Clinical decision support systems for polypharmacy optimization in older patients: a narrative review

Area of Science:

• Gerontology
• Clinical Pharmacy
• Health Informatics

Background:

• Multimorbidity and polypharmacy are rising in older adults, increasing risks of inappropriate medications, drug interactions, and adverse reactions.
• Medication review and deprescribing are effective but challenging due to complexity and clinical variability.
• Clinical Decision Support Systems (CDSS) offer digital solutions for polypharmacy management by analyzing data and providing personalized recommendations.

Purpose of the Study:

• To identify and compare Clinical Decision Support Systems (CDSS) for managing polypharmacy, medication review, and deprescribing in older adults and patients with multimorbidity.
• To assess operational characteristics, workflow integration, decision-support functions, outputs, and validation evidence of various CDSS.

Main Methods:

• A narrative review was conducted to identify and compare CDSS.
• Systems were classified as manual, hybrid, or automated based on data acquisition.
• Operational features and validation evidence were assessed across different healthcare settings.

Main Results:

• Manual CDSS have high operational burden; hybrid systems balance automation and oversight; automated systems offer real-time support integrated with EHR.
• Significant heterogeneity exists in CDSS automation, implementation, and validation stages, from feasibility studies to RCTs.
• Evidence for CDSS effectiveness ranges from development studies to observational analyses and randomized controlled trials.

Conclusions:

• CDSS show promise for safer polypharmacy management in complex patients.
• Enhanced integration into workflows and use of multidimensional data can improve CDSS impact.
• Further comparative studies and real-world evaluations are needed to assess CDSS impact on prescribing, patient outcomes, and sustainability.