Drug–Drug Interactions in Elderly Patients with Potentially Inappropriate Medications in Primary Care, Nursing Home and Hospital Settings: A Systematic Review and a Preliminary Study

Abstract

Drug–drug interactions (DDI) occurring with potentially inappropriate medications (PIM) are additional risk factors that may increase the inappropriate character of PIM. The aim of this study was (1) to describe the prevalence and severity of DDI in patients with PIM and (2) to evaluate the DDI specifically regarding PIM. This systematic review is based on a search carried out on PubMed and Web-of-Science from inception to June 30, 2020. We extracted data of original studies that assessed the prevalence of both DDI and PIM in elderly patients in primary care, nursing home and hospital settings. Four hundred and forty unique studies were identified: 91 were included in the qualitative analysis and 66 were included in the quantitative analysis. The prevalence of PIM in primary care, nursing home and hospital were 19.1% (95% confidence intervals (CI): 15.1–23.0%), 29.7% (95% CI: 27.8–31.6%) and 44.6% (95% CI: 28.3–60.9%), respectively. Clinically significant severe risk-rated DDI averaged 28.9% (95% CI: 17.2–40.6), in a hospital setting; and were approximately 7-to-9 lower in primary care and nursing home, respectively. Surprisingly, only four of these studies investigated DDI involving specifically PIM. Hence, given the high prevalence of severe DDI in patients with PIM, further investigations should be carried out on DDI involving specifically PIM which may increase their inappropriate character, and the risk of adverse drug reactions.

Drug–Drug Interactions with Oral Anticoagulants as Potentially Inappropriate Medications: Prevalence and Outcomes in Elderly Patients in Primary Care and Hospital Settings

“…For each DDI or PIM–DDI, the type of interaction (pharmacokinetic or pharmacodynamic), mechanism of action and level of severity (1: contraindicated, 2: not recommended, 3: use with caution and 4: to take into account) were considered. Given the fact that there are variations in the classification of DDI and PIM–DDI among Theriaque and Micromedex, we used a mapping of the DDI risk classification based on the descriptions given by the providers [ 11 ]. As a result, we considered that major DDI/PIM–DDI refers to levels 1 and 2 of Theriaque (“contraindicated” and “not recommended”) and to the “contraindicated” and “major” levels of Micromedex.…”

“…It should be noticed that PIM criteria (including more than 90 drugs on the Beers list) are regularly updated but involve only a very limited number of DDIs. However, DDI occurring specifically with PIM (i.e., PIM–DDI) seems a relevant issue, although we showed it was poorly studied [ 11 ]. Indeed, it could be hypothesized that the inappropriate feature of these PIM drugs (i.e., unfavorable benefit/risk ratio) could be increased by a drug–drug interaction since for most the drugs ADRs are related to the systemic concentrations.…”

“…For example, an interaction by a metabolic or a transporter inhibition could increase the systemic exposure of the PIM and thus may increase the frequency and/or severity of ADEs. In a descriptive study of pharmacokinetic DDI involving PIM we showed a prevalence ranging from 0.10% (Tramadol–Terbinafine) to 19.04% (Apixaban–Amiodarone) [ 11 ]. These elements highlight the fact that DDI involving PIM (PIM–DDI) should be considered and the potential clinical outcomes of these PIM–DDI should be questioned.…”

Prioritising Risk Factors for Prescription Drug Overdose among Older Adults in South Korea: A Multi-Method Study

“…Drug clearance decreases with the occurrence of ageing-related renal and hepatic function impairment [ 9 ]. Moreover, older people are more likely to be exposed to multiple drugs owing to comorbidities, and the risk of drug–drug interaction also increases as a result of age-related changes in drug pharmacokinetics and pharmacodynamics [ 10 ]. Older adults are therefore at a high risk for mortality from overdose.…”

The Challenges of Implementing Comprehensive Clinical Data Warehouses in Hospitals

“…Aggregating all this data will thus make it possible to model diseases during their various stages of development and help understand them. Simulation and modeling tools will make it possible to validate predictive algorithms for the evolution of a disease, optimize treatments, improve their effectiveness, or reduce their toxicity [ 6 , 7 ]. To learn, function and improve, AI, algorithms and models need to be fed with massive quantities of data that are as structured as possible and of high quality.…”