Open Consultation Hours

Have questions about data requests or resources such as i2b2, ACT, TriNetX, etc?
Join us during our open consultation hours or contact us to schedule a meeting.

Mondays

10-11 am

Monday
WebEx

Tuesdays

2-3 pm

Tuesday
WebEx

Request Consultation 

Contact us at
ctsidata@wakehealth.edu
to schedule a meeting.

All open office hours held virtually via WebEx.
See standing WebEx links above or search Informatics on events page to add specific date to your calendar.

Translational Data Warehouse (TDW)

The Translational Data Warehouse (TDW) is a comprehensive research data warehouse integrating clinical data from our WakeOne system and other research information from multiple data sources. Currently the TDW consists of clinical data which includes demographics, diagnoses, procedures, medications, lab results, vitals, and visit details from the medical record (historical and current).

Data can be used for retrospective chart reviews and analysis, identify patients for recruitment, or to pull aggregate numbers for cohort identification and build projected enrollment tables.

Informatics Spotlight PDF

Program Spotlight 

View the Informatics Program one-sheet summary!

 

Download PDF

   

Self-Service Model

The i2b2 platform is a query tool that allows investigators to query clinical data in the Translational Data Warehouse for cohort identification and pull detailed data for research projects. Medical Center users can automatically log in to i2b2 with valid CITI certification. Use of i2b2, as well as training on i2b2 or the Data Puller tool, is available at no cost.

Learn more about CITI certification and training

i2b2

SKAN

Prior to IRB approval, i2b2 can be used to pull aggregate numbers and enrollment tables based on inclusion and exclusion criteria. For IRB-approved studies, the Data Puller tool within i2b2 can be used to select and receive data elements based on HIPAA Waiver criteria approved in your IRB application.

Log in to i2b2

The SKAN (Search Kibana Accessible Notes) NLP (Natural Language Processing) system can be used to pull aggregate numbers based on inclusion and exclusion of content in clinical notes.

Log in to SKAN