Abstract
Polypharmacy is a common phenomenon among adults using opioids, which may influence the frequency, severity, and complexity of drug–drug interactions (DDIs) experienced. Clinicians must be able to easily identify and resolve DDIs since opioid-related DDIs are common and can be life-threatening. Given that clinicians often rely on technological aids—such as clinical decision support systems (CDSS) and drug interaction software—to identify and resolve DDIs in patients with complex drug regimens, this narrative review provides an appraisal of the performance of existing technologies. Opioid-specific CDSS have several system- and content-related limitations that need to be overcome. Specifically, we found that these CDSS often analyze DDIs in a pairwise manner, do not account for relevant pharmacogenomic results, and do not integrate well with electronic health records. In the context of polypharmacy, existing systems may encourage inadvertent serious alert dismissal due to the generation of multiple incoherent alerts. Future technological systems should minimize alert fatigue, limit manual input, allow for simultaneous multidrug interaction assessments, incorporate pharmacogenomic data, conduct iterative risk simulations, and integrate seamlessly with normal workflow.
Highlights
The progressively worsening population health problem of opioid use disorders and the rising death rates from opioid overdoses have caused policy makers and researchers to work on strategies for optimizing opioid medication management while concurrently curtailing opioid prescriptions [1].Clinicians are faced with the challenge of treating pain adequately to improve patients’ quality of life while trying to avert the potential of overuse, misuse, and abuse among patients who are prescribed opioids [1]
In light of such troubling information, this narrative review aims to explore our current understanding of opioid-related polypharmacy and subsequent drug–drug interaction (DDI) with an evidence-based appraisal of the performance of clinical decision support systems (CDSS) used in practice to resolve opioid-related
Concomitant diagnoses may often be psychiatric-related, such as major depressive disorder or bipolar disorder [4]. This can lead to central nervous system (CNS) polypharmacy, which has been defined as the use of three or more medications with psychoactive properties [2,21]
Summary
The progressively worsening population health problem of opioid use disorders and the rising death rates from opioid overdoses have caused policy makers and researchers to work on strategies for optimizing opioid medication management while concurrently curtailing opioid prescriptions [1]. Existing systems are far from fail-safe as an abundance of evidence indicates that clinicians may still miss clinically important DDIs, in patients with polypharmacy [12,13,16,17,18,19]. In light of such troubling information, this narrative review aims to explore our current understanding of opioid-related polypharmacy and subsequent DDIs with an evidence-based appraisal of the performance of CDSS used in practice to resolve opioid-related.
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