Clinical research teams using the Indiana CTSI’s Clinical Data Interoperability Services (CDIS) tool can reduce data entry time by half
When Kiran Naqvi learned about a new tool that could pull data from electronic health records and into her REDCap study database as soon as it was available, she knew it had the potential to dramatically improve the workflow on her team.
The tool, Naqvi learned, is called Clinical Data Interoperability Services (CDIS), and the Indiana CTSI’s data and informatics team is helping clinical researchers implement it.
“With CDIS, we have been able to continue this study without having to hire another person to help with data entry, and coordinators can spend their time on other things, like clinical visits, where they are needed the most,” Naqvi said.
Automated data extraction saves time
Naqvi, a clinical research specialist at Riley Children’s Hospital, is part of a team working on an observational study that uses advanced molecular analyses of urine, blood, and kidney tissue samples to understand the biological causes and mechanisms of kidney diseases. The study, which is prospective, requires participants to make multiple visits to the Children’s Clinical Research Center (CCRC), and for the study team to track a large number of samples.
This work is time-intensive, said Naqvi. Study coordinators are working on multiple studies and don’t always have the capacity to spend hours on data entry.
Waqas Amin, MD, associate director of informatics for the Indiana CTSI, met with Naqvi and her team to talk about how automating their data extraction with CDIS could make their clinical research operations more efficient.
Naqvi, along with principal investigator Myda Khalid, MD, and lead coordinator Sherry Wilson, decided to use the tool after they determined that it would reduce the amount of time coordinators would spend on data entry by more than half.
Troy Carter at IU Health developed and built the customized CDIS tool for their particular database, and put it into operation shortly afterward.
“CDIS has worked very well for our needs. We can pull demographic information and labs directly from CERNER,” which is the electronic health record system IU Health is using until next year, Naqvi said. “Data gets pulled right away, as soon as the labs have resulted, which helps to keep the database updated.”
A “clear success”
According to Amin, CDIS has demonstrated the ability to retrieve up to 568 structured data elements per patient across multiple encounters by focusing on high-quality laboratory and demographic data.
“This provides researchers with timely, accurate information for their studies,” he said. “It has substantially improved research workflow by automating clinical data extraction and significantly reducing manual data entry and patient chart review time.”
He added that the extensive validation of the tool before and during implementation confirmed that extracted data matched the source record. No data quality concerns have been reported by study teams.
Some limitations do remain, Amin said. REDCap has constraints on the number of variables that can be extracted; there are brief processing delays before data are populated; and sometimes there are challenges with extracting complex data regarding medications and conditions. But the overall impact has been overwhelmingly positive.
“The REDCap CDIS implementation has been a clear success,” he said. “Users consistently report that the system has improved efficiency, and that they have appreciated the implementation team’s support throughout deployment.”
Amin noted that the implementation team is focused on making sure the tool will retain its capabilities when IU Health transitions from CERNER to Epic in 2027.
Are you interested in learning more about using CDIS in your clinical research? Contact Amin.
