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Deputy suggests improving medical assistance system

english.guiyang.gov.cn|Updated: 2021-03-05

Chen Yan, a deputy to the National People's Congress and the mayor of Guiyang, the capital city of Southwest China's Guizhou province, suggests improving the national medical assistance system.

As an essential part of the multi-level medical security system, medical assistance is an institutional arrangement to protect the fundamental medical rights and interests of people in need. It has played a vital role in advancing poverty alleviation and preventing illness-induced poverty. The system has also helped prevent previously impoverished people from falling back into poverty due to an illness.

In 2020, Guiyang raised 120.27 million yuan ($18.58 million) in urban and rural medical assistance funding, among which 54.74 million yuan was used to help 183,520 people in need.

Since 2008, the medical assistance system has experienced some problems in its specific implementation, according to Chen.

Among the problems are the imprecise identification of rescue targets, the lackluster regulation of rescue funds and inconsistent medical assistance standards.

To address these problems, the deputy made three detailed suggestions.

The first is to optimize the development concept of medical assistance. This includes considering diseases and medical expenses and monitoring the shift from precise short-term poverty alleviation to long-term medical equity. This suggestion also calls for making breakthrough progress to solve the problem of illness-induced poverty.

Chen's second suggestion is to optimize the top-level design of the medical assistance system. This includes the nation's issuance of new medical assistance fund management measures as soon as possible, local financial departments setting up special accounts for urban and rural medical assistance funds, and the country establishing a medical assistance reserve fund system.

The third is to optimize the payment mechanism for medical assistance benefits. This includes applying big data and other methods to accurately identify rescue targets and the launch of national guidance for medical assistance work.

 

 


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