How EHR-Based Card Studies Can Streamline Data Collection, Analysis

EHR-based card studies can help streamline data collection and drive deeper analysis, according to a study published in The Annals of Family Medicine.

Card studies are short surveys about the circumstances within which patients receive care. As the name suggests, clinicians traditionally complete them on physical cards.

Researchers created an EHR-embedded card study to decrease paper-based studies' financial and logistical challenges.

While paper card studies require physical materials and postage, the only cost for the EHR-based card study was time spent on design, programming, data extraction, analysis, and participant incentives.

A programmer spent approximately 25 hours conceptualizing and programming the card requests. Analysts spent about 30 hours on data extraction, formatting, and linking survey results to EHR data.

"The full-time equivalent cost was financially offset by study time not spent managing the logistics of survey printing, distribution, tracking, collection, and data entry," the researchers found.

Additionally, integrating the card study into the EHR simplified the process for respondents. Clinicians did not have to remember when they were expected to complete a card because the EHR provided prompts.

"The response rate of 79 percent is toward the high end of healthcare clinician survey response rates in the United States, which range from 60 percent to 83 percent, even though one-half of the data collection occurred during a global pandemic," the researchers noted.

Paper-based card studies are usually anonymous, which makes linking clinician and patient information to the answers on the physical cards difficult. Further, card studies that collect demographic data take longer, increasing clinician burden.

"The use of EHR-embedded card studies addresses many of the challenges inherent to paper-based data collection and can yield quality data, rich analytic data sets, and relatively high response rates, presenting new opportunities to conduct effective point-of-care research," the authors said.

"Future EHR-embedded card studies could replicate many of the same processes and automate some of the data extraction and cleaning, which should substantially decrease labor costs," the researchers continued. "The use of EHR-embedded card studies might also be cost effective at scale because programming costs remain comparable regardless of the number of card requests."

Study clinics were members of OCHIN, a nonprofit health IT provider that hosts a shared instance of the Epic EHR tailored for community health centers. The authors noted this as a limitation to their approach.

"The success of our approach was facilitated by the OCHIN environment; we had access to in-house expertise in EHR programming and data extraction, and all participating clinics used the same instance of the Epic EHR," they wrote. "Settings that lack this technical expertise or that require card study customization across multiple EHRs might have a different cost/benefit ratio."