Investigating the Relationship Between Nurse Education Level and Quality of Care Delivered to Patients

Posted: Oct 30, 2023

• Noel Fischer
• Blake Cunningham
• Cooper Franklin

Abstract

This research presents a novel computational framework for analyzing the complex relationship between nurse education levels and patient care quality using machine learning and network analysis techniques. Unlike traditional healthcare studies that rely on linear regression models and self-reported data, our approach integrates multi-source electronic health records, institutional staffing data, and real-time patient monitoring systems to create a comprehensive dataset spanning 18 months across three major healthcare institutions. We developed a hybrid analytical methodology combining temporal pattern recognition, causal inference modeling, and quality metric clustering to identify non-linear relationships and threshold effects that conventional statistical methods often miss. Our findings reveal several counterintuitive patterns, including the existence of optimal education mix ratios within nursing teams and context-dependent effectiveness of advanced degrees. The results demonstrate that the relationship between education and care quality is mediated by institutional factors, team composition dynamics, and specific patient population characteristics. This research contributes both methodologically through its innovative analytical framework and substantively through its nuanced understanding of how educational preparation translates to clinical practice across different healthcare contexts.