USE OF DYNAMIC REGRESSION MODEL FOR REDUCTION OF SHORTAGES IN DRUG SUPPLY

IF 2.1 Q4 Economics, Econometrics and Finance
A. Burinskienė
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Abstract

The study is given to the use of dynamic regression model for reduction of shortages in drug supply: Purpose – the use of a dynamic regression model to identify the influence of lead-time on the reduction of time delays in drugs supply. To reach the goal, the author focuses on the improvement of drugs availability and the minimisation of time delays in drugs supply. Research methodology – the application of dynamic regression method to minimise shortage. The author suggests a dynamic regression model and accompanies it with autocorrelation and heteroskedasticity tests: Breush-Godfrey Serial Correlation LM Test for autocorrelation and ARCH test for heteroskedasticity. Findings – during analysis author identifies the relationship between lead-time and time delays in drugs supply. The author delivers a specific regression model to estimate the effect of deterministic lead-time on shortage. Probability F and Probability Chi-Square of this testing show that there is no significant autocorrelation and heteroskedasticity. Research limitations – the research is delivered for a one-month time frame. For the future, the study could review other periods. The author has incorporated the lead-time component in shortage reduction study by leaving capacity uncertainty component unresearched. The future studies could incorporate both elements into shortage reduction case analysis. Practical implications – presented framework could be useful for practitioners, which analyse drug shortage reduction cases. The revision of supply time table is recommended for pharmacies aiming to minimise the shortage level. Originality/Value – the analysis of deterministic lead-time and identification that the periodicity of shortage is evident each eight days. The study contributes to lead-time uncertainty studies where most of the authors analyse the stochastic lead-time impact on shortages.
利用动态回归模型减少药品供应短缺
研究给出了使用动态回归模型来减少药物供应短缺:目的——使用动态回归模型来确定交货时间对减少药物供应时间延迟的影响。为了实现这一目标,作者着重于提高药物的可获得性和最小化药物供应的时间延迟。研究方法-应用动态回归方法,以尽量减少短缺。作者提出了一种动态回归模型,并附有自相关和异方差检验:自相关的Breush-Godfrey序列相关LM检验和异方差的ARCH检验。在分析过程中发现,作者确定了药品供应前置时间和时间延迟之间的关系。作者提出了一个具体的回归模型来估计确定性交货期对缺货的影响。本次检验的概率F和概率卡方表明,不存在显著的自相关和异方差。研究限制-研究是一个月的时间框架交付。未来,这项研究可能会回顾其他时期。作者在减少短缺研究中引入了前置时间因素,而没有对产能不确定性因素进行研究。未来的研究可以将这两个因素纳入减少短缺的案例分析。实际意义-提出的框架可能对从业者有用,他们分析减少药物短缺的案例。建议各药房修订供应时间表,以尽量减少短缺程度。原创性/价值——对确定性交货时间的分析,确定每8天明显出现一次短缺。该研究有助于提前期不确定性研究,其中大多数作者分析了对短缺的随机提前期影响。
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CiteScore
0.30
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0.00%
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