CI for a DSS to predict nursing coverage in a geriatric care facility

Area of Science:

• Informatics
• Computational Intelligence
• Nursing Informatics

Background:

• Informatics significantly impacts societal growth, work, and life, with applications in environment, safety, and healthcare.
• Current informatics use in these areas is suboptimal for societal benefit.
• Computational intelligence (CI) or soft computing can increase confidence in informatics applications.

Purpose of the Study:

• To propose the use of CI techniques for improving informatics applications.
• To determine crisp data for enhanced decision-making in nursing care.

Main Methods:

• Utilizing computational intelligence (CI) techniques.
• Employing neural networks and genetic algorithms for data analysis.
• Reasoning on data sources to identify nursing informatics patterns.

Main Results:

• Emerging nursing informatics patterns with increased prediction accuracy.
• Potential for more accurate acuity systems.
• Improved therapeutic care and decreased mortality rates.

Conclusions:

• CI techniques can enhance the reliability and effectiveness of informatics in nursing.
• Data-driven decision-making in nursing care can be significantly improved.
• This approach promises better patient outcomes and reduced mortality.