Adverse drug reactions in older adults – what is preventing prediction?

Dr. Emma Jennings @elmjennings is a dual higher specialist trainee in Geriatric and General Internal Medicine with The Royal College of Physicians Ireland (RCPI). She is currently undertaking a research PhD in Medicine, at University College Cork, Ireland. Her area of interest is adverse drug reaction [ADR] risk prediction and prevention in high risk hospitalised multi-morbid older patients. Her commentary paper Detection and Prevention of Adverse Drug Reactions in Multi-Morbid Older Patients has recently been published in Age and Ageing Journal.

As people age they are more likely to experience chronic medical conditions and be prescribed regular medication. Taking five or more regular medications is referred to as polypharmacy. A diagnosis of three or more chronic conditions at the same time is recognised as multi-morbidity.
 
An ADR is a form of unintentional harm that can occur when taking any medication. Polypharmacy and multi-morbidity increase ADR potential. At least 1 in 10 older adults experience an ADR associated with acute hospitalisation. ADRs are for the most part preventable, yet still commonly occur in multi-morbid older adults with polypharmacy.
 
An ADR can lead to increased morbidity, mortality, and increased healthcare costs. Therefore, efforts to reduce avoidable ADRs occurring would benefit older patients and healthcare services. Despite over 60 years of ADR research there has been little improvement in prediction models. A large amount of variability exists in the patient populations that experience ADRs and in the methods used to study them.
 
Dr. Jennings’ commentary piece compares risk prediction models by population, predictive patient variables and overall predictive value. She concludes that ADRs are a growing public health problem, which require a new approach for prediction and prevention. The predictive value of published ADR prediction tools to date is poor-to-fair at best. Reliable and user friendly methods remain elusive and future concentration on high-risk drug classes may improve prediction and prevention.

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