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Updated: Jan 20, 2026

Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis
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Association of an Algorithm-Generated Medication Optimization Score With Clinical Outcomes in Ambulatory Patients

Mohamed S Ali1, Kaitlyn M Greer1, Sabah Ganai1

  • 1College of Pharmac, University of Michigan, Ann Arbor, Michigan, USA.

Pharmacotherapy
|January 18, 2026
PubMed
Summary

A new algorithm for medication optimization in heart failure with reduced ejection fraction (HFrEF) significantly lowers mortality or hospitalization risks. This tool effectively identifies guideline-directed medical therapy (GDMT) optimization opportunities in real-world heart failure care.

Keywords:
advanced heart failure careguideline‐directed medical therapyheart failure with reduced ejection fractionmedication optimization score

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Area of Science:

  • Cardiology
  • Medical Informatics
  • Pharmacology

Background:

  • Guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) implementation is often suboptimal.
  • A computable algorithm was developed to generate a medication optimization score (MOS) and provide guideline-based recommendations.
  • An updated algorithm version incorporating sodium-glucose co-transporter 2 inhibitors was developed in 2021.

Purpose of the Study:

  • To evaluate the association between algorithm-generated medication optimization information and clinical outcomes in real-world HFrEF patients.
  • To assess the effectiveness of the updated algorithm in identifying opportunities for GDMT optimization.

Main Methods:

  • Retrospective cohort study of 1352 ambulatory adult patients with chronic HFrEF.
  • Algorithm-generated MOS calculated using electronic health record data.
  • Primary outcome: composite of all-cause mortality or hospitalization. Analyzed using Cox proportional hazards models, time-varying Cox models, and marginal structural models (MSM).

Main Results:

  • Higher baseline MOS was associated with a lower hazard of the composite outcome (HR 0.96, p=0.040).
  • Time-varying MOS showed a stronger association with reduced risk (HRs of 0.88, p<0.001).
  • Event rates decreased with increasing MOS categories, and MOS improved longitudinally over time.

Conclusions:

  • Higher algorithm-generated MOS values are significantly associated with lower all-cause mortality or hospitalization in HFrEF.
  • The MOS values increased over the follow-up period, indicating improved medication optimization.
  • The algorithm effectively identifies opportunities for GDMT optimization in real-world clinical settings.