Investigating the Impact of Nurse Engagement on Quality Improvement Initiatives in Hospital Settings

Posted: Dec 22, 2022

• Corbin Foster
• Wesley Rivera
• Ellie Greene

Abstract

This research examines the complex relationship between nurse engagement and the effectiveness of quality improvement initiatives in hospital environments through a novel computational framework that combines natural language processing, network analysis, and machine learning. Unlike traditional survey-based approaches, our methodology analyzes unstructured electronic health record data, nurse communication patterns, and institutional documentation to quantify engagement in ways previously unexplored. We developed a multi-dimensional engagement index that captures both explicit participation in quality initiatives and implicit behavioral indicators across clinical workflows. Our analysis of data from three major hospital systems revealed that nurse engagement exhibits non-linear relationships with quality outcomes, with critical threshold effects that explain why some initiatives succeed while others fail despite similar implementation strategies. The findings demonstrate that engagement patterns follow power-law distributions rather than normal distributions, suggesting that a small subset of highly engaged nurses disproportionately influences initiative success. Furthermore, we identified specific communication network structures that amplify engagement effects and developed predictive models that can forecast initiative outcomes with 87