Regional healthcare resource allocation and decision-making: Evaluating the effectiveness of the three-stage super-efficiency DEA model
This study addresses the challenge of achieving a more rational allocation of medical resources at the regional level, using Guangxi Province, China, as a case study. A three-stage super-efficiency Data Envelopment Analysis (DEA) model is employed to assess and analyze the effectiveness of resource...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024163438 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850108717194805248 |
|---|---|
| author | Ying Liu Lanxian Mai Feng Huang Zhiyu Zeng |
| author_facet | Ying Liu Lanxian Mai Feng Huang Zhiyu Zeng |
| author_sort | Ying Liu |
| collection | DOAJ |
| description | This study addresses the challenge of achieving a more rational allocation of medical resources at the regional level, using Guangxi Province, China, as a case study. A three-stage super-efficiency Data Envelopment Analysis (DEA) model is employed to assess and analyze the effectiveness of resource allocation. The research methodology involves identifying input, output, and environmental variable indicators to construct a healthcare resource allocation index system. The indicator data are processed using Excel software. The three-stage super-efficiency DEA model is then applied to evaluate the healthcare system in Guangxi Province, focusing on Pure Technical Efficiency Change (PEC), Scale Efficiency Change (SEC), Efficiency Change (EC), Technological Change (TC), and Total Factor Productivity (TFP). Finally, the Malmquist index method is utilized to measure and dynamically analyze the efficiency of healthcare resource allocation. The study's results show that, from a static perspective, the average comprehensive efficiency is 1.067 before adjustment and 1.054 after adjustment, indicating relatively high overall efficiency in healthcare resource allocation in Guangxi Province. However, environmental factors and random errors have led to an overestimation of healthcare resource allocation efficiency, which the three-stage super-efficiency DEA model effectively corrects. Additionally, the average SEC and PEC values are 0.997 and 0.998, respectively, both below 1. This indicates that both scale efficiency and pure technical efficiency contribute to a decline in technical efficiency. Based on the results of the sensitivity analysis, the conclusions regarding the efficiency of healthcare resource allocation in Guangxi are deemed highly reliable. Despite the influence of uncertain factors, the model consistently provides stable and coherent assessment results in most scenarios. Therefore, special attention is needed to improve scale efficiency in healthcare resource allocation within the region, alongside enhancing management and technological capabilities in the healthcare sector. Overall, this study provides valuable reference and guidance for researchers and practitioners in related fields and offers scientific decision support for healthcare resource allocation. |
| format | Article |
| id | doaj-art-2f7e7f1834c445e49e4c452db184acf1 |
| institution | OA Journals |
| issn | 2405-8440 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-2f7e7f1834c445e49e4c452db184acf12025-08-20T02:38:17ZengElsevierHeliyon2405-84402024-12-011023e4031210.1016/j.heliyon.2024.e40312Regional healthcare resource allocation and decision-making: Evaluating the effectiveness of the three-stage super-efficiency DEA modelYing Liu0Lanxian Mai1Feng Huang2Zhiyu Zeng3School Of Public Policy And Management., Guangxi University, Nanning, 530004, Guangxi, ChinaSchool Of Information and Management, Guangxi Meidical University, Nanning, 530021, Guangxi, China; The First Affiliated Hospital, Guangxi Meidical University, Nanning, 530021, Guangxi, ChinaThe First Affiliated Hospital, Guangxi Meidical University, Nanning, 530021, Guangxi, China; Corresponding author.The First Affiliated Hospital, Guangxi Meidical University, Nanning, 530021, Guangxi, China; Corresponding author.This study addresses the challenge of achieving a more rational allocation of medical resources at the regional level, using Guangxi Province, China, as a case study. A three-stage super-efficiency Data Envelopment Analysis (DEA) model is employed to assess and analyze the effectiveness of resource allocation. The research methodology involves identifying input, output, and environmental variable indicators to construct a healthcare resource allocation index system. The indicator data are processed using Excel software. The three-stage super-efficiency DEA model is then applied to evaluate the healthcare system in Guangxi Province, focusing on Pure Technical Efficiency Change (PEC), Scale Efficiency Change (SEC), Efficiency Change (EC), Technological Change (TC), and Total Factor Productivity (TFP). Finally, the Malmquist index method is utilized to measure and dynamically analyze the efficiency of healthcare resource allocation. The study's results show that, from a static perspective, the average comprehensive efficiency is 1.067 before adjustment and 1.054 after adjustment, indicating relatively high overall efficiency in healthcare resource allocation in Guangxi Province. However, environmental factors and random errors have led to an overestimation of healthcare resource allocation efficiency, which the three-stage super-efficiency DEA model effectively corrects. Additionally, the average SEC and PEC values are 0.997 and 0.998, respectively, both below 1. This indicates that both scale efficiency and pure technical efficiency contribute to a decline in technical efficiency. Based on the results of the sensitivity analysis, the conclusions regarding the efficiency of healthcare resource allocation in Guangxi are deemed highly reliable. Despite the influence of uncertain factors, the model consistently provides stable and coherent assessment results in most scenarios. Therefore, special attention is needed to improve scale efficiency in healthcare resource allocation within the region, alongside enhancing management and technological capabilities in the healthcare sector. Overall, this study provides valuable reference and guidance for researchers and practitioners in related fields and offers scientific decision support for healthcare resource allocation.http://www.sciencedirect.com/science/article/pii/S2405844024163438Healthcare resourcesDecision-makingThree-stage super-efficiency DEA modelEfficiency evaluationPolicy recommendation |
| spellingShingle | Ying Liu Lanxian Mai Feng Huang Zhiyu Zeng Regional healthcare resource allocation and decision-making: Evaluating the effectiveness of the three-stage super-efficiency DEA model Heliyon Healthcare resources Decision-making Three-stage super-efficiency DEA model Efficiency evaluation Policy recommendation |
| title | Regional healthcare resource allocation and decision-making: Evaluating the effectiveness of the three-stage super-efficiency DEA model |
| title_full | Regional healthcare resource allocation and decision-making: Evaluating the effectiveness of the three-stage super-efficiency DEA model |
| title_fullStr | Regional healthcare resource allocation and decision-making: Evaluating the effectiveness of the three-stage super-efficiency DEA model |
| title_full_unstemmed | Regional healthcare resource allocation and decision-making: Evaluating the effectiveness of the three-stage super-efficiency DEA model |
| title_short | Regional healthcare resource allocation and decision-making: Evaluating the effectiveness of the three-stage super-efficiency DEA model |
| title_sort | regional healthcare resource allocation and decision making evaluating the effectiveness of the three stage super efficiency dea model |
| topic | Healthcare resources Decision-making Three-stage super-efficiency DEA model Efficiency evaluation Policy recommendation |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024163438 |
| work_keys_str_mv | AT yingliu regionalhealthcareresourceallocationanddecisionmakingevaluatingtheeffectivenessofthethreestagesuperefficiencydeamodel AT lanxianmai regionalhealthcareresourceallocationanddecisionmakingevaluatingtheeffectivenessofthethreestagesuperefficiencydeamodel AT fenghuang regionalhealthcareresourceallocationanddecisionmakingevaluatingtheeffectivenessofthethreestagesuperefficiencydeamodel AT zhiyuzeng regionalhealthcareresourceallocationanddecisionmakingevaluatingtheeffectivenessofthethreestagesuperefficiencydeamodel |