Enhancing patient stratification methods for medication review during acute admissions

Area of Science:

• Clinical Pharmacy
• Geriatric Medicine
• Internal Medicine

Background:

• Hospital medication reviews identify inappropriate prescribing but resource limits necessitate targeted patient selection.
• Current patient stratification relies on medication count and age, potentially missing high-risk individuals.
• Predicting adverse clinical outcomes like readmission or mortality is key for efficient medication review targeting.

Purpose of the Study:

• To explore if clinical factors beyond medication count and age can improve prediction of adverse clinical outcomes in acutely hospitalized medical patients.
• To identify novel biomarkers or indices for better patient stratification for medication review.

Main Methods:

• An exploratory study analyzed data from 27,873 acutely admitted medical patients (≥18 years) at Copenhagen University Hospital Hvidovre.
• Outcomes assessed were acute readmission or mortality within 90 days post-discharge.
• Predictive models compared traditional factors (medication count, age) with medication risk score (MERIS), renal function, anticholinergic burden, a frailty index (FI-OutRef), and plasma soluble urokinase plasminogen activator receptor (suPAR).

Main Results:

• Neither MERIS, renal function, nor anticholinergic burden improved outcome prediction compared to medication count and age.
• Incorporating a frailty index (FI-OutRef) or suPAR significantly enhanced the prediction of 90-day adverse clinical outcomes.
• These findings suggest FI-OutRef and suPAR are valuable for identifying patients who would benefit most from medication review.

Conclusions:

• Frailty index (FI-OutRef) and suPAR are superior predictors of adverse clinical outcomes in hospitalized medical patients compared to traditional factors.
• These biomarkers offer practical proxies of disease burden for improved patient stratification for medication review.
• Optimizing medication review targeting can enhance patient safety and resource allocation in hospitals.