Purpose: The purpose of this study was to implement a clinical pharmacist-led medication therapy management (MTM) service within a primary-care setting that is enhanced by 1) a clinical decision support system (CDSS) that includes a unique combination of medication risk mitigation factors, which aids the pharmacist in interpreting the medication profile, and 2) pharmacogenomics (PGx) testing. Methods: This was a service implementation study, whereby Medicare beneficiaries were eligible if they were patients of Elmwood Family Physicians, a private family, primary care practice with 2 locations in New Jersey, and were on at least 7 medications. Patients had a medication reconciliation completed by a pharmacist and performed a PGx buccal swab. Patient information was run through a CDSS to aid the pharmacist with screening for multidrug interactions and assessing patient’s medication-related risks. The output of the CDSS was used to create recommendations and provide a consult to the physicians. Recommendations were followed up by return of the consult. Results: Enrolled patients used a mean (± standard deviation) of 12.1 (± 4.6) medications. The turnaround time for the MTM Plus consults was 11.7 (± 6.2) days. During the consults, the pharmacist identified 138 medication-related problems (MRPs). The most common MRPs were drug-drug interactions (29.0%) and drug-gene interactions (DGIs; 24.6%). Conclusion: Implementing a clinical pharmacist-led MTM Plus service in the primary care setting is feasible. This study highlights that DGIs are common in older adults in family practice and indicates that PGx testing identifies additional MRPs that may otherwise go unnoticed in these patients. The experiences we shared can aid other clinicians in establishing successful MTM Plus services. Future studies should also measure the impact of such personalized medicine services on economic, clinical, and humanistic outcomes. This study has been registered with ClinicalTrials.gov (study No. NCT02748148).

Aim: Estimate cost avoidance of pharmacist recommendations for participants enrolled in the Program of All-inclusive Care for the Elderly. Materials & methods: Convenience sample of 200 pharmacogen...

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.

Aim: Evaluate results of pharmacogenomics testing for participants enrolled in the Program of All-inclusive Care for the Elderly (PACE). Materials & methods: A convenience sample of 100 participants from the PHARM-GENOME-PACE study. Genetic variants were determined by pharmacogenomics testing. Drug-gene interactions (DGIs), drug-drug-gene interactions (DDGIs) and phenoconversions were interrogated from a clinical decision support system. Results: In total, 146 genetic variants, 169 DGIs and 125 DDGIs were detected. DGIs and DDGIs occurred most commonly with the CYP2D6 gene (36.1 and 39.2%, respectively). There were 280 instances of phenoconversions; majority (62.9%) affecting the CYP3A4 isoenzyme. Conclusion: Prevalence of exposures to DGIs and DDGIs among PACE participants is high. Pharmacists using a clinical decision support system can support PACE practitioners with assessing multidrug simultaneous interactions. Clinical trial registration: NCT03257605.

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Treatment of behavioral and psychological symptoms of dementia (BPSD) and comorbidities often necessitates the concomitant use of antipsychotics and non-antipsychotic drugs, thereby potentiating the risk for drug–drug interactions (DDIs). The primary objective of our study was to identify potentially clinically relevant cytochrome P450 (CYP)-mediated DDIs involving antipsychotics among participants enrolled in the Program of All-Inclusive Care for the Elderly (PACE) with BPSD. Additionally, we wanted to determine the prevalence of antipsychotic use in this population. The study included 10,001 PACE participants. The practice setting used a proprietary clinical decision support system (CDSS) to analyze simultaneous multidrug interactions. A retrospective analysis of pharmacy claims data was conducted to identify DDIs involving antipsychotics prescribed for BPSD, using snapshots of medication profiles paired with the CDSS. Of the participants who met inclusion criteria, 1190 (11.9%) were prescribed an antipsychotic; of those, 1071 (90.0%) were prescribed an atypical antipsychotic. Aripiprazole commonly caused (being a perpetrator drug 94.6% of the time) potential DDIs with antidepressants (e.g., duloxetine, venlafaxine, mirtazapine), opioids (e.g., hydrocodone, oxycodone, tramadol) and metoprolol via the CYP2D6 isoform. Risperidone commonly caused (85.7%) potential DDIs with donepezil, lamotrigine and trazodone via the CYP3A4 isoform. Quetiapine exclusively suffered (100%) from potential DDIs with amlodipine, buspirone, omeprazole or topiramate via the CYP3A4 isoform. Antipsychotics are commonly prescribed to PACE participants for BPSD treatment and they may interact with other drugs used to treat comorbidities. A thorough review of concomitant medications will help mitigate the likelihood of potentially dangerous CYP-mediated DDIs involving antipsychotics.