Association between trajectories of adherence to endocrine therapy and risk of treated breast cancer recurrence among US nonmetastatic breast cancer survivors.

BACKGROUND: Endocrine therapy is the mainstay treatment for breast cancer (BC) to reduce BC recurrence risk. During the first year of endocrine therapy use, nearly 30% of BC survivors are nonadherent, which may increase BC recurrence risk. This study is to examine the association between endocrine therapy adherence trajectories and BC recurrence risk in nonmetastatic BC survivors. METHODS: This retrospective cohort study included Medicare beneficiaries in the United States (US) with incident nonmetastatic BC followed by endocrine therapy initiation in 2010-2019 US Surveillance, Epidemiology, and End Results linked Medicare data. We calculated monthly fill-based proportion of days covered in the first year of endocrine therapy. We applied group-based trajectory models to identify distinct endocrine therapy adherence patterns. After the end of the first-year endocrine therapy trajectory measurement period, we estimated the risk of time to first treated BC recurrence within 4 years using Cox proportional hazards models. RESULTS: We identified 5 trajectories of adherence to endocrine therapy in BC Stages 0-I subgroup (n = 28,042) and in Stages II-III subgroup (n = 7781). A trajectory of discontinuation before 6 months accounted for 7.0% in Stages 0-I and 5.8% in Stages II-III subgroups, and this trajectory was associated with an increased treated BC recurrence risk compared to nearly perfect adherence (Stages 0-I: adjusted hazard [aHR] = 1.84, 95% CI = 1.46-2.33; Stages II-III: aHR = 1.38, 95% CI = 1.07-1.77). CONCLUSIONS: Nearly 7% of BC survivors who discontinued before completing 6 months of treatment was associated with an increased treated BC recurrence risk compared to those with nearly perfect adherence among Medicare nonmetastatic BC survivors.

Association between trajectories of prescription opioid use and risk of opioid use disorder and overdose among US nonmetastatic breast cancer survivors.

PURPOSE: To examine the association between prescription opioid use trajectories and risk of opioid use disorder (OUD) or overdose among nonmetastatic breast cancer survivors by treatment type. METHODS: This retrospective cohort study included female nonmetastatic breast cancer survivors with at least 1 opioid prescription fill in 2010-2019 Surveillance, Epidemiology and End Results linked Medicare data. Opioid mean daily morphine milligram equivalents (MME) calculated within 1.5 years after initiating active breast cancer therapy. Group-based trajectory models identified distinct opioid use trajectory patterns. Risk of time to first OUD/overdose event within 1 year after the trajectory period was calculated for distinct trajectory groups using Cox proportional hazards models. Analyses were stratified by treatment type. RESULTS: Four opioid use trajectories were identified for each treatment group. For 38,030 survivors with systemic endocrine therapy, 3 trajectories were associated with increased OUD/overdose risk compared with early discontinuation: minimal dose (< 5 MME; adjusted hazard ratio [aHR] = 1.73 [95% CI 1.43-2.09]), very low dose (5-25 MME; 2.67 [2.05-3.48]), and moderate dose (51-90 MME; 6.20 [4.69-8.19]). For 9477 survivors with adjuvant chemotherapy, low-dose opioid use was associated with higher OUD/overdose risk (aHR = 7.33 [95% CI 2.52-21.31]) compared with early discontinuation. For 3513 survivors with neoadjuvant chemotherapy, the differences in OUD/OD risks across the 4 trajectories were not significant. CONCLUSIONS: Among Medicare nonmetastatic breast cancer survivors receiving systemic endocrine therapy or adjuvant chemotherapy, compared with early discontinuation, low-dose or moderate-dose opioid use were associated with six- to sevenfold higher OUD/overdose risk. Breast cancer survivors at high-risk of OUD/overdose may benefit from targeted interventions (e.g., pain clinic referral).

Medications for Opioid Use Disorder and Mortality and Hospitalization Among People With Opioid Use-related Infections.

