12 research outputs found

    An Interprofessional Curriculum on Antimicrobial Stewardship Improves Knowledge and Attitudes Toward Appropriate Antimicrobial Use and Collaboration.

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    BackgroundInappropriate antimicrobial use can threaten patient safety and is the focus of collaborative physician and pharmacist antimicrobial stewardship teams. However, antimicrobial stewardship is not comprehensively taught in medical or pharmacy school curricula. Addressing this deficiency can teach an important concept as well as model interprofessional healthcare.MethodsWe created an antimicrobial stewardship curriculum consisting of an online learning module and workshop session that combined medical and pharmacy students, with faculty from both professions. Learners worked through interactive, branched-logic clinical cases relating to appropriate antimicrobial use. We surveyed participants before and after the curriculum using validated questions to assess knowledge and attitudes regarding antimicrobial stewardship and interprofessional collaboration. Results were analyzed using paired χ2 and t tests and mixed-effects logistic regression.ResultsAnalysis was performed with the 745 students (425 medical students, 320 pharmacy students) who completed both pre- and postcurriculum surveys over 3 years. After completing the curriculum, significantly more students perceived that they were able to describe the role of each profession in appropriate antimicrobial use (34% vs 82%, P < .001), communicate in a manner that engaged the interprofessional team (75% vs 94%, P < .001), and describe collaborative approaches to appropriate antimicrobial use (49% vs 92%, P < .001). Student favorability ratings were high for the online learning module (85%) and small group workshop (93%).ConclusionsA curriculum on antimicrobial stewardship consisting of independent learning and an interprofessional workshop significantly increased knowledge and attitudes towards collaborative antimicrobial stewardship among preclinical medical and pharmacy students

    Impact of infrastructural policies to reduce travel time expenditure of car users with significant reductions in energy consumption

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    © 2017 Elsevier Ltd The increasing number of vehicles and drivers have led to a marked increase in travel time expenditure (TTE), congestion, demand for fossil fuels, and adverse environmental impacts. Improving energy efficiency in the transportation sector, public awareness of the behavior of the people vis-à-vis energy efficiency, implementing policies that encourage other modes of transportation (e.g., public transit, ride-sharing, bicycles, and walking, etc.) that decrease vehicle dependency are some effective approaches that mitigate the aforementioned negative effects, which will lead to significant reductions in the total energy consumption. This article investigates the effect of governmental policies on vehicle dependency reduction and the decrease of TTE by vehicle owners, and propose a novel method to calculate the current and future TTEs by individuals. The effect of demographic variables and the region on vehicle dependency and TTE for students of three of the most populated universities in Malaysia (University of Malaya, University Putra Malaysia, and University Technology Malaysia) were investigated as well. The peoples’ expectations from individual modes of transportation such as cycling and walking were also analyzed. The results showed that all demographic factors, except nationality, affect the levels of vehicle ownership, while income levels and nationality affects TTE by personal vehicles. The results show that the average TTE can be reduced by 89% if the recommended infrastructure (e.g., increase bus routes, train routes, train services, frequencies of buses and train, and facilities for cyclists, etc.) is provided. These outcomes can assist policy makers to efficiently manage transportation budgets, and would also help people decrease vehicle usage, which will subsequently decrease their corresponding TTE and fuel consumption

    A risk score for iliofemoral patients with deep vein thrombosis

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    Objective: Deep vein thrombosis (DVT) is a common condition with a high risk of post-thrombotic morbidity, especially in patients with a proximal thrombus. Successful iliofemoral clot removal has been shown to decrease the severity of postthrombotic syndrome. It is assumed that earlier thrombus lysis is associated with a better outcome. Generally, the earlier IFDVT is confirmed, the earlier thrombus lysis could be performed. D-Dimer levels and Wells score are currently used to assess the preduplex probability for DVT; however, some studies indicate that the D-dimer value varies depending on the thrombus extent and localization. Using D-dimer and other risk factors might facilitate development of a model selecting those with an increased risk of IFDVT that might benefit from early referral for additional analysis and adjunctive iliofemoral thrombectomy.Methods: All consecutive adult patients from a retrospective cohort of STAR diagnostic center (primary care) in Rotterdam suspected of having DVT between September 2004 and August 2016 were assessed for this retrospective study. The diagnostic workup for DVT including Wells score and D-dimer were performed as well as complete duplex ultrasound examination. Patients with objective evidence of DVT were categorized according to thrombus localization using the Lower Extremity Thrombolysis classification. Logistic regression analysis was done for a model predicting IFDVT. The cutoff value of the model was determined using a receiver operating characteristic curve.Results: A total of 3381 patients were eligible for study recruitment, of whom 489 (14.5%) had confirmed DVT. We developed a multivariate model (sensitivity of 77% and specificity of 82%; area under the curve, 0.90; 0.86-0.93) based on D-dimer, Wells score, age, and anticoagulation use, which is able to distinguish IFDVT patients from all patients suspected of DVT.Conclusions: This multivariate model adequately distinguishes IFDVT among all suspected DVT patients. Practically, this model could give each patient a preduplex risk score, which could be used to prioritize suspected IFDVT patients for an immediate imaging test to confirm or exclude IFDVT. Further validation studies are needed to confirm potential of this prediction model for IFDVT
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