Unita di consumo dei farmaci e valutazioni farmacoeconomiche: uso e misuso di DDD e PDD

Mario Eandi

DOI: https://doi.org/10.7175/fe.v3i4.756

Abstract

In pharmacoeconomical evaluations the quantification of drug utilization has to be done on the basis of measurement units that allow comparisons among series of longitudinal and transversal data. The most common techniques used for the analysis and the comparison of drug utilization patterns are based either on the Defined Daily Dose (DDD), a unit system proposed by WHO’s Drug Utilization Research Group, or on the Prescribed Daily Dose (PDD), a statistical parameter obtained from the analysis of drug prescriptions. This article illustrates the meaning of the main indicators of drug consumption that can be build with these techniques, underlining their utility and limitations. The DDD is the conventionally established theoretical mean daily dose of a drug, referred to a way of administration and to its main indication. It is, therefore, a mere technical measurement unit that cannot be interpreted as mean prescribed or consumed dose, and even less as recommended dose. The PDD, on the contrary, is not a measurement unit but a statistical mean value, that expresses the central tendency of the prescription variability in a defined setting. Starting from Italian data on the consumption of wide-spread antibiotics, the use and interpretation of various indicators based on the DDDs and PDDs are discussed. The parameters derived with the DDD technique are suitable for monitoring drug utilization and pharmaceutical expenditure. The PDD method is more direct, indicates the mean quantities actually prescribed and permits the estimation of the total dose consumed per therapeutic cycle and of other clinically relevant parameters, but requires the acquisition of more data than the other technique does. It is also important to remark the fact that both methods can’t be directly used for economical evaluations trying to assess the efficiency of resource allocation, as they are not correlated to the clinical outcomes of the therapy.

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