Evidence map›Paper›PMID 36359698›Full record

ArticleEntropy (Basel, Switzerland)2022

Using Shannon Entropy to Improve the Identification of MP-SBM Models with Undesirable Output.

Zhanxin Ma, Jie Yin, Lin Yang, Yiming Li, Lei Zhang, Haodong Lv

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zhanxin MaSchool of Economics and Management, Inner Mongolia University, Hohhot 010021, China.
Jie YinSchool of Economics and Management, Inner Mongolia University, Hohhot 010021, China.
Lin YangSchool of Economics and Management, Inner Mongolia University, Hohhot 010021, China.
Yiming LiSchool of Economics and Management, Inner Mongolia University, Hohhot 010021, China.
Lei ZhangSchool of Economics and Management, Inner Mongolia University, Hohhot 010021, China.
Haodong LvSchool of Environment, Tsinghua University, Beijing 100084, China.

Funding

Inner Mongolia Natural Science Foundation 2021MS07025National Natural Science Foundation of China 72161031, 71661025, 72104114Program for Young Talents of Science and Technology in Universities of Inner Mongolia Auton-omous Region, and the Philosophy and Social Science Planning Project of the Inner Mongolia Autonomous Region 2021NDC179, 2021NDB167
6 · The paper itself

Abstract

In the context of the COVID-19 global epidemic, it is particularly important to use limited medical resources to improve the systemic control of infectious diseases. There is a situation where a shortage of medical resources and an uneven distribution of resources in China exist. Therefore, it is important to have an accurate understanding of the current status of the healthcare system in China and to improve the efficiency of their infectious disease control methods. In this study, the MP-SBM-Shannon entropy model (modified panel slacks-based measure Shannon entropy model) was proposed and applied to measure the disposal efficiency of the medical institutions responding to public health emergencies (disposal efficiency) in China from 2012 to 2018. First, a P-SBM (panel slacks-based measure) model, with undesirable outputs based on panel data, is given in this paper. This model measures the efficiency of all DMUs based on the same technical frontier and can be used for the dynamic efficiency analysis of panel data. Then, the MP-SBM model is applied to solve the specific efficiency paradox of the P-SBM model caused by the objective data structure. Finally, based on the MP-SBM model, undesirable outputs are considered in the original efficiency matrix alignment combination for the deficiencies of the existing Shannon entropy-DEA model. The comparative analysis shows that the MP-SBM-Shannon model not only solves the problem of the efficiency paradox of the P-SBM model but also improves the MP-SBM model identification ability and provides a complete ranking with certain advantages. The results of the study show that the disposal efficiency of the medical institutions responding to public health emergencies in China shows an upward trend, but the average combined efficiency is less than 0.47. Therefore, there is still much room for improvement in the efficiency of infectious disease prevention and control in China. It is found that the staffing problem within the Center for Disease Control and the health supervision office are two stumbling blocks.

Indexed as

data envelopment analysisefficiency assessmentMP-SBMpublic health eventsShannon entropy model

Identifiers

PMID36359698
PMCPMC9689818

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.