BACKGROUND: Severe skin and soft tissue infections related to injection drug use have increased in concordance with a shift to heroin and illicitly manufactured fentanyl. Opioid agonist therapy medications (methadone and buprenorphine) may improve long-term outcomes by reducing injection drug use. We aimed to examine the association of medication use with mortality among people with opioid use-related skin or soft tissue infections. METHODS: An observational cohort study of Medicaid enrollees aged 18 years or older following their first documented medical encounters for opioid use-related skin or soft tissue infections during 2007-2018 in North Carolina. The exposure was documented medication use (methadone or buprenorphine claim) in the first 30 days following initial infection compared with no medication claim. Using Kaplan-Meier estimators, we examined the difference in 3-year incidence of mortality by medication use, weighted for year, age, comorbidities, and length of hospital stay. RESULTS: In this sample, there were 13,286 people with opioid use-related skin or soft tissue infections. The median age was 37 years, 68% were women, and 78% were white. In Kaplan-Meier curves for the total study population, 12 of every 100 patients died during the first 3 years. In weighted models, for every 100 people who used medications, there were four fewer deaths over 3 years (95% confidence interval = 2, 6). CONCLUSION: In this study, people with opioid use-related skin and soft tissue infections had a high risk of mortality following their initial healthcare visit for infections. Methadone or buprenorphine use was associated with reductions in mortality.

Computational phenotyping within electronic healthcare data to identify transgender people in the United States: A narrative review.

PURPOSE: With the expansion of research utilizing electronic healthcare data to identify transgender (TG) population health trends, the validity of computational phenotype (CP) algorithms to identify TG patients is not well understood. We aim to identify the current state of the literature that has utilized CPs to identify TG people within electronic healthcare data and their validity, potential gaps, and a synthesis of future recommendations based on past studies. METHODS: Authors searched the National Library of Medicine's PubMed, Scopus, and the American Psychological Association PsycInfo's databases to identify studies published in the United States that applied CPs to identify TG people within electronic healthcare data. RESULTS: Twelve studies were able to validate or enhance the positive predictive value (PPV) of their CP through manual chart reviews (n = 5), hierarchy of code mechanisms (n = 4), key text-strings (n = 2), or self-surveys (n = 1). CPs with the highest PPV to identify TG patients within their study population contained diagnosis codes and other components such as key text-strings. However, if key text-strings were not available, researchers have been able to find most TG patients within their electronic healthcare databases through diagnosis codes alone. CONCLUSION: CPs with the highest accuracy to identify TG patients contained diagnosis codes along with components such as procedural codes or key text-strings. CPs with high validity are essential to identifying TG patients when self-reported gender identity is not available. Still, self-reported gender identity information should be collected within electronic healthcare data as it is the gold standard method to better understand TG population health patterns.

Using Joinpoint regression for drug utilization research: Tutorial and case study of prescription opioid use in the United States.

PURPOSE: Drug utilization researchers are often interested in evaluating prescribing and medication use patterns and trends over a specified period of time. Joinpoint regression is a useful methodology to identify any deviations in secular trends without a preconceived notion of where these break points might occur. This article provides a tutorial on the use of joinpoint regression, within Joinpoint software, for the analysis of drug utilization data. METHODS: The statistical considerations for whether a joinpoint regression analytical technique is a suitable approach are discussed. Then, we offer a tutorial as an introduction on conducting joinpoint regression (within Joinpoint software) through a step-by-step application, which is a case study developed using opioid prescribing data from the United States. Data were obtained from public files available through the Centers for Disease Control and Prevention from 2006 to 2018. The tutorial provides parameters and sample data needed to replicate the case study and it concludes with general considerations for the reporting of results using joinpoint regression in drug utilization research. RESULTS: The case study evaluated the trend of opioid prescribing in the United States from 2006 to 2018, where time points of significant variation (one in 2012 and another in 2016) are detected and interpreted. CONCLUSIONS: Joinpoint regression is a helpful methodology for drug utilization for the purposes of conducting descriptive analyses. This tool also assists with corroborating assumptions and identifying parameters for fitting other models such as interrupted time series. The technique and accompanying software are user-friendly; however, researchers interested in using joinpoint regression should exercise caution and follow best practices for correct measurement of drug utilization.

