Bebek Erdebilli , Cigdem Sicakyuz , İbrahim Yilmaz
{"title":"可持续医疗系统效率评估的多重标准决策和数据包络分析综合框架","authors":"Bebek Erdebilli , Cigdem Sicakyuz , İbrahim Yilmaz","doi":"10.1016/j.health.2024.100327","DOIUrl":null,"url":null,"abstract":"<div><p>Efficiency is critical in allocating sustainable healthcare resources to ensure that hospitals can effectively care for patients while maintaining high-quality care delivery. Hence, it is necessary to monitor efficiency carefully. This study aims to assess hospital unit effectiveness through a novel comprehensive approach integrating Multiple-Criteria Decision Making (MCDM) with Data Envelopment Analysis (DEA). The proposed MCDM-DEA framework involves allocating varying weights to distinct data categories. It harnesses the capabilities of the q-rung orthopair fuzzy (q-ROF) methodology to address the inherent uncertainties in healthcare performance assessment. The experimental results provide a comprehensively structured ranking system for specific hospital departments. This ranking system allows decision-makers to identify the strengths and weaknesses of each department, enabling them to make informed decisions regarding resource allocation and improvement strategies. Furthermore, the integration of MCDM-DEA provides a robust and objective assessment tool for monitoring and evaluating the performance of hospital departments over time. These rankings offer invaluable insights to decision-makers, equipping them with the strategic information needed to enhance the overall performance of hospital units.</p></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":"5 ","pages":"Article 100327"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772442524000297/pdfft?md5=6c714f9d6778326d4cafac5a4ffb5c58&pid=1-s2.0-S2772442524000297-main.pdf","citationCount":"0","resultStr":"{\"title\":\"An integrated multiple-criteria decision-making and data envelopment analysis framework for efficiency assessment in sustainable healthcare systems\",\"authors\":\"Bebek Erdebilli , Cigdem Sicakyuz , İbrahim Yilmaz\",\"doi\":\"10.1016/j.health.2024.100327\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Efficiency is critical in allocating sustainable healthcare resources to ensure that hospitals can effectively care for patients while maintaining high-quality care delivery. Hence, it is necessary to monitor efficiency carefully. This study aims to assess hospital unit effectiveness through a novel comprehensive approach integrating Multiple-Criteria Decision Making (MCDM) with Data Envelopment Analysis (DEA). The proposed MCDM-DEA framework involves allocating varying weights to distinct data categories. It harnesses the capabilities of the q-rung orthopair fuzzy (q-ROF) methodology to address the inherent uncertainties in healthcare performance assessment. The experimental results provide a comprehensively structured ranking system for specific hospital departments. This ranking system allows decision-makers to identify the strengths and weaknesses of each department, enabling them to make informed decisions regarding resource allocation and improvement strategies. Furthermore, the integration of MCDM-DEA provides a robust and objective assessment tool for monitoring and evaluating the performance of hospital departments over time. These rankings offer invaluable insights to decision-makers, equipping them with the strategic information needed to enhance the overall performance of hospital units.</p></div>\",\"PeriodicalId\":73222,\"journal\":{\"name\":\"Healthcare analytics (New York, N.Y.)\",\"volume\":\"5 \",\"pages\":\"Article 100327\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772442524000297/pdfft?md5=6c714f9d6778326d4cafac5a4ffb5c58&pid=1-s2.0-S2772442524000297-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/S2772442524000297\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare analytics (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772442524000297","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An integrated multiple-criteria decision-making and data envelopment analysis framework for efficiency assessment in sustainable healthcare systems
Efficiency is critical in allocating sustainable healthcare resources to ensure that hospitals can effectively care for patients while maintaining high-quality care delivery. Hence, it is necessary to monitor efficiency carefully. This study aims to assess hospital unit effectiveness through a novel comprehensive approach integrating Multiple-Criteria Decision Making (MCDM) with Data Envelopment Analysis (DEA). The proposed MCDM-DEA framework involves allocating varying weights to distinct data categories. It harnesses the capabilities of the q-rung orthopair fuzzy (q-ROF) methodology to address the inherent uncertainties in healthcare performance assessment. The experimental results provide a comprehensively structured ranking system for specific hospital departments. This ranking system allows decision-makers to identify the strengths and weaknesses of each department, enabling them to make informed decisions regarding resource allocation and improvement strategies. Furthermore, the integration of MCDM-DEA provides a robust and objective assessment tool for monitoring and evaluating the performance of hospital departments over time. These rankings offer invaluable insights to decision-makers, equipping them with the strategic information needed to enhance the overall performance of hospital units.