How to Use the FORTA ("Fit fOR The Aged") List to Improve Pharmacotherapy in the Elderly.

Abstract

BACKGROUND:

Multimorbidity and polypharmacy are threats to elderly patients; improvement of medication is important and a novel listing approach (the FORTA list) should support this in clinical practice. Here we aim to describe procedural details of successful application of FORTA. FORTA labels range from A (indispensable), B (beneficial), C (questionable) to D (avoid), depending on evidence for safety, efficacy and overall age-appropriateness. As implicit tool it is only applicable if medical details of the patient are known; the drug selection process and secondary assessments are compiled into a manual for successful, embedded use of FORTA.

DISCUSSION:

A flow chart is developed for the complex process of medication in the elderly starting from history taking and diagnostic assessment including disease grading. This is the base for FORTA-assisted selection of drugs to avoid overtreatment (drug not necessary), undertreatment (condition not or not sufficiently treated by positively labeled drugs) or mistreatment (drugs indicated, but negatively rather than positively labeled drug chosen). Selection is followed by secondary analyses, e. g. regarding contraindications (e. g. allergies), former drug responses, interactions, route of application, duration and dosing (e. g. renal adaptation). This may lead to iterative process optimization. The medication scheme is updated in reflection of clinical effects (e. g. blood pressure) and side effects (e. g. dizziness).

CONCLUSION:

The FORTA approach as an implicit tool should be embedded into the diagnostic and therapeutic workup of elderly patients and can give pivotal hints for the choice of medications; however it should not be seen as an isolated instrument.

• Authors: M Wehling
• Journal: Drug research (Drug Res (Stuttg)) Vol. 66 Issue 2 Pg. 57-62 (Feb 2016) ISSN: 2194-9387 [Electronic] Germany
• PMID: 26198035 (Publication Type: Journal Article)
• Copyright: © Georg Thieme Verlag KG Stuttgart · New York.

Topics

• Aged
• Algorithms
• Decision Support Techniques
• Drug Therapy (methods, standards)
• Humans