Prescription Patterns of Adjuvant Pain Medications Following an Opioid Supply Restriction Law: An Interrupted Time Series Analysis.

BACKGROUND: Florida House Bill 21 (HB21) was implemented in July 2018 to limit prescriptions of Schedule II opioids for acute pain patients, but it is unclear whether such restrictions have a collateral influence on the utilization of commonly prescribed adjuvant pain medications. OBJECTIVE: The objective of this study was to assess whether this law was associated with a change in use patterns of gabapentinoids, benzodiazepines, and muscle relaxants. METHODS: We obtained prescription claims for medications dispensed from January 1, 2015, to June 31, 2019, from a health plan serving a large Florida employer. Interrupted time series analyses were conducted to compare pre-HB21 and post-HB21 implementation changes in the mean monthly number of users and prescriptions for gabapentinoids, benzodiazepines, and muscle relaxants. RESULTS: There was a 6% immediate increase (relative risk: 1.06; 95% confidence interval: 1.02, 1.11) in the monthly proportion of gabapentinoid users, and an 11% immediate increase in the monthly proportion of gabapentinoids prescriptions (relative risk: 1.11; 95% confidence interval: 1.04, 1.18) per 1000 patients following law implementation. However, after the law, we observed a significant reduction in trend for the monthly proportion of muscle relaxants and benzodiazepine users. CONCLUSIONS: An increased number of patients and prescriptions were observed for gabapentinoids, while fewer patients received benzodiazepines and muscle relaxants after HB21. In previous studies, opioid prescription restriction laws are shown to reduce opioids, but this work suggests that these laws may also have unintended consequences for the use of adjunctive medications that were not intended to be affected.

Changes in Prescribing by Provider Type Following a State Prescription Opioid Restriction Law.

BACKGROUND: Many states have implemented opioid days' supply restriction policies, leading to reductions in opioid prescribing. Although research within certain provider types exist, no study has evaluated a restriction policy by various provider types. OBJECTIVE: To evaluate changes in opioid utilization following a days' supply restriction policy stratified by provider type: surgery, emergency medicine, primary care, specialty care, and dentistry. DESIGN: Interrupted time series (ITS) PARTICIPANTS: Opioid prescription claims of patients in a private health plan serving a large Florida employer from 1/1/2015 to 3/31/2019. Provider types were determined using the Healthcare Provider Taxonomy Code associated with the national provider identifier (NPI). INTERVENTIONS: Florida's opioid restriction policy implemented on July 1, 2018. MAIN MEASURES: Changes in mean morphine milligram equivalent (MMEs), mean days' supply, and mean number of units dispensed per opioid prescription before and after policy implementation. KEY RESULTS: There were 10,583 opioid initial prescriptions dispensed. Treating providers were classified as surgery (16.4%; n = 1732), emergency care (14.3%; n = 1516), primary care (21.2%; n = 2241), specialty care (11.4%; n = 1207), and dentistry providers (23.7%; n = 2511). Significant reductions in mean days' supply were observed across most provider types ranging from 14% reduction for dentistry providers to 41% reduction for specialty care providers. Significant changes were observed for emergency care and specialty care providers with a 30% (p = 0.001)and 29% (p < 0.001) reduction in mean MME, respectively, and a 27% (p = 0.040) reduction in mean number of units dispensed in emergency care providers, after implementation. Pre-implementation trends in opioid prescribing varied by provider type impacting the effects of the opioid days' supply restriction policy. CONCLUSIONS: Pre-policy opioid prescribing varied by provider type with a differential impact on mean MMEs, mean days' supply, and mean number of units dispensed per prescription following implementation.

Co-utilization of opioids and nonbenzodiazepine hypnotic drugs in U.S. ambulatory care visits, 2006-2016.

