A sequential mixed-methods study to develop and validate the nursing infection control effectiveness index (NICEI)

BACKGROUND: Healthcare-associated infections (HAIs) significantly threaten patient safety and increase healthcare costs. Nursing practices critically influence HAI incidence, but existing indicators are fragmented, lacking a unified measure for evaluating nursing effectiveness in infection control. METHODS: A sequential mixed-methods study was conducted to develop and validate the Nursing Infection Control Effectiveness Index (NICEI). This index integrated 16 nursing-led HAI indicators using entropy-weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). A two-round Delphi survey, facilitated by a custom R Shiny platform, was conducted with nursing experts to derive Analytic Hierarchy Process (AHP) weights, incorporating real-time consistency checks and iterative feedback to enhance consensus. Validation included discrimination tests, correlation and regression analyses with HAI incidence. Sensitivity was assessed by comparing entropy weights to AHP weights. An R Shiny tool was developed to support flexible implementation. RESULTS: NICEI demonstrated a moderate negative correlation with HAI incidence (ρ = −0.328, p < 0.001) and effectively differentiated performance across infection risk tiers. Entropy-weighted NICEI was sensitive to data variations, whereas AHP-weighted NICEI showed high stability under perturbation. The developed tool enabled flexible index calculation and visualization. CONCLUSION: NICEI provides a valid, standardized composite measure for assessing nursing infection control performance, supporting both cross-sectional and longitudinal evaluations. It facilitates targeted quality improvement and resource allocation in clinical settings. CLINICAL TRIAL NUMBER: Not applicable.