Assessment of the utilization of real-time prescription benefits for patient cost savings within an outpatient setting.

Background: This study evaluates the impact of Real-Time Prescription Benefits (RTPB), a tool integrated into electronic health records (EHRs), on patient out-of-pocket costs in an academic institution. RTPB provides prescribers with alternative, less expensive medications based on insurance plans. The primary measure was cost-savings, defined as the difference between the out-of-pocket cost of the prescribed medication and its alternative. Methods: A retrospective analysis of prescriptions from outpatient clinics in a university-based health system was conducted between May 2020 and July 2021. Prescriptions were analyzed at the 2nd level of the Anatomical Therapeutic Chemical (ATC) classification system. Costs were standardized to a 30-day supply. Standardized cost and total cost per prescription, and overall savings for the top 20 medication classes at the 2nd ATC level were calculated. The overall impact of RTPB was estimated based on selecting the least expensive alternative suggested by RTPB. Results: The study found that RTPB information was provided for 22% of prescriptions, with suggested alternatives for 1.26%. Among prescriptions with an alternative selected, the standardized average cost saving was $38.83. The study realized $15,416 in patient total cost savings. If the least expensive RTPB-suggested alternative were chosen for all prescriptions, an estimated $276,386 could have been saved. Psychoanaleptic and psycholeptic medications were the most prescribed with an alternative, with most savings in specialty drugs like anthelmintic and immunostimulant medications. Conclusion: The study highlights the importance of RTPB in reducing patient costs. It reports patient cost-savings with RTPB in prescribing decisions. Future research could explore the impact of RTPB on medication adherence using pharmacy claims data.

Comparison between upper and lower airway microbiome profiles in chronic rhinosinusitis patients.

BACKGROUND: Dysregulation of the airway microbiota is thought to contribute to airway inflammation in both chronic rhinosinusitis (CRS) and asthma. However, the relationship between the upper and lower airway microbiome remains unclear. METHODS: Sinus and lung brushes were collected from 29 CRS participants undergoing sinus surgery. DNA was extracted and submitted for 16s rRNA microbiome sequencing. Alpha and beta diversity metrics, taxonomic composition, and differences between individual taxa were compared for paired sinus and bronchial samples. RESULTS: Twenty-three out of 29 participants had sufficient samples for analysis. The mean (standard deviation) age was 51.59 (14.57) years, and 10 (44%) patients were female. Twelve (52%) patients had comorbid asthma. Sinus brushes had significantly higher alpha diversity indexes (Shannon and Faith) compared to bronchial brushes (p < 0.001). Beta diversity metrics were significantly different between the sinus and bronchial samples. Principal coordinate analysis showed no clustering of paired nasal and bronchial samples. Sinus brushes had significantly more Lawsonella, Corynebacterium, and Staphylococcus compared to bronchia brushes, while the latter were enriched in Tropheryma and Sphingomonas, among others (false discovery rate [FDR]-adjusted p < 0.01). Finally, CRS patients with comorbid asthma had significantly higher Pseudomonas and Peptoniphilus in sinus brushes and lower Prevotella in bronchial brushes when compared to non-asthmatics (FDR-adjusted p < 0.01). CONCLUSION: The sinus and bronchial bacterial microbiomes differ in important ways. Our study suggests that migration of bacteria from the sinus into the lower airways is unlikely in patients with CRS.

DNA Methylation Demonstrates Bronchoalveolar Cell Senescence in People Living with HIV: An Observational Cohort Study.

BACKGROUND: DNA methylation may be a link between HIV, aging, and the increased risk of lung comorbidities. We investigated whether bronchoalveolar lavage (BAL) cells of people living with HIV (PLWH) demonstrate epigenetic disruptions and advanced epigenetic aging. METHODS: BAL cell DNA methylation from 25 PLWH and 16 HIV-uninfected individuals were tested for differential methylation of Alu and LINE-1 sites, markers of aging. We used a weighted gene correlation network analysis to identify HIV- and age-associated co-methylation networks. We tested the effect of HIV on DNA methylation using a robust linear model (false discovery rate < 0.10). RESULTS: The BAL cells of PLWH were marked by global hypomethylation in both Alu and LINE-1 elements. Six co-methylated CpG networks were identified that were significantly associated with age; of these, the red module was significantly differentially methylated in PLWH and enriched pathways (e.g., Ras signaling and T-cell receptors). We identified 6428 CpG sites associated with HIV. CONCLUSIONS: We have shown here for the first time that alterations in the DNA methylation of BAL cells in the lung with HIV show a pattern of advanced aging. This study strongly supports that HIV may contribute to an increased the risk of lung comorbidities through the epigenetics of aging.

Transferability and Accuracy of Ionic Liquid Simulations with Equivariant Machine Learning Interatomic Potentials.

Ionic liquids (ILs) are an exciting class of electrolytes finding applications in many areas from energy storage to solvents, where they have been touted as "designer solvents" as they can be mixed to precisely tailor the physiochemical properties. As using machine learning interatomic potentials (MLIPs) to simulate ILs is still relatively unexplored, several questions need to be answered to see if MLIPs can be transformative for ILs. Since ILs are often not pure, but are either mixed together or contain additives, we first demonstrate that a MLIP can be trained to be compositionally transferable; i.e., the MLIP can be applied to mixtures of ions not directly trained on, while only being trained on a few mixtures of the same ions. We also investigated the accuracy of MLIPs for a novel IL, which we experimentally synthesize and characterize. Our MLIP trained on ∼200 DFT frames is in reasonable agreement with our experiments and DFT.