OBJECTIVE(S): This study aimed to characterize the co-utilization of non-benzodiazepine sedative 'Z'-drugs with opioids at ambulatory care visits in the United States. DESIGN: A cross-sectional analysis of the National Ambulatory Medical Care Survey (NAMCS) from 2006 to 2016 was completed. SETTING AND PARTICIPANTS: Ambulatory care visits in the United States involving adult patients with an opioid prescription were included in the analysis. OUTCOME MEASURES: The primary outcome was initiation or continuation of a Z-drug (zolpidem, eszopiclone, or zaleplon) in a patient visit in conjunction with an opioid medication. RESULTS: The authors analyzed 564,090,296 visits (weighted from a sample of 28,773) with a reported opioid prescription. Co-utilization of opioids with Z-drugs fluctuated during the study period beginning at 4.0% in 2006 (95% CI 2.2%-5.7%), 6.3% in 2012 (3.7%-8.9%), and 4.7% in 2016 (2.8%-6.5%). Among all opioid visits in the study period, co-utilization with a Z-drug was not significantly different among female patients compared with male patients (5.26% vs. 4.63%, P = 0.26). Among visits with concomitant opioid and Z-drugs, 7.0% reported new initiation of both medications in the same visit. CONCLUSION: At ambulatory care visits between 2006 and 2016, co-utilization of opioids and Z-drugs fluctuated with some differences by sex. Major regulatory advisories and policy changes during this period may have contributed to these varying rates of utilization. Additional work is needed to identify predictors of co-utilization and downstream consequences more widely.

Impact of Opioid Restrictions During a Critical Drug Shortage Period: Interrupted Time Series for Institutional Opioid Utilization.

OBJECTIVES: This study aimed to evaluate the impact of intravenous opioid product restrictions at an academic medical institution in an urban setting during the time of critical opioid shortages. We assessed the effect of ordering restrictions on inpatient opioid utilization measured by 1) changes in intermittent oral and injectable opioid product administration; 2) changes in total institutional opioid administration; and 3) changes in the utilization of individual restricted opioid agents. METHODS: This study is a single-center retrospective analysis by interrupted time series of institutional opioid utilization from 07/2017 to 06/2018. Utilization was quantified using milligrams of intravenous morphine equivalent administered or dispensed per admitted patient. Restrictions were grouped into 10 distinct phases, which informed the interruptions in linear regression models. RESULTS: Sequential restrictions during the study period led to shifts in use of individual agents but did not have a significant impact on overall total opioid utilization. "Soft" restrictions did not have a direct, statistically significant impact on medication use but did decrease utilization over time. In situations where a product was restricted with a "soft stop" followed by a "hard stop," the "hard stop" directly reduced usage. CONCLUSIONS: Targeted ordering restrictions allowed the institution to redirect drug use according to clinical need without affecting the overall utilization. Clinical decision support led providers to choose therapeutically equivalent alternatives. The demonstrated effect of restrictions will guide institutions in the selection of "hard stop" or "soft stop" restrictions in response to future shortages.

Changes in Quantity of Opioids Dispensed following Florida's Restriction Law for Acute Pain Prescriptions.

OBJECTIVE: To assess the impact of Florida's 3-day opioid prescription supply law, effective July 2018, on opioids dispensed for acute pain patients. METHODS: Pharmacy claims from a health plan serving a large Florida employer from January 2015 through March 2019 were analyzed. We used an interrupted time series study design accounting for autocorrelation of trends before and after policy change. Acute pain patients met inclusion criteria if they had not received any opioid containing medications in the past 180 days. Patients could contribute to additional new use time if subsequent opioid claims occurred ≥180 days since the previous claim. Outcomes included mean number of units dispensed of the initial opioid prescription, mean morphine milligram equivalents (MMEs) per day of initial prescription by month, and mean total MMEs per initial prescription by month. RESULTS: A total of 8,375 enrollees had 10,583 unique opioid starts in the given timeframe. Following the policy, there was an immediate significant decrease in the units dispensed per prescription of 4.9 (95% confidence interval [CI] -8.95, -.82 units). Additionally, there was a significant immediate reduction in total MMEs dispensed per prescription of 25.6 (95% CI -44.76, -6.44 MMEs). CONCLUSIONS: Among a group of privately-insured plan enrollees in Florida, and as a result of the law, there were significant decreases in the number of units dispensed, and total MMEs of opioid prescriptions. The immediate reduction in new opioid utilization following policy implementation suggests effective policy; however, impacts on chronic pain patients were not assessed.

