Validation of Stroke Meaningful Use Measures in a National EHR System

Phipps M, Fahner J, Sager D, Coffing J, Maryfield B, Williams LS. Validation of Stroke Meaningful Use Measures in a National EHR System. [Abstract]. Stroke; A Journal of Cerebral Circulation. 2015 Apr 1; 46(4):AWP275.

Background: The Affordable Care Act included eight stroke indicators in its Meaningful Use (MU) program. This project evaluated stroke MU measures in national VHA data and determined sources of error in using centralized electronic health record (EHR) data. Methods: We converted local SQL queries that generated stroke indicators to run on VA Central Data Warehouse (CDW) data, mapping each local data element to the corresponding CDW data element and table. Numerator (NM) and denominator (DN) results were generated from CDW data in a sample of 2200 ischemic stroke admissions in 11 VA hospitals. Local and CDW NM and DN results were compared to chart review. NM and DN mismatch reports were iteratively examined to identify, categorize, and correct sources of error. We calculated passing rates, sensitivity and specificity for the NMs and DNs, and an overall accuracy kappa statistic. Results: Results for two measures (VTE prophylaxis and antithrombotic (AT) by day 2) are shown in the Table. The most common error in VTE prophylaxis was failure to identify mechanical prophylaxis devices (171/185 NM false negative errors), and in the AT measure was failure to identify a contraindication to therapy (50/59 DN false positive errors). Errors impacting multiple indicators included difficulty identifying Comfort Care status, discrepancies between electronic and charted medication administration, and difficulty identifying medications given in the ER. Passing rates (chart review vs. EHR) were higher with chart review for VTE (87% vs 76%) but similar for AT (91% vs 90%). Conclusions: Stroke MU indicators can be relatively accurately generated from existing EHR systems but accuracy decreases in central compared to local data sources. To improve stroke MU measure accuracy, EHRs should include standardized data elements for devices, Comfort Care status, recording contraindications, and medications given in the ER. Key Words:Quality assessment Health policy Stroke Health services research