Preventable adverse drug events (ADEs) represent a significant public health challenge for the older adult population, since they are associated with higher medical expenditures and more hospitalizations and emergency department (ED) visits. This study examines whether a novel medication risk prediction tool, the MedWise Risk Score™ (MRS), is associated with ADEs and other pertinent outcomes in participants of the Programs of All-Inclusive Care for the Elderly (PACE). Unlike other risk predictors, this tool produces actionable information that pharmacists can easily use to reduce ADE risk. This was a retrospective cross-sectional study that analyzed administrative medical claims data of 1965 PACE participants in 2018. To detect ADEs, we identified all claims that had ADE-related International Classification of Diseases and Health Related Problems, 10th revision (ICD-10) codes. Using logistic and linear regression models, we examined the association between the MRS and a variety of outcomes, including the number of PACE participants with an ADE, total medical expenditures, ED visits, hospitalizations, and hospital length of stay. We found significant associations for every outcome. Specifically, every point increase in the MRS corresponded to an 8.6% increase in the odds of having one or more ADEs per year (OR = 1.086, 95% CI: 1.060, 1.113), $1037 USD in additional annual medical spending (adjusted R² of 0.739; p < 0.001), 3.2 additional ED visits per 100 participants per year (adjusted R² of 0.568; p < 0.001), and 2.1 additional hospitalizations per 100 participants per year (adjusted R² of 0.804; p < 0.001). Therefore, the MRS can risk stratify PACE participants and predict a host of important and relevant outcomes pertaining to medication-related morbidity.

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.

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.

Background: Given associations with serious cognitive and physical adverse effects (e.g., dementia, falls), strong anticholinergics, like urinary antimuscarinics (UAMs), should be avoided in older adults. This feasibility study aimed to (1) evaluate the implementation rate of pharmacists' recommendations intended to de‐escalate UAMs, (2) quantify the change in overall anticholinergic dosing exposure from these recommendations, and (3) investigate factors that predict recommendation implementation. Methods: This was a retrospective, observational, before‐and‐after study. Pharmacists ( n = 18) devised strategies to de‐escalate UAMs in 187 participants (mean age 72.4 ± 9.4; 77.0% female; mean number of medications 12.9 ± 4.6) of 35 Programs of All‐Inclusive Care for the Elderly (PACE). PACE prescribers (non‐physicians and physicians) determined whether to implement recommendations. Implementation was defined as a change in the prescription records consistent with the pharmacist's recommendation at 2‐, 4‐, 6‐, and 9‐months post‐recommendation. Anticholinergic dosing exposure was measured at each time point using standardized daily doses (SDD). Multivariable logistic regression was used to identify factors that predicted recommendation implementation. Results: Across 9 months, recommendations were implemented in 118 out of 187 participants, yielding a 63.1% implementation rate. Of these, 77.1% ( n = 91/118) implemented by month 2. Implementers' mean overall anticholinergic SDD decreased 65.4% from baseline (baseline: 2.6 [95% CI: 2.2, 3.0] to month 9: 0.9 [95% CI: 0.6,1.2], p < 0.001) whereas non‐implementers demonstrated no significant change ( p = 0.52). Taking <10 baseline medications (OR 2.75; 95% CI: 1.09, 7.61); baseline UAM SDD ≥2 (OR 2.20; 95% CI: 1.11, 4.44); uncomplicated recommendations (OR 3.38; 95% CI: 1.67–7.03); and baseline calcium channel blocker use (OR 2.19; 95% CI: 1.09, 4.52) predicted implementation. Conclusion: Our high implementation rate indicates that pharmacists' recommendations to de‐escalate UAMs as a way to reduce overall anticholinergic exposure is feasible in medically complex, community‐dwelling older adults. Future research should investigate whether these recommendations benefit cognitive (e.g., delirium, dementia) and/or physical functioning (e.g., falls).

Little is known about the types of drug information inquiries (DIIs) prescribers caring for older adults ask pharmacists during routine practice. The objective of this research was to analyze the types of DIIs prescribing clinicians of Programs of All-Inclusive Care for the Elderly (PACE) made to clinical pharmacists during routine patient care. This was a retrospective analysis of documented pharmacists’ encounters with PACE prescribers between March through December, 2018. DIIs were classified using a developed taxonomy that describes prescribers’ motivations for consulting with pharmacists and their drug information needs. Prescribers made 414 DIIs during the study period. Medication safety concerns motivated the majority of prescribers’ inquiries (223, 53.9%). Inquiries received frequently involved modifying drug therapy (94, 22.7%), identifying or resolving adverse drug events (75, 18.1%), selecting or adjusting doses (61, 14.7%), selecting new drug therapies (57, 13.8%), and identifying or resolving drug interactions (52, 12.6%). Central nervous system medications (e.g., antidepressants and opioids), were involved in 38.6% (n = 160) of all DIIs. When answering DIIs, pharmacists made 389 recommendations. Start alternative medications (18.0%), start new medications (16.7%), and change doses (12.1%) were the most frequent recommendations rendered. Prescribers implemented at least 79.3% (n = 268) of recommendations based on pharmacy records (n = 338 verifiable recommendations). During clinical practice, PACE prescribers commonly ask pharmacists a variety of DIIs, largely related to medication safety concerns. In response to these DIIs, pharmacists provide medication management recommendations, which are largely implemented by prescribers.