EHR-Generated Clinical Measures Useful in Estimating Quality of Care

Nine of 12 clinical quality measures generated by interoperable electronic health records showed good consistency in estimating quality of care, a recent AHRQ-supported study concludes. The study, “Accuracy of Electronically Reported ‘Meaningful Use’ Clinical Quality Measures: A Cross-Sectional Study,” which appeared in the January 15 issue of the Annals of Internal Medicine, suggests that electronic quality measurement can identify areas in need of improvement and quantify the impact of changes that have been made. This study was a part of AHRQ’s research into how to improve electronically enabled quality measurement. Select to access a short video about this project. Select to access the abstract on PubMed.®

Ann Intern Med. 2013 Jan 15;158(2):77-83. doi: 10.7326/0003-4819-158-2-201301150-00001.

Accuracy of Electronically Reported "Meaningful Use" Clinical Quality Measures: A Cross-sectional Study.

Kern LM, Malhotra S, Barrón Y, Quaresimo J, Dhopeshwarkar R, Pichardo M, Edwards AM, Kaushal R.

Abstract

Chinese translation

BACKGROUND:

The federal Electronic Health Record Incentive Program requires electronic reporting of quality from electronic health records, beginning in 2014. Whether electronic reports of quality are accurate is unclear.

OBJECTIVE:

To measure the accuracy of electronic reporting compared with manual review.

DESIGN:

Cross-sectional study.

SETTING:

A federally qualified health center with a commercially available electronic health record.

PATIENTS:

All adult patients eligible in 2008 for 12 quality measures (using 8 unique denominators) were identified electronically. One hundred fifty patients were randomly sampled per denominator, yielding 1154 unique patients.

MEASUREMENTS:

Receipt of recommended care, assessed by both electronic reporting and manual review. Sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and absolute rates of recommended care were measured.

RESULTS:

Sensitivity of electronic reporting ranged from 46% to 98% per measure. Specificity ranged from 62% to 97%, positive predictive value from 57% to 97%, and negative predictive value from 32% to 99%. Positive likelihood ratios ranged from 2.34 to 24.25 and negative likelihood ratios from 0.02 to 0.61. Differences between electronic reporting and manual review were statistically significant for 3 measures: Electronic reporting underestimated the absolute rate of recommended care for 2 measures (appropriate asthma medication [38% vs. 77%; P < 0.001] and pneumococcal vaccination [27% vs. 48%; P < 0.001]) and overestimated care for 1 measure (cholesterol control in patients with diabetes [57% vs. 37%; P = 0.001]).

LIMITATION:

This study addresses the accuracy of the measure numerator only.

CONCLUSION:

Wide measure-by-measure variation in accuracy threatens the validity of electronic reporting. If variation is not addressed, financial incentives intended to reward high quality may not be given to the highest-quality providers.