Learn about CRC’s Informatics resources

CRC Resources - Informatics



CRC informatics and computing resources include:

  • Computer Laboratory
  • Data Collection and Storage
  • Data Management Planning / Software Development
  • Custom Hardware / Software System Development for Data Collection and Analysis
  • Automated Surveys
  • CRC Intranet Data Resources

We are here to provide you with the informatics solution tailored to your study through the use of existing VICTR tools for electronic data collection and data management or the implementation of new solutions according to your specific needs. Please let me know if you need help defining a data collection strategy for your study, we can discuss what your specific needs are and determine the best approach to take.

Vital Signs Data Collection


Collection, manipulation, storage, retrieval, and classification of information recorded using vital sign monitors. Devices allow for recurrent/cyclic interventions as well as manual measurements.


CRC Interactive Voice Response System (IVR)


IVR software is a solution used to design and administer user-friendly automated surveys at Vanderbilt University Clinical Research Center. The tool is a secure, locally hosted solution for IVR (Interactive Voice Response) data acquisitions, providing:

  • Cost effective access to voice response technology for all projects
  • Automated data collection and validations
  • Audit trails for record validation and troubleshooting
  • Integration with third party database backend and repositories
  • One month average project implementation
  • System generated prompts/menus
  • Human generated prompts/menus
  • From simple to complex branching logic support
  • Answer validation

Example of survey applications:

  • Questionnaires
  • Structured Interviews
  • Applicant Screening
  • Information for Hotlines
  • Satisfaction or follow-up surveys
  • Patient reminders

For over four years the Clinical Research Center has built the proficiency to host automated IVR solutions following best practices for data manipulation.