Effects of hydrocodone rescheduling on opioid use outcomes: A systematic review.

OBJECTIVE: To evaluate opioid prescribing, dispensing, and use in relation to hydrocodone-containing product (HCP) rescheduling. METHODS: Seven biomedical databases and grey literature sources were searched with keywords and database-specific controlled vocabulary relevant to HCP rescheduling for items published between January 2014 and July 2019. We included English-language quasi-experimental studies that assessed changes in HCP and other opioid prescribing, dispensing, utilization, and opioid-related health outcomes before and after HCP rescheduling. A data extraction sheet was created for this review. Two authors evaluated risk of bias for each included study. Two of 4 authors each independently extracted patient demographics and opioid-related outcomes from the included studies. Conflicts were resolved by a third author. RESULTS: All studies identified (n = 44) were quasi-experimental in design with 10 using an interrupted time series approach. A total of 24 studies reported a decrease in HCP prescribing by 3.1%-66.0%. Six studies reported a decrease in HCP days' supply or doses by 14.0%-80.8%. There was increased prescribing of oxycodone-containing products by 4.5%-13.9% in 5 studies, tramadol by 2.7%-53.0% in 9 studies, codeine-containing products by 0.8%-1352.9% in 8 studies). Five studies reported a decrease in morphine equivalents by at least 10%, whereas 2 studies reported an increase in morphine equivalents. Differences in populations, sample sizes, and approaches did not allow for a meta-analysis. Details regarding approach and findings were limited in published conference abstracts (n = 16). CONCLUSIONS: Hydrocodone rescheduling was associated with reductions in prescribing and use of HCPs but was also associated with increased prescribing and use of other opioids, both schedule II and nonschedule II.

Consistency of psychotropic drug-drug interactions listed in drug monographs.

BACKGROUND: With an increasing prevalence of psychotropic polypharmacy, clinicians depend on drug-drug interaction (DDI) references to ensure safe regimens, but the consistency of such information is frequently questioned. OBJECTIVES: To evaluate the consistency of psychotropic DDIs documented in Clinical Pharmacology (CP), Micromedex (MM), and Lexicomp (LC) and summarize consistent psychotropic DDIs. METHODS: In May 2016, we extracted severe or major psychotropic DDIs for 102 psychotropic drugs, including central nervous system (CNS) stimulants, antidepressants, an antimanic agent (lithium), antipsychotics, anticonvulsants, and anxiolytics-sedatives-hypnotics from CP, MM, and LC. We then summarized the psychotropic DDIs that were included in all 3 references and with evidence quality of "excellent" or "good" based on MM. RESULTS: We identified 1496, 938, and 1006 unique severe or major psychotropic DDIs from CP, MM, and LC, respectively. Common adverse effects related to psychotropic DDIs include increased or decreased effectiveness, CNS depression, neurotoxicity, QT prolongation, serotonin syndrome, and multiple adverse effects. Among these interactions, only 371 psychotropic DDIs were documented in all 3 references, 59 of which had "excellent" or "good" quality of evidence based on MM. CONCLUSION: The consistency of psychotropic DDI documentation across CP, MM, and LC is poor. DDI documentations need standards that would encourage consistency among drug information references. The list of the 59 DDIs may be useful in the assessment of psychotropic polypharmacy and highlighting DDI alerts in clinical practice.

Characteristics of US Medicare Beneficiaries with Chronic Cough vs. Non-Chronic Cough: 2011-2018.

