Reports from Xidian University Provide New Insights into Cybernetics and Systems Analysis (A Supply Chain Model for Medicare of Impoverished People With the Policy of Targeted Poverty Alleviation of China) - Insurance News | InsuranceNewsNet

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March 12, 2020 Newswires
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Reports from Xidian University Provide New Insights into Cybernetics and Systems Analysis (A Supply Chain Model for Medicare of Impoverished People With the Policy of Targeted Poverty Alleviation of China)

Health Policy and Law Daily

2020 MAR 12 (NewsRx) -- By a News Reporter-Staff News Editor at Health Policy and Law Daily -- Researchers detail new data in Cybernetics and Systems Analysis. According to news reporting from Xi’an, People’s Republic of China, by NewsRx journalists, research stated, “The purpose of this paper is to present a new method and model for constructing a new decision-making paradigm of Medicare, which can not only satisfy the needs of the sick people but also reduce the possibility of people slipping back to poverty due to diseases under the policy of Targeted Poverty Alleviation (TPA) of China. Design/methodology/approach This paper uses the traditional supply chain theory to analyze the Medicare of impoverished people with the policy of TPA of China and transforms it into a multi-layer supply chain optimization decision-making problem.”

Funders for this research include National Natural Science Foundation of China, Youth Innovation Team of Shaanxi Universities, Fundamental Research Funds for the Central Universities, Interdisciplinary Foundation of Humanities and Information of Xidian University.

The news correspondents obtained a quote from the research from Xidian University, “First, a nonlinear integer programming model for poor people’s Medicare decision with opportunity constraints is constructed. To facilitate the solution of the optimal decision scheme, the abovementioned model is transformed into a linear integer programming model with opportunity constraints by using the Newsvendor model for reference. Meanwhile, the scope of the inventory model is discussed, for it can be combined with the construction of the medical insurance system better. Second, the theoretical model is applied to the practical problem. Finally, based on the results of the theoretical model applying the practical problem, we give further improvement and modification of the theoretical model applies it to the actual situation further. This paper presents a theoretical model about determine the optimal the inventory, under the framework of traditional supply chain decision-making, for it can be combined with the construction of the medical insurance system better. The theoretical model is applied to the practical problem of the fight against poverty in XX County, China. By using the actual data and MATLAB, optimal decision scheme is obtained. Originality/value There are two aspects of value. On the one hand, this paper provides a new way to construct a Medicare system of impoverished people with TPA of China.”

According to the news reporters, the research concluded: “On the other hand, this paper tries making a new way to handle the storage of medicines and related medical devices at basic standard clinics decision-making problems based on above mentioned Medicare system.”

For more information on this research see: A Supply Chain Model for Medicare of Impoverished People With the Policy of Targeted Poverty Alleviation of China. Kybernetes, 2019;49(3):896-915. Kybernetes can be contacted at: Emerald Group Publishing Ltd, Howard House, Wagon Lane, Bingley BD16 1WA, W Yorkshire, England.

Our news journalists report that additional information may be obtained by contacting B.Z. Sun, Xidian University, School of Economics and Management, Xian, People’s Republic of China.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1108/K-03-2019-0180. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

(Our reports deliver fact-based news of research and discoveries from around the world.)

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