Background: Public attention and recent US Congressional activity has intensified focus on escalating medication prices. However, the actual cost of medication use extends beyond the up-front cost of purchasing medicines. It also encompasses the additional medical costs of morbidity and mortality resulting from nonoptimized medication regimens, including medication nonadherence. Objectives: Applying the most current nationally representative data sources, our goal was to estimate the cost of prescription drug–related morbidity and mortality in the United States. Methods: Total costs of nonoptimized prescription drug use and average pathway costs for a patient who experienced a treatment failure (TF), a new medical problem (NMP), or a TF and NMP were modeled in Microsoft Excel (Microsoft Corporation, Redmond, WA) and TreeAge Pro Healthcare, v2014 (TreeAge Software, Inc, Williamstown, MA), respectively. Results: The estimated annual cost of prescription drug–related morbidity and mortality resulting from nonoptimized medication therapy was $528.4 billion in 2016 US dollars, with a plausible range of $495.3 billion to $672.7 billion. The average cost of an individual experiencing TF, NMP, or TF and NMP after initial prescription use were $2481 (range: $2233, $2742), $2610 (range: $2374, $2848) and $2572 (range: $2408, $2751), respectively. Conclusions: The estimated annual cost of drug-related morbidity and mortality resulting from nonoptimized medication therapy was $528.4 billion, equivalent to 16% of total US health care expenditures in 2016. We propose expansion of comprehensive medication management programs by clinical pharmacists in collaborative practices with physicians and other prescribers as an effective and scalable approach to mitigate these avoidable costs and improve patient outcomes.

Recent FDA approvals of glucagon-like peptide 1 (GLP-1) receptor agonists linked to substantial weight loss have generated interest in demand projections. However, a longitudinal analysis in a large, diverse, current, real-world database has not been published. The study objective was to determine user frequency of GLP-1 receptor agonist products overall and by type 2 diabetes (T2D), cardiovascular disease (CVD), and overweight/obese status. Secondary objective was monthly growth rate estimation by product since first appearance in University of California Health. This retrospective cohort study included patients who were dispensed a GLP-1 receptor agonist from 2014 to 2022 in The University of California Health Data Warehouse (UCHDW). Exponential growth rates were estimated using a log-linear regression model. Between 2014 to 2018, only Trulicity and Victoza exceeded 5,000 annual users. Ozempic users increased from 569 in 2019 to 7,667 in 2020. use accelerated with more than 13,310 users in 2021 to surpass Trulicity. Ozempic count was 22,891 in 2022. Wegovy rose from 989 in 2021 to 2,992 in 2022. Mounjaro increased to 1,508 users in 2022. While generally similar trends were observed for T2D, CVD, and overweight/obese subgroups, the ascent of Ozempic as most frequently utilized was more apparent in the overweight/obese group. The monthly growth rates were 83.9% for Ozempic, 119.2% for Wegovy, 84.8% for Rybelsus, 53.3% for Saxenda, 12.9% for Adlyxin, 78.8% for Trulicity and 254.3% for Mounjaro. This first cohort study of weight-loss associated GLP-1 agonists in a large, diverse, state-wide health system demonstrated a rapid increased use that represents a clear and, likely durable, transition in utilization for this category. Informed decision making and longitudinal studies are needed to ensure evidence-concordant prescribing and supply stability.

We sought to evaluate the relationship between different levels of medication possession ratio (MPR) attained and achievement of clinically meaningful reductions in lipid levels. This was a retrospective cohort study of 4691 new statin users from the Department of Veteran Affairs (VA). Subjects were required to be eligible for VA medical and pharmacy services throughout the 1 year study period from index date and to have complete data for exposure, outcome, and adjustment variables. MPR was defined as number of days supplied with prescription medication divided by days of observation. Achieving 25% or greater reduction from baseline in lipid levels for three lipid outcomes: non-high-density lipoprotein (non-HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and total cholesterol (TC). We observed a statistically significant trend of an increasing proportion of study subjects achieving a 25% reduction or more for all three lipid outcomes (p-values <0.001 for each of the three outcomes using the Cochran–Armitage trend test). Using multiple logistic regression, odds ratios (ORs) for each of the three outcomes were at a maximum for the 0.9–1.0 MPR category with ORs of 12.90 (95% confidence interval (CI), 9.60, 17.35) for the non-HDL cholesterol outcome; 11.29 (95% CI, 8.61, 14.80) for the LDL cholesterol outcome; and 9.11 (95% CI, 6.62, 12.53) for the TC outcome. Direct comparison of the 0.9–1.0 MPR category versus the 0.8–0.89 MPR category demonstrated an increase in odds of achieving 25% or more reduction for all three lipid outcomes. We conclude that significant improvements in outcomes are achieved with higher MPR thresholds than commonly targeted. The authors propose consideration of an MPR-adherence threshold of 0.9 MPR. Limitations include the possible modification of study findings in non-VA settings. MPR is a secondary adherence measure based on refill frequency.

The novel SARS-CoV-2 virus has caused more than 118 million cases of COVID-19 and more than 2.6 million deaths worldwide.¹ To evaluate the use of potential therapeutic options—including dexamethasone, remdesivir, enoxaparin, heparin, colchicine, hydrocortisone, tocilizumab, azithromycin, hydroxychloroquine, and medication classes of angiotensin-2 converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs)²—we measured daily and overall use percentages over the course of 2020 for hospitalized patients.

Introduction: The scope of pharmacy practice has evolved over the last few decades to focus on the optimization of medication therapy. Despite this positive impact, the lack of reimbursement remains a significant barrier to the implementation of innovative pharmacist practice models. Summary: We describe the successful development, implementation and outcomes of three types of pharmacist collaborative care models: (1) a pharmacist with physician oversight, (2) pharmacist–interprofessional teams and (3) physician–pharmacist teams. The outcome measurement of these pharmacist care models varied from the design phase to patient volume measurement and to comprehensive quality dashboards. All of these practice models have been successfully funded by affiliated health systems or grants. Conclusions: The expansion of pharmacist services delivered by clinical faculty has several benefits to affiliated health systems: (1) significant improvements in patient care quality, (2) access to experts in specialty areas, and (3) the dissemination of outcomes with national and international recognition, increasing the visibility of the health system.

BACKGROUND: Statins remain a fundamental component of pharmacologic therapy for hyperlipidemia. Health benefits of statin therapy are jeopardized when adherence is reduced. OBJECTIVES: To (a) assess the association between copayment and copayment type on statin adherence using 2 different thresholds of adherence and (b) identify the incremental change in statin adherence associated with presence of copayment and copayment type. METHODS: We executed a retrospective cohort study of new users of statins with dyslipidemia from the Veterans Health Administration (VHA) within the Veterans Integrated Service Network 22 who initiated a statin between November 30, 2006, and December 2, 2007. We used exposure categories of Any Copayment versus No Copayment, indicating a patient had a copayment or had no copayment in order to obtain medications, respectively. As a separate analysis, we varied the exposures to the standard VHA copayment categories: (a) Service-Connected (SC) Copayment (patients with service-related i...