Background: Chronic cough (CC), characterized as a cough lasting >8 weeks, is a common multi-factorial syndrome in the community, especially in older adults. Methods: Using a pre-existing algorithm to identify patients with CC within the 2011-2018 Medicare beneficiaries, we examined trends in gabapentinoid use through repeated cross-sectional analyses and identified distinct utilization trajectories using group-based trajectory modeling (GBTM) in a retrospective cohort study. Individuals without CC but with any respiratory conditions related to cough served as a comparator group. Results: Among patients with CC, gabapentinoid use increased from 18.6% in 2011 to 24.1% in 2018 (p = 0.002), with a similar upward trend observed in the non-CC cohort but with overall lower usage (14.7% to 18.4%; p < 0.001). Patients with CC had significantly higher burdens of respiratory and non-respiratory comorbidities, as well as greater healthcare service and medication use compared to the non-CC cohort. The GBTM analyses identified three distinct gabapentinoid utilization trajectories for CC and non-CC patients: no use (77.3% vs. 84.5%), low use (13.9% vs. 10.3%), and high use (8.8% vs. 5.2%). Conclusions: Future studies are needed to evaluate the safety and effectiveness of gabapentinoid use in patients with refractory or unexplained CC in real-world settings.

The Unseen Hand: AI-Based Prescribing Decision Support Tools and the Evaluation of Drug Safety and Effectiveness.

The use of artificial intelligence (AI)-based tools to guide prescribing decisions is full of promise and may enhance patient outcomes. These tools can perform actions such as choosing the 'safest' medication, choosing between competing medications, promoting de-prescribing or even predicting non-adherence. These tools can exist in a variety of formats; for example, they may be directly integrated into electronic medical records or they may exist in a stand-alone website accessible by a web browser. One potential impact of these tools is that they could manipulate our understanding of the benefit-risk of medicines in the real world. Currently, the benefit risk of approved medications is assessed according to carefully planned agreements covering spontaneous reporting systems and planned surveillance studies. But AI-based tools may limit or even block prescription to high-risk patients or prevent off-label use. The uptake and temporal availability of these tools may be uneven across healthcare systems and geographies, creating artefacts in data that are difficult to account for. It is also hard to estimate the 'true impact' that a tool had on a prescribing decision. International borders may also be highly porous to these tools, especially in cases where tools are available over the web. These tools already exist, and their use is likely to increase in the coming years. How they can be accounted for in benefit-risk decisions is yet to be seen.

Association between Opioid-Benzodiazepine Trajectories and Injurious Fall Risk among US Medicare Beneficiaries.

Background/Objectives: Concurrent opioid (OPI) and benzodiazepine (BZD) use may exacerbate injurious fall risk (e.g., falls and fractures) compared to no use or use alone. Yet, patients may need concurrent OPI-BZD use for co-occurring conditions (e.g., pain and anxiety). Therefore, we examined the association between longitudinal OPI-BZD dosing patterns and subsequent injurious fall risk. Methods: We conducted a retrospective cohort study including non-cancer fee-for-service Medicare beneficiaries initiating OPI and/or BZD in 2016-2018. We identified OPI-BZD use patterns during the 3 months following OPI and/or BZD initiation (i.e., trajectory period) using group-based multi-trajectory models. We estimated the time to first injurious falls within the 3-month post-trajectory period using inverse-probability-of-treatment-weighted Cox proportional hazards models. Results: Among 622,588 beneficiaries (age ≥ 65 = 84.6%, female = 58.1%, White = 82.7%; having injurious falls = 0.45%), we identified 13 distinct OPI-BZD trajectories: Group (A): Very-low OPI-only (early discontinuation) (44.9% of the cohort); (B): Low OPI-only (rapid decline) (15.1%); (C): Very-low OPI-only (late discontinuation) (7.7%); (D): Low OPI-only (gradual decline) (4.0%); (E): Moderate OPI-only (rapid decline) (2.3%); (F): Very-low BZD-only (late discontinuation) (11.5%); (G): Low BZD-only (rapid decline) (4.5%); (H): Low BZD-only (stable) (3.1%); (I): Moderate BZD-only (gradual decline) (2.1%); (J): Very-low OPI (rapid decline)/Very-low BZD (late discontinuation) (2.9%); (K): Very-low OPI (rapid decline)/Very-low BZD (increasing) (0.9%); (L): Very-low OPI (stable)/Low BZD (stable) (0.6%); and (M): Low OPI (gradual decline)/Low BZD (gradual decline) (0.6%). Compared with Group (A), six trajectories had an increased 3-month injurious falls risk: (C): HR = 1.78, 95% CI = 1.58-2.01; (D): HR = 2.24, 95% CI = 1.93-2.59; (E): HR = 2.60, 95% CI = 2.18-3.09; (H): HR = 2.02, 95% CI = 1.70-2.40; (L): HR = 2.73, 95% CI = 1.98-3.76; and (M): HR = 1.96, 95% CI = 1.32-2.91. Conclusions: Our findings suggest that 3-month injurious fall risk varied across OPI-BZD trajectories, highlighting the importance of considering both dose and duration when assessing injurious fall risk of OPI-BZD use among older adults.

