17 research outputs found

    Соціальний капітал у формуванні екстерналій освітньої сфери

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    У статті аналізується передавальний механізм імпульсу, який одержує економіка від зміни рівня освіти. Виходячи із припущення про прискорення (уповільнення) економічного зростання як одну із можливих екстерналій освіти, автори досліджують опосередкований вплив соціального капіталу на формування цієї екстерналії.В статье анализируется передаточный механизм импульса, полученного экономикой от изменения уровня образования. Исходя из предположения об ускорении (замедлении) экономического роста как о возможной экстерналии образования, авторы исследуют опосредованное влияние социального капитала на формирование этой экстерналии.The article under consideration analyzes the intermediary mechanism of impulse which results in economics due to education level change. In terms of assumption as regards economic growth acceleration (impairment) as one of possible education externalities the authors are researching the indirect social capital influence upon this externality formation

    Inter-hospital variation in the utilization of diagnostics and their proportionality in the management of adult community-acquired pneumonia

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    Background: Utilization of diagnostics and biomarkers are the second largest cost drivers in the management of patients hospitalized with community-acquired pneumonia (CAP). The present study aimed to systematically assess the inter-hospital variation in these cost drivers in relation to antibiotic use in CAP. Methods: Detailed resource utilization data from 300 patients who participated in a multicenter placebo-controlled trial investigating dexamethasone as adjunctive treatment for community-acquired pneumonia was grouped into 3 categories: clinical chemistry testing, radiological exams, and microbiological testing. Based on the identified top 5 items per category, average costs were calculated per category and per hospital. Antibiotic de-escalation at day 3 and secondary ICU admission were assessed as outcomes for proportionality of diagnostics use. Results: The mean costs for diagnostics varied between hospitals from 350 (SD 31) to 841 (SD 37) euro per patient (p < 0.001). This difference was primarily explained by variation in costs for microbiological testing (mean 195 vs. 726 euro per patient, p < 0.001). There was no difference in number of secondary ICU admissions but there was an inverse association between the costs of microbiological testing and level of antibiotic de-escalation. De-escalation occurred most frequently in the hospital with the lowest cost for microbiological testing (48% vs. 30%; p = 0.018). The latter hospital had an automated physician alert system in place to consider a timely iv-to-oral switch of antibiotics. Conclusions: Large inter-hospital variation exists in resource utilization, mainly in microbiological diagnostics in the management of adult patients with community-acquired pneumonia. A counterintuitive inverse association between the magnitude of these costs and the amount of antibiotic de-escalation was found. Future studies about the optimal cost-effective set of microbiological testing for antimicrobial stewardship in pneumonia patients should acknowledge the interaction between testing, way of communication of results and triggered physician alert systems. Trial registration: ClinicalTrials.gov NCT01743755

    Inter-hospital variation in the utilization of diagnostics and their proportionality in the management of adult community-acquired pneumonia

    No full text
    Background: Utilization of diagnostics and biomarkers are the second largest cost drivers in the management of patients hospitalized with community-acquired pneumonia (CAP). The present study aimed to systematically assess the inter-hospital variation in these cost drivers in relation to antibiotic use in CAP. Methods: Detailed resource utilization data from 300 patients who participated in a multicenter placebo-controlled trial investigating dexamethasone as adjunctive treatment for community-acquired pneumonia was grouped into 3 categories: clinical chemistry testing, radiological exams, and microbiological testing. Based on the identified top 5 items per category, average costs were calculated per category and per hospital. Antibiotic de-escalation at day 3 and secondary ICU admission were assessed as outcomes for proportionality of diagnostics use. Results: The mean costs for diagnostics varied between hospitals from 350 (SD 31) to 841 (SD 37) euro per patient (p < 0.001). This difference was primarily explained by variation in costs for microbiological testing (mean 195 vs. 726 euro per patient, p < 0.001). There was no difference in number of secondary ICU admissions but there was an inverse association between the costs of microbiological testing and level of antibiotic de-escalation. De-escalation occurred most frequently in the hospital with the lowest cost for microbiological testing (48% vs. 30%; p = 0.018). The latter hospital had an automated physician alert system in place to consider a timely iv-to-oral switch of antibiotics. Conclusions: Large inter-hospital variation exists in resource utilization, mainly in microbiological diagnostics in the management of adult patients with community-acquired pneumonia. A counterintuitive inverse association between the magnitude of these costs and the amount of antibiotic de-escalation was found. Future studies about the optimal cost-effective set of microbiological testing for antimicrobial stewardship in pneumonia patients should acknowledge the interaction between testing, way of communication of results and triggered physician alert systems. Trial registration: ClinicalTrials.gov NCT01743755

