A new study suggests that the quality data residing in EMRs may or may not reflect the actual state of the patient population. The study, which appears in the Annals of Internal Medicine, concludes that the accuracy of EMR-based quality measures can be questionable, sometimes overestimating and sometimes underestimating the delivery of quality care.
The study, done by Weill Cornell Medical College, analyzed clinical data from EMRs run by one of the largest community health center networks in New York state, reports Healthcare IT News. Researchers from Weill Cornell looked at the accuracy of EMR reporting for 12 quality measures (11 of which are Meaningful Use standards).
After comparing their analysis with a manual check, researchers found that in three areas, reports drawn from EMRs weren’t as accurate as they should be. They underestimated the percentage of patients getting prescriptions for asthma and those getting vaccinations to protect against bacterial pneumonia. Another problem measure predicted that more patients with diabetes had healthy cholesterol levels than actually did.
What’s causing the gap in accuracy? For one thing, doctors and nurses entering data in EMRs may be entering data in fields that aren’t being captured by quality reporting algorithms, HIN’s piece suggests.
While the story doesn’t say this, I think there’s also some gaps in quality reporting generally which have existed since well before EMRs became commonplace. I don’t know how to address the issue — other than perhaps appoint a nurse-manager to track the progress of quality reporting and ride herd on their colleagues — but given how important quality reporting is, it seems that it will be necessary to devote more resources to the problem.