"The doctors in the ER were trying to figure out whether the shortness of breath in this woman was due exclusively to her failing heart, or was there a problem with pneumonia," Resnik says. "People who have pneumonia do not respond promptly to [BiPAP] treatment. But she responded promptly. This gave them information."
Resnik bets that few point-and-click EMRs have a check box or slider control for how quickly a patient responded to a treatment.
Text fields in EMRs can capture this information, but in a busy exam room, with doctors trying to point, click, and enter EMR data during the exam, while also trying to maintain eye contact with the patient, how much time will be left for text entry?
The dilemma compounds when you realize that any data entered in text fields will resist analysis. Database analysis works best with discrete numbers. So even if we get doctors to enter the portions of their narrative that don't fit in discrete data fields, we've lost the ability to really analyze that data.
As an experiment, Resnik and some other researchers took 20 cardiology dictations and went through them manually, highlighting the info that could be placed in discrete fields, without having to type into a text box.
"Then we took two cardiology experts and said, 'Let's pretend this clinical record is somebody a doctor across the country referred to you as a case,'" Resnik says. Researchers had highlighted info that couldn't be placed in the discrete fields, and they asked the cardiologists to rate how severe a gap in the record the highlighted information was.