Abstract

Introduction: AHA Get with The Guidelines (GWTG) is a proven in-hospital approach to improving patient outcomes. The Heart Failure (HF) quality measures for quadruple therapy includes angiotensin receptor/neprilysin inhibitors, beta blockers, aldosterone receptor antagonists, and sodium-glucose transport inhibitors, device counseling, vaccination status assessment, and follow up. Capturing guideline directed therapy (GDT) retrospectively can be done in several ways including the current process of manual review of electronic records, abstraction, and submission to the HF Registry. A SmartPhrase can contribute to adherence of GDT at discharge more efficiently. Research Question: Our research question was, “Can the use of a SmartPhrase improve adherence to AHA HF guidelines?” Goal: To prompt clinicians to address GDT to meet the quality metrics endorsed by the AHA by providing a template for documentation of these therapies in the discharge summary or progress note. Methods: We compared our adherence to the GWTG-HF quality measures prior to after implementing a standard HF DC Checklist SmartPhrase. We evaluated whether the improvement was associated with the SmartPhrase. A Health Information student undertook a project with her preceptor, a Quality Data Manager to analyze SmartPhrase use by providers. Results: We found significant improvement in most GWTG-HF quality measures, including GDT quadruple therapy post-sharing this SmartPhrase. Downstream potential benefits to improved adherence to these HF GDT metrics are improvement in 30-day readmissions. Positive trends in the GWTG-HF quality metrics included an overall improvement from Q1 2022 baseline data for quadruple GDT therapy of 37.2% to Q1 2023 of 80.4%. Conclusions: The adoption of the SmartPhrase improved adherence to the quality metrics. Use of the SmartPhrase varied by provider. Providers used the dot phrase as it was given to them by the team or by copying and pasting the phrase. The use of copy and paste made tracking the use of the SmartPhrase difficult to track electronically. We are exploring additional methods to improve efficient documentation including natural language (NLP).

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