EHR Nudges to Improve Quality of Care in HF

Heart failure (HF) is a common, morbid, and costly condition with an enormous toll on health and the health care system in the US. Unlike other HF types, for patients with HFrEF decades of high quality, randomized controlled trials have demonstrated numerous interventions-including medications, devices, and cardiac rehabilitation-that improve quality of life, lengthen survival, and reduce hospitalizations. Despite the substantial evidence, many patients with HFrEF do not receive optimal guideline-directed medical therapy (GDMT) as shown by several US quality registries dating back to 2009. Contributors to gaps in care quality have been shown to include patient-level (i.e., illness severity, race/ethnicity, socio-economic status), clinician-level (i.e., lack of knowledge, clinical inertia), and health system-level (i.e., lack of care coordination) factors. Pharmacist-led clinics in several health systems and studies have been shown to lead to high rates of GDMT intensification. This finding is consistent with decades of research in HF and other conditions in which more resources allocated to disease management can improve quality of care. Yet, little data exist on adherence to optimal GDMT after completion of an intensive disease management program. Northwestern Medicine is a large, integrated system that operates multiple pharmacist-led clinics to optimize GDMT in patients with HFrEF. Once patients reach the maximum level of intensification, they complete the program and are no longer actively followed by the pharmacist team. The adoption of electronic health records (EHRs) and integration of novel data sources, such as prescription fill data from third-party vendors, create the opportunity to implement strategies to monitor adherence over time and intervene when adherence declines. Clinical decision support nudges in the EHR are inexpensive strategies that have been shown in clinical areas outside of HF to increase adherence to evidence-based therapies. Studies that use pharmacy fill data to monitor adherence to evidence-based care are rare given some of the technical challenges of accessing these data and using them for clinical decision support tools. In this pilot feasibility study, we aim to develop and test a pharmacist-facing clinical decision support tool designed to increase adherence to GDMT and evaluate the tool using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) evaluation framework.