Pragmatic Model and Faculty Toolkit for PharmD Student Engagement in Social and Administrative Pharmacy Research.

OBJECTIVE: We aim to describe the development of a pharmacy student workgroup as an experiential education model to provide social and administrative pharmacy research opportunities and provide a toolkit for faculty seeking to increase student research engagement via this model. METHODS: Three pharmacy faculty with diverse training backgrounds but a common interest in opioid medications established a workgroup named the Opioid Research Workgroup. The workgroup consisted of first-year pharmacy students, research interns, and advanced graduate trainees. A hierarchical leadership model of supervision was implemented, whereby students reported progress on research tasks directly to an advanced graduate trainee leading a project team. To understand students' perspectives on the research experience and educational outcomes, students were asked to complete an anonymous voluntary survey after a year of participation. RESULTS: Since its establishment, the workgroup has published multiple conference abstracts, manuscripts, and grants. Students' overall satisfaction with the Workgroup on a scale of 1-5, 5 being very high, was 4.69. The successful scalability and longevity of this model are dependent on administrative support that protects faculty resources. The toolkit provided offers resources for those interested in adapting this model. CONCLUSION: Our experience with the pragmatic model of pharmacy student engagement in research proved successful in terms of research output and student training experience. Although the model can be applied across a variety of health science clinical and research topics, and faculty can leverage this approach to increase productivity in research output, faculty must ensure that resources are available to support this effort.

Enhancing active learning of medication errors in the PharmD curriculum through a multi-perspective video-based experience.

INTRODUCTION: We created and assessed an immersive instructional series of video-based activities for pharmacy student evaluation of medication errors via root cause analysis (RCA). METHODS: A novel series of video vignettes showed a medication error from the perspectives of each healthcare team member involved. Students were engaged in a series of activities to guide them through RCA interspersed with the vignettes. A pre/post-assessment tool measured student-perceived skills and attitudes in medication error prevention and handling. Per item pre/post-mean scores were compared using Mann-Whitney U tests with Bonferroni correction. RESULTS: From N = 270 students, 231 and 163 completed the anonymous pre- and post-assessment, respectively. Most students positively endorsed attitude items at both assessment intervals, with no significant changes in mean for "learning how to improve patient safety is an appropriate use of time in pharmacy school" (pre-assessment = 4.26; post-assessment = 4.23). However, there were significant improvements in the skills items "I am confident in my ability to analyze a case to find the root causes of an error" (pre = 3.44; post = 3.85) and "I can identify the key factors in systems and processes that could lead to a medication error" (pre = 3.55; post = 3.88). CONCLUSIONS: Pharmacy students reported significantly improved self-perceived skills in handling and preventing medication errors, but not in attitudes, following the immersive instructional activity. There are opportunities to expand such an immersive instructional series in an interprofessional setting, which may yield different findings.