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. 2021 May 17:2021:565-574.
eCollection 2021.

Ranking Methodology to Evaluate the Severity of a Quality Gap Using a National EHR Database

Shivani Sivasankar  1   2 , An-Lin Cheng  1 , Mark Hoffman  1   2
Affiliations

Ranking Methodology to Evaluate the Severity of a Quality Gap Using a National EHR Database

Shivani Sivasankar et al. AMIA Jt Summits Transl Sci Proc. .

Abstract

Selecting quality improvement projects can often be a reactive process. In order to demonstrate a data-driven strategy, we used multi-site, de-identified electronic health record (EHR) data to prioritize the severity of a quality concern: inappropriate A1c test orders for sickle cell disease patients in two randomly chosen facilities (Facility A & B). The best linear unbiased predictions (BLUP) generated from Generalized Linear Mixed Model (GLMM) was estimated for all 393 facilities with 37,151 SCD patients in the Cerner Health FactsTM (HF) data warehouse based on the ratio of inappropriate A1c orders. Ranking the BLUP after applying the GLMM indicates that the facility A being in the second quartile may not have a quality gap as significant as facility B in the top quartile for this quality concern. This study illustrates the utility of multisite EHR data for evaluating QI projects and the utility of GLMM to enable this analysis.

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Figures

Figure 1.
Figure 1.
Facility A and facility B are within the second quartile among the range of the ratio of SCD patients with A1c tests from all facilities in HF for the year 2016
Figure 2.
Figure 2.
Facility A is in the second quartile and facility B is in the top quartile among the range of BLUP values estimated through GLMM from all the facilities in HF for the year 2016
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