Development and Evaluation of a Prototype CDSS for Fall Prevention.

Area of Science:

• Gerontology and Nursing Informatics
• Clinical Decision Support Systems

Background:

• Falls are a significant risk for patient safety, particularly in healthcare settings.
• Effective fall prevention strategies require accurate risk assessment and tailored interventions.
• Current nursing workflows may benefit from enhanced tools for fall risk management.

Purpose of the Study:

• To develop and validate a prototype clinical decision support system (CDSS) for fall prevention.
• To integrate patient-specific data, fall-risk prediction models, and clinical practice guidelines (CPGs) into a cohesive system.
• To support nurses in planning and documenting fall prevention care activities.

Main Methods:

• Development of a prototype CDSS incorporating a fall-risk prediction model and evidence-based CPGs.
• Verification of the knowledge base and inference engine accuracy using ten clinical scenarios.
• Evaluation of user interface heuristics by four expert reviewers.

Main Results:

• The prototype CDSS successfully integrates patient data, risk prediction, and CPGs for tailored recommendations.
• Initial validation confirmed the accuracy of the system's rules and inference engine.
• User interface heuristics were evaluated by experts, providing feedback for refinement.

Conclusions:

• The developed CDSS prototype demonstrates potential for enhancing fall prevention strategies in nursing practice.
• The system's ability to provide tailored recommendations and aid documentation warrants further investigation.
• Ongoing evaluation will assess the impact on nurses' workflow and patient outcomes, validating its clinical utility.