In the present situation mapping these ambiguities and creating a standardized classification system would be advantageous.
quarter there were shortages of third generation cephalosporins. Conclusion and relevance All classes were affected. Rippling effects in J class may be assumed regarding the evolution of drug shortages. That may lead to worse consequences, such as antibiotic resistance or disruptions to patient care.
Background The growing use of supplementary products (herbal remedies, food supplements, etc.) poses an unignorable and poorly explored risk to hospital patients. The results of our previous study [1] show that 85.5% of hospital patients took at least one supplementary product; and with one patient out of four we have identified potential interactions. However, several questions arise about their clinical relevance: (1) Might the interaction harm the patient? (2) Is treatment modification or close monitoring necessary? (3) Is it reasonable to prohibit the use of any supplement? Purpose To explore and study those determinants that need to be taken into account when managing drug/supplement interactions. Materials and Methods Taking the results of our previous study as a basis we have systematically evaluated the literature and the available authentic databases. ResultsThere are significant differences between the databases we have looked at, as to which interactions are present in the system, and how broad a spectrum of active ingredients is included when a known case of interaction occurs. We identified the following factors, which have to be taken into account when evaluating a potential interaction: type of underlying evidence (in vitro studies, case reports, clinical trials, etc.) which form of a given interacting substance has been reported on (species, plant-part, type of extract, etc.) and whether this component is present in the product mechanism and dose dependence of the interaction which patient groups are more likely to develop symptoms due to the interaction We evaluated 155 components found in supplementary products by the listed criteria, then assessed the relevance and classification of interactions. Conclusions Special software, that contains all the recommended criteria we have set up, could become an effective tool for preventive screening of interactions on hospital admission. Reference A. Végh, E. Lankó, A. Fittler, L. Botz (2012): Identification and prevention of deleterious effects of supplementary health products on medical therapy – A challenge for clinical pharmacists; abstract in EJHP 19 (2), p. 95. No conflict of interest.
BackgroundAntimicrobial stewardship guidelines emphasise the importance of benchmarking hospital antimicrobial drug use in order to improve patient outcomes. However, benchmarking strategies are still in their infancy with several methodological limitations. PurposeBenchmarking antibiotic use, cost and prevalence of nosocomial infections (NI) in 7 surgical and neurosurgical wards of 3 hospitals in 2014.Material and methodsConsumption and cost of antibiotics and NI prevalence were measured in the different wards. For risk adjustment, the supposed correlation from the literature between antibiotic consumption and casemix index (CMI) was tested with regression analysis.ResultsA wide heterogeneity was found in antibiotic consumption (20–64 DDD/100 patient days; 120–730 DDD/100 admissions) and costs between the different wards. Wards using the most and least antibiotics differed when measured in the 2 metrics. In 1 ward, 19 NI/100 admissions were revealed, which was remarkably higher compared with the others (0.91–6.89 NI/100 admissions). Significant interhospital differences were detected in CMI, patient days, number of admissions and average length of stay. We found no correlation between antibiotic consumption and CMI (correlation coefficients, CMI and DDD/100 patient days -0.02; CMI and DDD/100 admissions -0.17).ConclusionThe heterogeneity in antibiotic consumption and costs might be caused by several factors: the measured interhospital differences may be influenced by variations in average length of stay, number of occupied beds and patient casemix. The ideal metric of antibiotic use is still under investigation. We suggest using both DDD/100 patient days and DDD/100 admissions. In the ward with the remarkably higher prevalence of NI, the critical appraisal of the effectiveness of local infection control practice seems to be essential. Recent risk adjustment methods, such as regression analysis with CMI, cannot be validated because these oversimplify the complex risk adjustment process. Other methods need electronic patient records, which are still rare in hospitals. Thus we suggest a novel method for adjusting risks in benchmarking. In all wards the risk factors for NI (eg, days of central venous catheters, days of mechanical ventilation) and comorbidities which influence antibiotic consumption (eg, patients with renal impairment, immunosuppressed patients) should be determined and summed, and then quantified (‘scored’) with the results of relevant good quality published studies.No conflict of interest.
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