Abstract
Introduction: Distinguishing heart failure (HF) patients who have suboptimal care quality due to physiological limitations vs non-clinical reasons (i.e. clinical inertia) may facilitate deployment of limited resources in a learning health system. We sought to evaluate the impact of accounting for physiological limitations on quality measures (QMs) using electronic health record (EHR) data. Methods: We developed EHR-based QMs for guideline-directed medical therapies (GDMT) for patients with HF with reduced ejection fraction (HFrEF), adapted from the 2020 ACC/AHA report on quality measures. In a cohort of HFrEF patients from primary care and cardiology clinics at an integrated health system, we compared the 2021 monthly rate of prescription of beta blockers (BBs), ACEis/ARBs/ARNIs, mineralocorticoid receptor antagonist (MRAs), and SGLT2 inhibitors (SGLT2is), with and without available clinical exclusions based on vitals, renal function, and medical history. Results: A cohort of 4186 patients with HFrEF (mean age 69, 35% female, 18% Black) had at least one eligible encounter in 2021. The monthly prescription rates of GDMT were high for BBs (79.1-84.8%) and ACEIs/ARBs/ARNIs (69.1-77.0%), but low for MRAs (39.4-52.0%) and SGLT2is (6.9-23.2%). With the addition of clinical exclusions, the performance on each QM was higher for BBs (83.1-88.0%), ACEIs/ARBs/ARNIs (78.1-84.7%) MRAs (48.3-60.2%), and SGLT2is (8.8-28.7%) (Figure). Conclusions: The addition of EHR-based clinical exclusions resulted in higher QM performance and identified a narrower population that may benefit more from quality improvement strategies.
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