Advancing Healthcare Service Efficacy by Optimizing Pharmaceutical Inventory Management: Leveraging ABC, VED Analysis for Trend Demand

G. Umadevi, S. Umamaheswari
{"title":"Advancing Healthcare Service Efficacy by Optimizing Pharmaceutical Inventory Management: Leveraging ABC, VED Analysis for Trend Demand","authors":"G. Umadevi, S. Umamaheswari","doi":"10.6000/1929-6029.2023.12.33","DOIUrl":null,"url":null,"abstract":"Background: The modern world has witnessed significant advancements across various industries such as food, healthcare, fashion, economics, and education. Among these sectors, healthcare is essential, given its critical role in promoting the well-being of individuals and communities. Purpose: Pharmaceuticals are a significant part of the healthcare system, as they are a crucial factor in increasing life expectancy and are often considered the heart of the health industry. Maintaining effective inventory management for drugs is essential for pharmacists to provide efficient and reliable services to their patients. Methodology: The study thoroughly analyzes the cost and consumption data for each type of demand, to develop a well-suited review and issuance policy for the apothecary. Research Limitations/Implications: The paper delves into the ABC analysis, VED analysis, and trend demand for medical stores, making it a valuable resource for pharmacy stores seeking to optimize their operations and inventory management. Originality/Value: A total of 564 drugs were included in this study, and data were collected from random strip sales between October 2022 and Mar 2023. The study's findings can be used to make informed decisions about inventory planning and classification strategies. The model utilized in this study is based on three categories of medicines: high priority, medium priority, and low priority. By analyzing the demand for these medicines, they can be categorized based on their priority within the three core groups. Pharmacists can use the model to detect shortages and take proactive measures to avoid them by analyzing demand patterns and inventory levels.","PeriodicalId":73480,"journal":{"name":"International journal of statistics in medical research","volume":"34 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of statistics in medical research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.6000/1929-6029.2023.12.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Background: The modern world has witnessed significant advancements across various industries such as food, healthcare, fashion, economics, and education. Among these sectors, healthcare is essential, given its critical role in promoting the well-being of individuals and communities. Purpose: Pharmaceuticals are a significant part of the healthcare system, as they are a crucial factor in increasing life expectancy and are often considered the heart of the health industry. Maintaining effective inventory management for drugs is essential for pharmacists to provide efficient and reliable services to their patients. Methodology: The study thoroughly analyzes the cost and consumption data for each type of demand, to develop a well-suited review and issuance policy for the apothecary. Research Limitations/Implications: The paper delves into the ABC analysis, VED analysis, and trend demand for medical stores, making it a valuable resource for pharmacy stores seeking to optimize their operations and inventory management. Originality/Value: A total of 564 drugs were included in this study, and data were collected from random strip sales between October 2022 and Mar 2023. The study's findings can be used to make informed decisions about inventory planning and classification strategies. The model utilized in this study is based on three categories of medicines: high priority, medium priority, and low priority. By analyzing the demand for these medicines, they can be categorized based on their priority within the three core groups. Pharmacists can use the model to detect shortages and take proactive measures to avoid them by analyzing demand patterns and inventory levels.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过优化药品库存管理提高医疗保健服务效率:利用 ABC 和 VED 分析了解需求趋势
背景:当今世界,食品、医疗保健、时尚、经济和教育等各行各业都取得了长足的进步。在这些行业中,医疗保健至关重要,因为它在促进个人和社区福祉方面发挥着关键作用。 目的:药品是医疗保健系统的重要组成部分,因为药品是延长预期寿命的关键因素,通常被视为医疗保健行业的核心。药剂师要为患者提供高效可靠的服务,就必须对药品进行有效的库存管理。 研究方法:本研究深入分析了各类需求的成本和消耗数据,为药剂师制定了一套完善的审查和发放政策。 研究局限性/意义:本文深入分析了医药商店的 ABC 分析、VED 分析和趋势需求,为药店优化运营和库存管理提供了宝贵的资源。 原创性/价值:本研究共涉及 564 种药品,数据来自 2022 年 10 月至 2023 年 3 月期间的随机带状销售。研究结果可用于就库存规划和分类策略做出明智决策。本研究采用的模型基于三类药品:高优先级、中优先级和低优先级。通过分析这些药品的需求量,可以根据其在三个核心类别中的优先级对其进行分类。药剂师可利用该模型检测短缺情况,并通过分析需求模式和库存水平采取积极措施避免短缺。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
0.40
自引率
0.00%
发文量
0
期刊最新文献
Support of Characteristics, Physical Environmental and Psychological On Quality Of Life Of Patients With DM Type II Competing Risks Model to Evaluate Dropout Dynamics Among the Type 1 Diabetes Patients Registered with the Changing Diabetes in Children (CDiC) Program The Impact of the Risk Perception of COVID-19 PANDEMIC on College Students' Occupational Anxiety: The Moderating Effect of Career Adaptability Adaptive Elastic Net on High-Dimensional Sparse Data with Multicollinearity: Application to Lipomatous Tumor Classification Triglyceridemic Waist Phenotypes as Risk Factors for Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1