Building a learning health analytical tool to improve quality and patient safety by empowering nursing practice and establishing a data driven culture.

611 Background: Healthcare is highly regulated to ensure that the highest standards of care are consistently followed in the pursuit of optimal patient outcomes. Regulatory bodies such as The Joint Commission and ANCC Magnet have standards for oncology care, which often include mandatory reporting of certain quality metrics. Regulatory outcome reporting can be time-consuming and might not reflect the complete story of how well a clinical workflow is functioning. Like most health facilities, our pre-measurement strategies included manual chart reviews with a small sample size. This did not provide us with actionable information leading to improvement. Methods: At our comprehensive cancer center, we decided to measure every component of the oncology infusion nursing workflows that lead to the outcome regulatory metrics. We developed a learning health system with a focus on providing timely analytics to improve care through quality improvement methodologies. We extracted all the data components within the electronic health record and developed an analytical dashboard that captures key areas of clinical process measures that contribute to an externally reported outcome measure. The outcome metrics included documentation of compliance rates for initial nursing assessments, pain management, and blood transfusion. Results: This approach has led to multiple positive results; there has been a reduction in cycle time for quality improvement projects by having the tool available and refreshed in a timely manner, establishing and sustaining a data driven culture with continuous improvement efforts and significant improvement in clinical outcomes and compliance metrics (see table). Conclusions: Within healthcare we have never had the opportunity to have computing power and clinical data availability as we have today. Rather than relying on retrospective chart reviews to look at things only from the outcome perspective, we now can develop a tool that encompasses our entire patient population and assesses our outcome metric by identifying specific process workflow elements that are contributing to it. This can be replicated by other institutions and is where healthcare analytics are headed. Our proof of concept has been successful, and we have started to use the same method to develop tools for areas such as inpatient restraints and ambulatory falls. Infusion compliance metrics results. Hospital wide compliance Q1 Calendar Year 2023 Q1 Calendar Year 2025 Initial Nursing Assessment 46% 63% Initial Pain Assessment 74% 81% Blood Transfusion encounter level compliance (with all compliance components completed) 34% 50% Blood Transfusion specific component: Vital Signs 30 mins prior start 78% 89% Blood Transfusion specific component: Vital Signs within 15 mins start 74% 90% Blood Transfusion specific component: Vital Signs 30 mins post transfusion 81% 90%