A Personalized Ontology-Based Decision Support System for Complex Chronic Patients: Retrospective Observational Study

Area of Science:

• Health Informatics
• Clinical Decision Support Systems
• Geriatric Pharmacology

Background:

• Rising life expectancy increases chronic diseases and polypharmacy prevalence.
• Clinical practice guidelines (CPGs) implementation faces challenges.
• Ontology-based clinical decision support systems (CDSS) can improve CPG adherence and patient care.

Purpose of the Study:

• To design, develop, and validate an ontology-based CDSS for personalized drug prescription recommendations.
• To target older adult patients with chronic diseases and polypharmacy.
• To reduce drug-related complications and enhance integrated care.

Main Methods:

• Developed an ontology-based CDSS using knowledge sources like CPGs, PROFUND, LESS/CHRON, and STOPP/START criteria.
• Mapped data using HL7 FHIR and SNOMED CT.
• Validated the CDSS through a retrospective case study and analyzed adoption factors.

Main Results:

• Successfully designed, developed, and validated an ontology-based CDSS.
• Retrospective case study using real patient data yielded favorable results.
• Analysis indicated favorable conditions for CDSS adoption by healthcare professionals.

Conclusions:

• An ontology-based CDSS was successfully developed and validated for personalized drug prescription.
• Future work requires real-world environment validation for usability and reliability.
• The developed CDSS shows promise for improving care for older adults with chronic conditions.