Search Results - (Author, Cooperation:F. Banfi)

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  1. 1
    S. Dal Conte ; C. Giannetti ; G. Coslovich ; F. Cilento ; D. Bossini ; T. Abebaw ; F. Banfi ; G. Ferrini ; H. Eisaki ; M. Greven ; A. Damascelli ; D. van der Marel ; F. Parmigiani
    American Association for the Advancement of Science (AAAS)
    Published 2012
    Staff View
    Publication Date:
    2012-03-31
    Publisher:
    American Association for the Advancement of Science (AAAS)
    Print ISSN:
    0036-8075
    Electronic ISSN:
    1095-9203
    Topics:
    Biology
    Chemistry and Pharmacology
    Computer Science
    Medicine
    Natural Sciences in General
    Physics
    Published by:
    http://www.aaas.org/

    Latest Papers from Table of Contents or Articles in Press
  2. 2
    Cosentino, M. ; Leoni, O. ; Banfi, F. ; Lecchini, S. ; Frigo, G.
    Springer
    Published 2000
    Staff View
    ISSN:
    1432-1041
    Keywords:
    Key words Drug prescribing ; Defined daily dose ; Drug dispensation data
    Source:
    Springer Online Journal Archives 1860-2000
    Topics:
    Chemistry and Pharmacology
    Medicine
    Notes:
    Abstract Objective: To test the hypothesis that comparison of defined daily dose (DDD) and drug user data may help to estimate drug exposure in a defined population and provide information about drug prescribing patterns. Methods and results: First, comparison of DDD figures with the number of apparent drug users (ADU, i.e., individuals for whom at least one prescription of the drug had been dispensed during a given time period) is demonstrated to correspond to the product of the prescribed daily dose (PDD) and the proportion of days in which the drug had been taken (days of treatment/days in a time period, D). The resulting equation (DDD/day)/ADU in a time period=PDD × D is then applied to the analysis of different sets of drug dispensation data. Examples show that this approach may be helpful to monitor drug prescribing patterns over time. Moreover, in definite situations, it may provide reliable estimates of either PDD or D. Conclusions: Comparison of DDD and drug user data is suggested to be a cost-effective strategy to monitor drug prescribing patterns from an epidemiological perspective, which may be useful to researchers involved in drug utilisation studies as well as to health authorities for monitoring and regulatory purposes.
    Type of Medium:
    Electronic Resource
    URL:
    http://dx.doi.org/10.1007/s002280000170

    Articles: DFG German National Licenses