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A mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of German university hospitals
Standard Data Envelopment Analysis (DEA) models consider continuous-valued and known input and output statuses for measures. This paper proposes an extended Slacks-Based Measure (SBM) DEA model to accommodate flexible (a measure that can play the role of input and output) and integer measures simult...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer US
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10011311/ https://www.ncbi.nlm.nih.gov/pubmed/36396892 http://dx.doi.org/10.1007/s10729-022-09620-5 |
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author | Zarrin, Mansour |
author_facet | Zarrin, Mansour |
author_sort | Zarrin, Mansour |
collection | PubMed |
description | Standard Data Envelopment Analysis (DEA) models consider continuous-valued and known input and output statuses for measures. This paper proposes an extended Slacks-Based Measure (SBM) DEA model to accommodate flexible (a measure that can play the role of input and output) and integer measures simultaneously. A flexible measure’s most appropriate role (designation) is determined by maximizing the technical efficiency of each unit. The main advantage of the proposed model is that all inputs, outputs, and flexible measures can be expressed in integer values without inflation of efficiency scores since they are directly calculated by modifying input and output inefficiencies. Furthermore, we illustrate and examine the application of the proposed models with 28 university hospitals in Germany. We investigate the differences and common properties of the proposed models with the literature to shed light on both teaching and general inefficiencies. Results of inefficiency decomposition indicate that “Third-party funding income” that university hospitals receive from the research-granting agencies dominates the other inefficiencies sources. The study of the efficiency scores is then followed up with a second-stage regression analysis based on efficiency scores and environmental factors. The result of the regression analysis confirms the conclusion derived from the inefficiency decomposition analysis. |
format | Online Article Text |
id | pubmed-10011311 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-100113112023-03-15 A mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of German university hospitals Zarrin, Mansour Health Care Manag Sci Article Standard Data Envelopment Analysis (DEA) models consider continuous-valued and known input and output statuses for measures. This paper proposes an extended Slacks-Based Measure (SBM) DEA model to accommodate flexible (a measure that can play the role of input and output) and integer measures simultaneously. A flexible measure’s most appropriate role (designation) is determined by maximizing the technical efficiency of each unit. The main advantage of the proposed model is that all inputs, outputs, and flexible measures can be expressed in integer values without inflation of efficiency scores since they are directly calculated by modifying input and output inefficiencies. Furthermore, we illustrate and examine the application of the proposed models with 28 university hospitals in Germany. We investigate the differences and common properties of the proposed models with the literature to shed light on both teaching and general inefficiencies. Results of inefficiency decomposition indicate that “Third-party funding income” that university hospitals receive from the research-granting agencies dominates the other inefficiencies sources. The study of the efficiency scores is then followed up with a second-stage regression analysis based on efficiency scores and environmental factors. The result of the regression analysis confirms the conclusion derived from the inefficiency decomposition analysis. Springer US 2022-11-17 2023 /pmc/articles/PMC10011311/ /pubmed/36396892 http://dx.doi.org/10.1007/s10729-022-09620-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Zarrin, Mansour A mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of German university hospitals |
title | A mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of German university hospitals |
title_full | A mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of German university hospitals |
title_fullStr | A mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of German university hospitals |
title_full_unstemmed | A mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of German university hospitals |
title_short | A mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of German university hospitals |
title_sort | mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of german university hospitals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10011311/ https://www.ncbi.nlm.nih.gov/pubmed/36396892 http://dx.doi.org/10.1007/s10729-022-09620-5 |
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