American Journal of Health-System Pharmacy最新文献

Purpose: Health-system pharmacists play a crucial role in monitoring the pharmaceutical pipeline to manage formularies, allocate resources, and optimize clinical programs for new therapies. This article aims to support pharmacists by sharing new and anticipated novel drug approvals.

Summary: Selected drug approvals anticipated in the 12-month period covering the third quarter of 2024 through the second quarter of 2025 are reviewed. The analysis emphasizes drugs expected to have significant clinical and financial impact in hospitals and clinics selected from 54 novel drugs awaiting US Food and Drug Administration approval. New cell therapies for treating cancers continue to enter the drug pipeline, while novel targeted therapies for biliary tract, gastric, pancreatic, and breast cancers, as well as 3 subcutaneous versions of already approved drugs given intravenously, are awaiting approval. Additionally, many novel drugs are being developed for treatment of rare and ultra-rare diseases such as hereditary angioedema, macular telangiectasia, congenital adrenal hyperplasia, and Barth syndrome. Two new subcutaneous drugs for hemophilia, a new oral medication for hereditary angioedema, a novel monoclonal antibody for atopic dermatitis, and the first oral penem antibiotic are also in the pipeline.

Conclusion: New drugs with various indications for cancers and rare diseases continue to strengthen the drug pipeline.

Purpose: Due to the low specificity of drug-drug interaction (DDI) warnings, hospitals and healthcare systems would benefit from the ability to customize alerts, thereby reducing the burden of alerts while simultaneously preventing harm. We developed a tool, called the Drug Interaction Customization Editor (DICE), as a prototype to identify features and functionality that could assist healthcare organizations in customizing DDI alerts.

Methods: A team of pharmacists, physicians, and DDI experts identified attributes expected to be useful for filtering DDI warnings. A survey was sent to pharmacists with informatics responsibilities and other medication safety committee members to obtain their opinions about the tool. The survey asked participants to evaluate the 4 sections of the DICE tool (General, Medication, Patient, and Visit) on a scale ranging from 0 (not useful) to 100 (very useful). The survey provided an opportunity for participants to express their opinions on the overall usefulness of the DICE tool and to provide other comments.

Results: The 50 survey respondents were mainly pharmacists (n = 47, 94%) with almost half (n = 23, 47%) having health information technology/informatics training. Most respondents (n = 33, 80%) were employed by organizations with over 350 beds. Respondents indicated the most useful features of the DICE tool were the ability to filter DDI warnings based on routes of administrations (mean [SD] rating scale score, 86.5 [21.6]), primary drug properties (85.7 [20.5]), patient attributes (85.6 [16.7]) and laboratory attributes (88.8 [18.0]). The overall impression of the DICE tool was rated at 82.8 (19.0), and when asked about the potential to reduce DDI alerts, respondents rated the tool at 83.7 (21.8).

Conclusion: The ability to customize DDI alerts using data elements currently within the electronic health records (EHRs) has the potential to decrease alert fatigue and override rates. This prototype DICE tool could be used by end users and vendors as a template for developing a more advanced DDI filtering tool within EHR systems.

Purpose: To evaluate income trends among pharmacists and other select health professions (dentists, nurse practitioners, registered nurses, and physicians) in the US for the 10-year period of 2012 to 2021, with special attention given to the first 2 years of the COVID-19 pandemic (2020 and 2021).

Methods: A retrospective analysis was conducted of 2012 to 2021 income data for select health professions, collected from the American Community Survey. Univariate time series analysis was conducted using exponential smoothing to examine income patterns over the 10-year study period and forecast income for the next 5-year period (2022 to 2026) for each health profession. Additionally, time series regression models were constructed for each health profession. Descriptive statistics (mean percent change in income and SD) were calculated for each health profession for the prepandemic era (2012 to 2019) and the first 2 years of the pandemic (2020 and 2021).

Results: Goodness-of-fit statistics for each forecast model indicate highly accurate forecasts. The model for each health profession indicates a significant positive trajectory in income (P < 0.001), although pharmacists are projected to have a lower rate of income growth among the 5 health professions for the next 5-year period, 2022 to 2026. During the first 2 years of the pandemic, pharmacists had the lowest mean percent change in income (mean, 2.0%; SD, 2.0%) among the 5 health professions.

Conclusion: Growth in pharmacist income is projected to lag behind that in other health professions in the near future. Individual-, organization-, and profession-level strategies may facilitate opportunities for income growth among pharmacists.