An integrated multi-criteria approach to formulate and assess healthcare referral system strategies in developing countries

Mouhamed Bayane Bouraima , Stefan Jovčić , Libor Švadlenka , Vladimir Simic , Ibrahim Badi , Naibei Dan Maraka
{"title":"An integrated multi-criteria approach to formulate and assess healthcare referral system strategies in developing countries","authors":"Mouhamed Bayane Bouraima ,&nbsp;Stefan Jovčić ,&nbsp;Libor Švadlenka ,&nbsp;Vladimir Simic ,&nbsp;Ibrahim Badi ,&nbsp;Naibei Dan Maraka","doi":"10.1016/j.health.2024.100315","DOIUrl":null,"url":null,"abstract":"<div><p>This study aims to identify challenges in implementing a quality healthcare referral system in developing countries and explore the strategies to overcome these challenges. Data for this study were collected through consultations with experts in the field. We introduce a novel hybrid method called Criteria Importance Assessment (CIMAS) and Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN). CIMAS determines the relative importance of criteria, and AROMAN is employed to rank the strategies. The primary challenges identified include inadequate infrastructure facilities and deficient health information systems. The most appropriate strategy involves focusing on improving infrastructure facilities. We also carry out comprehensive sensitivity and comparative analyses to validate the applicability of the proposed model. This study identifies and elucidates the challenges of establishing a high-quality healthcare referral system in developing countries and substantially contributes to the existing body of knowledge by effectively delineating and prioritizing the strategies to tackle these challenges.</p></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":"5 ","pages":"Article 100315"},"PeriodicalIF":0.0000,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772442524000170/pdfft?md5=1af0ea426f4705f8f7cd160427cfd173&pid=1-s2.0-S2772442524000170-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare analytics (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772442524000170","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

This study aims to identify challenges in implementing a quality healthcare referral system in developing countries and explore the strategies to overcome these challenges. Data for this study were collected through consultations with experts in the field. We introduce a novel hybrid method called Criteria Importance Assessment (CIMAS) and Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN). CIMAS determines the relative importance of criteria, and AROMAN is employed to rank the strategies. The primary challenges identified include inadequate infrastructure facilities and deficient health information systems. The most appropriate strategy involves focusing on improving infrastructure facilities. We also carry out comprehensive sensitivity and comparative analyses to validate the applicability of the proposed model. This study identifies and elucidates the challenges of establishing a high-quality healthcare referral system in developing countries and substantially contributes to the existing body of knowledge by effectively delineating and prioritizing the strategies to tackle these challenges.

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
发展中国家制定和评估医疗转诊系统战略的综合多标准方法
本研究旨在确定发展中国家在实施优质医疗转诊系统方面所面临的挑战,并探讨克服这些挑战的策略。本研究的数据是通过咨询该领域的专家收集的。我们引入了一种名为标准重要性评估(CIMAS)和两步归一化替代排序法(AROMAN)的新型混合方法。CIMAS 确定标准的相对重要性,而 AROMAN 则用于对战略进行排序。确定的主要挑战包括基础设施不足和卫生信息系统缺陷。最合适的战略是重点改善基础设施。我们还进行了全面的敏感性分析和比较分析,以验证拟议模型的适用性。本研究确定并阐明了在发展中国家建立高质量医疗转诊系统所面临的挑战,并通过有效划分和优先排序应对这些挑战的策略,对现有知识体系做出了重大贡献。
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
Healthcare analytics (New York, N.Y.)
Healthcare analytics (New York, N.Y.) Applied Mathematics, Modelling and Simulation, Nursing and Health Professions (General)
CiteScore
4.40
自引率
0.00%
发文量
0
审稿时长
79 days
期刊最新文献
Optimized early fusion of handcrafted and deep learning descriptors for voice pathology detection and classification A deep neural network model with spectral correlation function for electrocardiogram classification and diagnosis of atrial fibrillation An ensemble convolutional neural network model for brain stroke prediction using brain computed tomography images A hierarchical Bayesian approach for identifying socioeconomic factors influencing self-rated health in Japan An electrocardiogram signal classification using a hybrid machine learning and deep learning approach
×
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