Application and Effectiveness of Big Data and Artificial Intelligence in the Construction of Nursing Sensitivity Quality Indicators.

Journal: Journal of healthcare engineering
Published Date:

Abstract

In order to explore the quality management efficiency of applying big data and artificial intelligence in nursing quality index, a method of building a nursing management platform integrating nursing indicators and nursing events is proposed. Based on the investigation of the application demand of nursing information system, the method achieves timely data sharing and transmission through WLAN technology and realizes nursing management monitoring, nursing quality index enquiry, and automatic statistical analysis under the vertical management mode of nursing. The results showed that 77 people (73%) thought the time decreased, 19 people (18%) thought the time was the same, and 9 people (7%) thought the time increased. In terms of intelligent application and big data of nursing information management system, there is a significant difference in nursing management efficiency before and after using nursing management information system ( < 0.001). The nursing management control platform is designed and applied, and the nursing quality control method and actual management process are improved, which is very good for strengthening nursing quality management. The overall optimization of the quality control process is realized, which helps to mobilize the initiative and enthusiasm of nursing staff and continuously improve the effectiveness of nursing management and nursing efficiency.

Authors

  • Aie Chen
    Blood Purification Department, Lishui People's Hospital of Zhejiang Province, Lishhui Zhejiang, 323000, China.
  • Xiaozhen Jiang
    Blood Purification Department, Lishui People's Hospital of Zhejiang Province, Lishhui Zhejiang, 323000, China.
  • Fen Lian
    Blood Purification Department, Lishui People's Hospital of Zhejiang Province, Lishhui Zhejiang, 323000, China.
  • Jing Wu
    School of Pharmaceutical Science, Jiangnan University, Wuxi, 214122, Jiangsu, China.
  • Xiaohua Weng
    Blood Purification Department, Lishui People's Hospital of Zhejiang Province, Lishhui Zhejiang, 323000, China.
  • Wen Li