    Course of SP-D, YKL-40, CCL18 and CA 15-3 in adult patients hospitalised with community-acquired pneumonia and their association with disease severity and aetiology : A post-hoc analysis

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    BACKGROUND AND AIM: SP-D, YKL-40, CCL18 and CA 15-3 are pulmonary markers that have been extensively investigated in different chronic pulmonary diseases. However, in acute pulmonary diseases, such as community-acquired pneumonia (CAP), little is known about the course of these markers and their relationship with the aetiological agent. The aim of this study was to investigate the course of these four markers in CAP and to study influence of disease severity, aetiology and antibiotic use prior to admission on their course. METHODS: We included 291 adult patients hospitalised with CAP and 20 healthy controls. Measurements were performed in serum of day 0, 2, and 4, and at least 30 days after admission. RESULTS: Our most important results were: 1) At all time-points, including 30 days after admission, YKL-40 and CCL18 levels were higher in CAP patients compared to healthy controls; and 2) Patients with CAP caused by an intracellular, atypical bacterium had lower YKL-40 and especially CCL18 levels on and during admission in comparison with other or unknown CAP aetiology. CONCLUSIONS: Our findings suggest that these pulmonary markers could be useful to assess CAP severity and, especially YKL-40 and CCL18 by helping predict CAP caused by atypical pathogens

    Atypical aetiology in patients hospitalised with community-acquired pneumonia is associated with age, gender and season; a data-analysis on four Dutch cohorts

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    BACKGROUND: Microorganisms causing community-acquired pneumonia (CAP) can be categorised into viral, typical and atypical (Legionella species, Coxiella burnetii, Mycoplasma pneumoniae, and Chlamydia species). Extensive microbiological testing to identify the causative microorganism is not standardly recommended, and empiric treatment does not always cover atypical pathogens. In order to optimize epidemiologic knowledge of CAP and to improve empiric antibiotic choice, we investigated whether atypical microorganisms are associated with a particular season or with the patient characteristics age, gender, or chronic obstructive pulmonary disease (COPD). METHODS: A data-analysis was performed on databases from four prospective studies, which all included adult patients hospitalised with CAP in the Netherlands (N = 980). All studies performed extensive microbiological testing. RESULTS: A main causative agent was identified in 565/980 (57.7 %) patients. Of these, 117 (20.7 %) were atypical microorganisms. This percentage was 40.4 % (57/141) during the non-respiratory season (week 20 to week 39, early May to early October), and 67.2 % (41/61) for patients under the age of 60 during this season. Factors that were associated with atypical causative agents were: CAP acquired in the non-respiratory season (odds ratio (OR) 4.3, 95 % CI 2.68-6.84), age <60 year (OR 2.9, 95 % CI 1.83-4.66), male gender (OR 1.7, 95 % CI 1.06-2.71) and absence of COPD (OR 0.2, 95 % CI 0.12-0.52). CONCLUSIONS: Atypical causative agents in CAP are associated with respectively non-respiratory season, age <60 years, male gender and absence of COPD. Therefore, to maximise its yield, extensive microbiological testing should be considered in patients <60 years old who are admitted with CAP from early May to early October. TRIAL REGISTRATION: NCT00471640 , NCT00170196 (numbers of original studies)
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