Nurse-to-Patient Ratios and 30-Day Readmission in Heart Failure: A National Big Data Analysis Using the NRD Database

Abstract

Purpose: This study investigates the association between nursing workforce dynamics and 30-day readmission risks among heart failure patients, examining the hypothesis that excessive workloads correlate with compromised clinical surveillance and discharge efficacy. Methods: Utilizing a retrospective cohort design, we executed a large-scale data linkage between the National Readmission Database (NRD, 2021) and CMS Provider Data, encompassing a representative sample of 685,210 heart failure hospitalizations. Multivariate logistic regression and XGBoost algorithms were employed to analyze the association between the Nurse-to-Patient Ratio (NPR) and readmission, adjusting for the Charlson Comorbidity Index, socioeconomic status, and institutional characteristics. Results: Findings demonstrate a significant correlation; patients in hospitals with the lowest staffing levels (ratio > 1:6) exhibited a readmission rate of 29.2%, compared to 15.1% in optimally staffed facilities (ratio ≤ 1:4). Every additional patient per nurse was associated with a 7% increase in readmission odds (OR = 1.07; 95% CI: 1.05–1.09; p < .001), while the XGBoost model achieved high discriminative performance (AUC = 0.82). Conclusion: The study concludes that nurse staffing represents a significant organizational factor associated with patient safety and readmission outcomes, suggesting that inadequate nursing capacity may hinder effective discharge education and institutional financial viability. Implications: These findings suggest that health policymakers consider transitioning toward acuity-based staffing models and integrating nursing metrics into value-based reimbursement frameworks to mitigate the national burden of heart failure readmissions.