Study Management REDCap

 Study data management 

REDCap (Research Electronic Data Capture) was launched at CDU in April 2012. REDCap is a secure, web-based electronic data capture system that is available to CDU researchers through the web application: https://redcap.cdrewu.edu. REDCap uses a MySQL database for data storage and facilitates dissemination and analysis of research study surveys as well as secure management of data from clinical trials and other clinical and basic science studies. It has been used successfully to manage data about biospecimens. REDCap is currently in use at over 300 institutions in the US and across the world. 

How to describe REDCap in the Facilities and Resources section of an NIH grant: REDCap is a secure, web-based electronic data capture system that is available to CDU researchers through the web application: https://redcap.cdrewu.edu. REDCap uses a MySQL database for data storage and facilitates dissemination and analysis of research study surveys as well as secure management of data from clinical trials and other clinical and basic science studies. 

How to describe REDCap on your CDU IRB application (items 10a and 10b): Study data were collected and managed using the REDCap1 electronic data capture resource administered by the Biomedical Informatics Core function of AXIS (Accelerating Excellence in Translational Research) and the UCLA Clinical and Translational Science Institute (CTSI). REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing: (1) an intuitive interface for validated data entry; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for importing data from external sources. CDU’s REDCap servers are hosted in a HIPAA-compliant manner by the SanDiego Supercomputer Center based at UC San Diego in San Diego, California. Vanderbilt University, with collaboration from a consortium of institutional partners, developed REDCap specifically around HIPAA-Security guidelines. REDCap can be used to easily build and manage online surveys and databases and all web-based information transmission is encrypted. REDCap currently supports over 400 consortium partners world-wide with over 50,000 research end-users(www.project-redcap.org). CDU’s implementation of REDCap can be found athttps://redcap.cdrewu.edu.1Paul A. Harris, Robert Taylor, Robert Thielke, Jonathon Payne, Nathaniel Gonzalez, Jose G. Conde, Research electronic data capture (REDCap) – A metadata-driven methodology and workflow process for providing translational research informatics support, J Biomed Inform. 2009Apr;42(2):377-81. 

How to acknowledge use of CDU’s implementation of REDCap in publications: Any publications resulting from the use of REDCap to collect and manage data at CDU should include the following acknowledgement: “This publication was made possible in part by NIH/NIMHD grant #U54MD007598 (formerly #U54RR026138) and by NIH/NCRR/NCATS grant #UL1TR000124.Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.” Any publications resulting from the use of REDCap to collect and manage data at CDU should include the following REDCap citation: Paul A. Harris, Robert Taylor, Robert Thielke, Jonathon Payne, Nathaniel Gonzalez, Jose G. Conde, Research electronic data capture (REDCap) – A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009 Apr;42{2):377-81. 

Study Data Analysis 

We can provide machine learning analyses for you research study data using a variety of techniques, including Bayesian networks, support vector machines, decision trees, neural networks, etc. We will help with data formatting, model selection for a predictive modeling problem, and predictions including sensitivity and specificity results as well as areas under the ROC curve. 

Computerized Clinical Decision Support and Geographic Information Systems 

We have expertise in developing computerized clinical decision support, including the use of alerts and reminders within electronic registries and GIS techniques that facilitate management of patients in medically underserved areas. 

Sociotechnical Studies 

It is widely recognized in the informatics field that along with the technical requirements outlined fora health information technology (HIT) project, an assessment of the sociotechnical factors that can impede successful implementation of a HIT is necessary. The literature on the adoption and diffusion of new technology suggests that stakeholders’ perceptions about innovations and the extent to which they see it as a “relative advantage” are key to the rate of diffusion and adoption. Given that low health literacy, distrust of technology and the healthcare system can be potential barriers to the acceptability of HIT in urban underserved settings, it is important to assess patient perceptions and health care organization level barriers and facilitators before widespread implementation of new HIT. 

Informatics-focused social scientific theories and methods can help in better understanding the impact and effectiveness of innovative HIT and identify the incongruities between the medical aims that drive such solutions and the on-the-ground experiences of those administering and receiving care. We provide such services, including guidance in the use of social scientific theories and methods to guide and evaluate implementation of new health information technologies, including in the use of qualitative methods such as focus groups interviews, in-depth interviews, ethnographic methods, shadowing, etc.). 

Training on Electronic Resources 

We provide one-on-one and group training on REDCap, CDU Profiles and other electronic resources. 

Download Study Data Management Document