A Knowledge-based Decision Support System for recommending safe recipes to individuals with dysphagia

Area of Science:

• Medical Informatics
• Nutrition Science
• Neurology

Background:

• Dysphagia, often linked to neuromuscular diseases, significantly impacts patient quality of life.
• Patients and caregivers struggle with safe food preparation, leading to malnutrition due to altered dietary consistencies and lack of knowledge.
• Unbalanced nutrient intake poses serious risks, especially for frail individuals.

Purpose of the Study:

• To develop an ontology-based Decision Support System (DSS) for neuromuscular patients with dysphagia.
• To assist patients and caregivers in preparing nutritionally balanced and safe meals for per-oral nutrition.
• To address the critical need for managing dietary challenges in dysphagia.

Main Methods:

• Formalized expert knowledge from ENT specialists, neurologists, and dieticians into a DSS.
• Developed the DSS based on scientific literature review and collaboration with medical experts.
• Created a prototype accessible via digital applications for physicians, patients, and caregivers.

Main Results:

• The DSS suggests recipes considering patient consistency limitations and dysphagia severity, ensuring nutritional balance.
• The prototype allows physicians to verify recommendations and enables patients/caregivers to autonomously prepare meals.
• Clinical evaluation with 9 clinicians assessed recipe quality and system acceptance.

Conclusions:

• Preliminary results indicate positive outcomes for DSS-generated recipes.
• The system demonstrates good usability in clinical practice.
• The DSS shows promise in supporting safe and balanced nutrition for dysphagia patients.