purposes of planning research involving patients or patient data from UCLA.
- I understand that cohort discovery queries will be audited and I agree to be individually accountable for each query that is run using my account
2. I HEREBY AGREE:
- not to share my username or password with anyone and not to allow others to conduct queries using my account in any other way;
- not to attempt to identify individuals represented in the query results by any means, including use of local electronic health records or other information together with the results;
- not to use or disclose the results of cohort discovery queries to any entity or individual for any purpose other than (1) to serve as preliminary data in research funding proposals, (2) in Institutional Review Board applications to conduct proposed research, and (3) other uses individually approved by the UCLA Clinical and Translational Science Institute (CTSI) Informatics Program (IP) staff, or as required by law;
- to report in writing to the UCLA CTSI IP staff any use or disclosure of query results that I become aware of that are not provided for by this Agreement, including without limitation, any disclosure to an unauthorized individual or entity, within ten (10) days of its discovery;
- to immediately notify the UCLA CTSI IP staff of any request or subpoena for query results, or other official inquiries. To the extent that UCLA decides to challenge such requests, I will cooperate fully in any such challenge.