Development and application of a nursing diagnosis-based decision support system for clinical nursing plans
10.3761/j.issn.0524-1769.2025.20.004
- VernacularTitle:基于护理诊断的临床护理计划决策支持系统的研发与应用
- Author:
Zuyang XI
1
;
Yongting WEI
;
Chaxiang LI
;
Jinglan LIU
;
Kexiong CUI
;
Lianghuan YU
;
Hongjing ZHAN
;
Jingjing LI
;
Qing TANG
Author Information
1. 443000 湖北者宜昌市 三峡大学第一临床医学院/宜昌市中心人民医院护理部
- Publication Type:Journal Article
- Keywords:
Nursing Diagnosis;
Nursing Plan;
Decision Support;
Information System;
Nursing Administra-tion Research
- From:
Chinese Journal of Nursing
2025;60(20):2458-2464
- CountryChina
- Language:Chinese
-
Abstract:
Objective To develop a decision support system for clinical nursing plans based on nursing diagno-sis and explore its application effects,in order to provide references for optimizing the clinical nursing process and improving the quality of nursing.Methods A multidisciplinary research team was established to construct a clini-cal nursing plan decision support system framework from 3 aspects,namely nursing diagnosis,nursing interventions,and outcome tracking.The system built a clinical nursing diagnosis decision knowledge base through 3 dimensions,namely basic nursing diagnoses,specialty disease nursing diagnoses,and nursing-related technical diagnoses.Deep learning-based artificial intelligence capture technology was developed to achieve intelligent matching and generate clinical nursing plan forms.Implemented in a tertiary hospital in Yichang City,Hubei Province,a control group(June to August 2024)and an experimental group(October to December 2024)were compared regarding nursing diagnosis implementation rate,nursing plan documentation accuracy,and clinical nursing quality scores.Results This research showed a significant improvements for nursing diagnosis implementation rate increased from 94.88％to 97.25％,and nursing plan documentation accuracy improved from 90.38％to 95.33％.Compared with the control group,the experimental group demonstrated statistically significant enhancements in deep vein thrombosis preven-tion,fall prevention,pressure injury management,unplanned extubation control,bloodstream infection control,catheter-related infection prevention,and key specialty nursing quality indicators(all P＜0.05).Conclusion The nursing di-agnosis-based clinical decision support system effectively improves nurses'diagnostic implementation rates,enhances documentation accuracy of nursing plans,and elevates overall clinical nursing quality.
