Construction and empirical study of a real time monitoring system for nursing sensitive quality indicators that based on multi-source data fusion
XU Xiaofei
ZHU Lingling
JIN Cunduo
YAN Jingjing
XU Ying
LIU Xiaohong
SHI Jinfen
Abstract：Objective To develop a real-time monitoring system for nursing sensitive quality indicators based on multi-source data fu-sion,to solve the problems of low efficiency,data lag in manual or semi manual statistics,and promote the continuous improvement of nursing quality.Methods Integrating multi-source data from systems such as the Hospital Information System(HIS),Nursing Management System,Nursing Documentation System,and Real-Time Nosocomial Infection Surveillance System,a real-time monitoring system for Nursing-Sensi-tive Quality Indicators(NSQIs)was constructed through modeled processing and analysis.The system encompassed structural,process,and outcome indicators.It supported a unified dashboard for the real-time monitoring of indicator data,enabled intelligent multidimensional analy-sis across customizable time frames,and validated its effectiveness through clinical application.Results A real-time monitoring system cov-ering 19 nursing-sensitive quality indicators was established.The accuracy rate of indicator data collection increased from 64.00%to 100%.The manual data collection time for nurses,head nurse,and nursing department were reduced from(9.45±3.78)min/day,(121.80±104.40)min/month,and(142.50±7.50)min/month,respectively,to zero.The data update frequency was shortened from"monthly" to"minute-lev-el".The overall satisfaction rate among nursing staff with the system reached 96.13%.Conclusion The real-time monitoring system for NSQIs can enable automated,continuous data surveillance,delivering objective,accurate,secure,and reliable results.It provides robust data support for the continuous improvement of nursing quality and offered a replicable technical pathway for the digital transformation of nursing quality management.
Keywords：nursing informatizationnursingsensitive quality indicatorreal-time monitoring systemnursing quality
Publication Date：2025-09-10
Online Publishing Date：2025-11-21(First online date of this platform, not the publication date of the document)
Pages：7( 795-801 )