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Leveraging the EMR for Clinical Science

February 7, 2012
by Gabriel Perna
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Researchers at the Stanford University School of Medicine are using EMRs to make pain research breakthroughs

In the world of medical research, the emergence of the electronic medical record (EMR) in hospitals is a game-changer, giving researchers the opportunity to use large, previously unobtainable data sets for their studies. You don’t have to tell that to Atul Butte, M.D., director for the Center for Pediatric Bioinformatics at Lucile Packard Children’s Hospital (Palo Alto, Calif.) and associate professor at Stanford University School of Medicine.  

As part of a Stanford research team, Butte and his colleagues mined a huge collection of data from EMRs to conclude that women report more pain than men. The Stanford research team used initial data from 72,000 patients that recorded 160,000 pain scores. It was eventually whittled down to 11,000 patients across 47 separate diagnostic categories that recorded 40 pain reports for each gender. Thanks to prodding from pain researchers, the EMR was able to record pain-scores along with other standard vital signs like blood-pressure and heart rate.

“We record those pain measures, it’s not just acted on, it’s recorded back into the EMR,” Butte says. “We realized that this enabled us to do a study on pain measurement, on a scale that has never been done before. Before our study, pain measures have been limited small data sets or studies.”

Thanks to the Stanford Translational Research Integrated Database Environment (STRIDE), which hosts a clinical data warehouse for two hospitals, Lucile Packard and Stanford Hospital and Clinics, the data from the pain researchers was stored securely. STRIDE, which is a standards-based informatics platform supporting clinical and translational research, is where the patient information was de-identified under protocols, says Butte.

The study came together, Butte says, because of a group of authors that have pain research and informatics backgrounds including Butte’s student, Linda Liu, postdoctoral scholar David Ruau, Martin Angst, M.D., professor of anesthesia, and David Clark, M.D., professor of anesthesia, While the researchers confirmed data from previous studies, they did make several breakthroughs in discovering unreported gender differences in pain measurement for various diseases.

Large-Scale Study

The idea of taking data from an EMR for research purposes isn’t completely novel, Butte concedes. For the most part it has been done on a smaller scale. He notes many providers are leveraging the EMR as a way to improve quality-of-care within their own institutions, which is research in its own right. However, looking at the EMR as a way to “answer the broader questions of science,” is not something you see a lot of people doing, he says.

The results of the study naturally came with various limitations, specifically for pain measurement itself. “If we ask an adult to measure pain on a scale from 0 to 10, it might look like a perfect measurement in the electronic medical record system. But there are some obvious things it doesn’t capture. For instance, when the nurse is asking about their pain, we can’t tell if it was a male nurse or a female nurse,” Butte says, adding that variation could change the answer from the patient. There were other caveats such as a lack of information on whether or not the patient was treated previously or not.

Essentially, this is a huge difference between an EMR-based study and a typical research study. “We can’t capture everything as we might be able to in a controlled setting,” Butte says. “But the controlled setting would be in a smaller study.”

Atul Butte, M.D.

Lasting Impact

The lasting impact of EMR-related studies will be huge, Butte predicts. Over the next 10 years, as every hospital in the country adopts an EMR, he says studies on pain will be able to include data from one million patients or more, not just 11,000. He says, in the short term, this research will be able to improve quality-of-care for providers. Long-term, molecular biologists and other scientific researchers will have access to large scores of human data to study disease, rather than relying on animal test subjects.  

“It’s amazing to know what kind of scientific questions we are enabling as we move towards the deployment of EMRs,” Butte says.

For the Stanford project, Butte says the researchers will continue their work and look into using the EMR to study other vital signs such as temperature, heart rate and ethnicity. Eventually, he foresees taking specific diseases and studying them one by one.



Since everyone has to have a login to the EMR, couldn't you use that employee data to get the gender of the nurse?

Unfortunately, our deidentified extract of the EHR data did not include any link back to the identity of the recorder, but in theory, yes, you are right.