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Introduction: Patients on nonvitamin K antagonist (NVKA) are usually taking other drugs. Potential interaction may increase the gastrointestinal (GI) bleeding risk associated with NVKA. Methods: Observational cohort study using Medicare data from 2017 to 2020. Participants receiving a NVKA were included. A concomitant overlapping period while on NVKA was assessed for nonsteroidal anti‐inflammatory drugs (NSAIDS), selective serotonin reuptake inhibitors (SSRI), antiplatelets, glucocorticoids, aspirin and proton pump inhibitors (PPI). A logistic regression predicting either any bleeding or GI bleeding was conducted estimating the odds ratio (OR) and 95% confidence interval (CI). Results: A total of 102 531 people on NVKA with mean age 77 years (SD = 9.8) and 55% females (N = 56 671) were included. Previous history of GI bleeding occurred in 2 908 (2.8%) participants, concomitant exposure to PPI occurred in 38 713 (38%), SSRI in 16 487 (16%), clopidogrel in 15 795 (15.4%), NSAIDs in 13 715 (13.4%) and glucocorticoids in 13 715 (13.4%). Risk for any bleeding was shown for clopidogrel (OR: 1.37, 95% CI: 1.30, 1.44), prasugrel/ticagrelor (OR: 1.36, 95% CI: 1.18, 1.58), glucocorticoids (OR: 1.26, 95% CI: 1.19, 1.34), and SSRIs (OR: 1.13, 95% CI: 1.07, 1.19). GI bleeding risk was shown for clopidogrel (OR: 1.44, 95% CI: 1.34, 1.55), prasugrel/ticagrelor (OR: 1.47, 95% CI: 1.20, 1.79), SSRIs (OR: 1.09, 95% CI: 1.01, 1.17) and glucocorticoids (OR: 1.33, 95% CI: 1.23, 1.44). PPI use was correlated with both NSAID (r = 0.07, p ≤ 0.0001) and SSRI use (r = 0.09, p ≤ 0.0001). Conclusion: NVKA concomitantly taken with antiplatelets, glucocorticoids, and SSRIs showed an increased risk for any bleeding and GI bleeding. [ABSTRACT FROM AUTHOR]

Background: Warnings about drug-drug interactions (DDIs) between warfarin and nonsteroidal anti-inflammatory drugs (NSAIDs) within electronic health records indicate potential harm but fail to account for contextual factors and preferences. We developed a tool called DDInteract to enhance and support shared decision-making (SDM) between patients and physicians when both warfarin and NSAIDs are used concurrently. DDInteract was designed to be integrated into electronic health records using interoperability standards. Objective: The purpose of this study was to conduct a formative evaluation of a DDInteract that incorporates patient and product contextual factors to estimate the risk of bleeding. Methods: A randomized formative evaluation was conducted to compare DDInteract to usual care (UC) using physician-patient dyads. Using case vignettes, physicians and patients on warfarin participated in simulated virtual clinical encounters where they discussed the use of taking ibuprofen and warfarin concurrently and determined an appropriate therapeutic plan based on the patient's individualized risk. Dyads were randomized to either DDInteract or UC. Participants completed a postsession interview and survey of the SDM process. This included the 9-item Shared Decision-Making Questionnaire (SDM-Q-9), tool usability and workload National Aeronautics and Space Administration (NASA) Task Load Index, Unified Theory of Acceptance and Use of Technology (UTAUT), Perceived Behavioral Control (PBC) scale, System Usability Scale (SUS), and Decision Conflict Scale (DCS). They also were interviewed after the session to obtain perceptions on DDInteract and UC resources for DDIs. Results: Twelve dyad encounters were performed using virtual software. Most (n=11, 91.7%) patients were over 50 years of age, and 9 (75%) had been taking warfarin for more than 2 years (75%). Regarding scores on the SDM-Q-9, participants rated DDInteract higher than UC for questions pertaining to helping patients clarify the decision (P=.03), involving patients in the decision (P=.01), displaying treatment options (P<.001), identifying advantages and disadvantages (P=.01), and facilitating patient understanding (P=.01) and discussion of preferences (P=.01). Five of the 8 UTAUT constructs showed differences between the 2 groups, favoring DDInteract (P<.05). Usability ratings from the SUS were significantly higher (P<.05) for physicians using DDInteract compared to those in the UC group but showed no differences from the patient's perspective. No differences in patient responses were observed between groups using the DCS. During the session debrief, physicians indicated little concern for the additional time or workload entailed by DDInteract use. Both clinicians and patients indicated that the tool was beneficial in simulated encounters to understand and mitigate the risk of harm from this DDI. Conclusions: Overall, DDInteract may improve encounters where there is a risk of bleeding due to a potential drug-drug interaction involving anticoagulants. Participants rated DDInteract as logical and useful for enhancing SDM. They reported that they would be willing to use the tool for an interaction involving warfarin and NSAIDs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Single phase monoclinic Li4MgOsO6 is prepared by solid state reaction of a stoichiometric mixture of Li5OsO6, Os, OsO2, and MgO (pressed pellet, Al2O3 crucible in evacuated silica tubes, 800 °C, 24 h; heating and cooling rates of 100 °C/h). [ABSTRACT FROM AUTHOR]