Design and implementation of an automatic nursing assessment system based on CDSS technology

Area of Science:

• Nursing Informatics
• Clinical Decision Support Systems
• Healthcare Technology Assessment

Background:

• Manual nursing assessments for patient status are burdensome and prone to digitalization errors.
• Existing tools for evaluating patient physiological, psychological, and socioeconomic status require improvement.
• There is a need for automated systems to enhance healthcare efficiency and reduce clinical risks.

Purpose of the Study:

• To propose and evaluate an automatic nursing assessment system using a clinical decision support system (CDSS).
• To reduce the workload on nurses and minimize errors associated with manual data collection.
• To improve the efficiency of healthcare delivery through automated patient status evaluation.

Main Methods:

• Developed a CDSS framework incorporating expert voting for electronic assessment sheet selection.
• Constructed the CDSS based on a nursing process workflow model with a multilayer architecture.
• Evaluated system performance by comparing adverse event incidence and daily assessment times pre- and post-implementation.

Main Results:

• Adverse nursing events incidence decreased significantly from 0.43% to 0.27% over two years (p=0.04).
• Median time for regular daily assessments decreased from 63 seconds to 51 seconds.
• The implemented system demonstrated a clear reduction in both adverse events and assessment duration.

Conclusions:

• The automatic nursing assessment system effectively reduces nurses' workload.
• The system leads to a significant decrease in the incidence of adverse nursing events.
• Automated assessment systems offer a viable solution for improving nursing practice and patient safety.