The Scarce Drugs Allocation Indicators in Iran: A Fuzzy Delphi Method Based Consensus

伊朗稀缺药品分配指标:基于模糊德尔菲法的共识

阅读:1

Abstract

Almost all countries are affected by a variety of drug-supply problems and spend a considerable amount of time and resources to address shortages. The current study aims to reach a consensus on the scarce drug allocation measures to improve the allocation process of scarce drugs in Iran by a population needs-based approach. To achieve the objective, two phases were conducted. Firstly, a set of population-based indicators of health needs were identified by reviewing the literature and were scrutinized by fifty academics/executives who were specialists in pharmaceutical resource allocation. In the second phase, a structured process, based on the Delphi technique requirements, was performed to finalize the indicators. The yield of literature review step was about 20 indicators, which was based on availability of data in Iran, 16 indicators were added to the next step and formed the initial questionnaire. Based on the results of the first questionnaire, only 3 indicators were rejected and 13 indicators were added to the Delphi phase. Then, in Delphi phase, the consensus was built after three Rounds. In addition to the burden of endemic, special, rare, and incurable diseases, traumatic diseases and total population of each province were the main measures. Furthermore, total mortality rates and the number of pharmacies in each province were on the border; hence, the monitoring team made the decision about inclusion or exclusion of such indicators. Other measures were in the range of 'important' ones. To reach a higher effective and efficient process of resource allocation, the paper suggests the use of a population needs-based approach in Iran's pharmaceutical sector. The scarce drug allocation indicators extracted in this study can make a considerable contribution to preventing, controlling, and mitigating drug shortages.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。