In a recent study, researchers found a wide measure-by-measure variation in the accuracy of electronic health records reporting. This variation may undermine the validity of electronic health records, which could affect the providers who receive financial incentives for adopting the system, according to study results.
Clinical data from the electronic health records (EHRs) of one of the largest community health center networks in New York were analyzed by researchers. Using 12 quality measures, 11 of which are included in the federal government’s set of measures for incentives, the researchers examined the accuracy of electronic reporting.
Overall, researchers found that electronic reporting underestimated the absolute rate of recommended care for two measures and overestimated care for one measure. Sensitivity of electronic reporting ranged from 46% to 98% per measure, according to study results, while specificity ranged from 62% to 97%, positive predictive value from 57% to 97% and negative predictive value from 32% to 99%.
In one example, an automated report generated by the reporting system showed 57% of eligible diabetic patients had controlled cholesterol; however, a manual check of the charts showed it was actually 37%. One problem may be that physicians and nurses filling out the EHRs may type in information in a place that is not being captured by quality reporting algorithms.
“This study reveals how challenging it is to measure quality in an electronic era. Many measures are accurate but some need refinement,” Rainu Kaushal, MD, MPH, director of the Center for Healthcare Informatics Policy, chief of the Division of Quality and Medical Informatics and the Frances and John L. Loeb Professor of Medical Informatics at Weill Cornell, stated in a press release. “Getting electronic quality measurement right is critically important to ensure that we are accurately measuring and incentivizing high performance by physicians so that we ultimately deliver the highest possible quality of care.”
For more information:
Kern LM. Ann Intern Med. 2013;158:77-83.
