Skip to Content
SBMI Horizontal Logo

Analysis of Clinical Quality Measures to Assess Improvement from Meaningful Use

Author: Lidia Turrubiartes, BA

Primary Advisor: Dean Sittig, PhD

Committee Members: Susan Fenton, PhD, RHIA, FAHIMA

Masters thesis, The University of Texas Health Science Center School of Health Information Sciences at Houston.


Background: One of the programs developed through the Health Information Technology for Economic and Clinical Health (HITECH) Act, a result of the American Recovery and Reinvestment Act of 2009 (ARRA), provides incentive payments for healthcare providers to implement electronic health records (EHRs) and achieve meaningful use (MU). One of the criteria for payment is to report clinical quality measures (CQMs), which provide a tool to providers to evaluate their quality of care. The ultimate goal of MU is to improve the areas being measured by CQMs. However, there is little evidence that shows improvements in CQMs through MU. Analyses of CQMs reported across all current reporting years for a large health system may provide better insight for healthcare quality improvements from MU.

Materials and Methods: SPSS crosstabs analyses were performed for each proportion type CQM to compare actions performed across the three years. Trend line graphs for both proportion and continuous variable type CQMs were created. Changes in scores from the first year of MU to the most current year of MU were calculated to get an “overall” picture of the improvement progress made for each CQM.

Results: There was a statistical difference in actions performed across the three years for 6 of the 9 proportion measures at p < 0.001. The trend line graph for proportion type measures revealed 3 distinct CQM sets for ranges 0%-15%, 20%-70%, and 68%-100%. 4 CQMs have score improvements the second year, but decrease the third year. 4 CQMs have score improvements each following year, and 1 has a lower score each following year. The continuous variable measures revealed 2 sets, each cluster of 3 corresponding to 1 CQM group. All of these CQMs improved each following year, determined by a decrease in patient admittance wait times. For overall change, 12 of the 15 CQMs improved, 2 CQMs worsened, and 1 showed no change.

Discussion:The vast majority of CQMs improved over the course of the three years through MU. CMS 71 – Anticoagulation Therapy for Atrial Fibrillation/Flutter and CMS 72 – Antithrombotic therapy by end of hospital day two should be further investigated to determine causes for declining trends. The health system used EHRs prior to the MU program, so familiarity with functions may affect improvement. Comparison of scores from different reporting length periods may not provide the most accurate sample data for analyses. The hospital improvement programs should be investigated to determine whether they are geared toward MU goals or if improvement toward MU is just a chance consequence.

Conclusion: For an EH entity with prior years of use of EHRs, there is improvement in CQMs following MU. The improvements in CQMs across the three years may be attributed to improved healthcare quality. However, further studies should be done to determine that the EHR users are not simply inputting data to meet MU goals or neglecting other areas of care and focusing on measures that need to be reported.