Evidence map›Paper›PMID 33632230›Full record

ArticleBMC health services research2021

The scale and structure of government financial investment in traditional medicine based on optimal efficiency: evidence from public traditional Chinese medicine hospitals (PTHs) of Henan province, China.

Weicun Ren, Xiaoli Fu, Clifford Silver Tarimo, Maisa Kasanga, Yanqing Wang, Jian Wu

Abstract read
In one paragraph

Article in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Weicun RenCollege of Public Health, Zhengzhou University, 100 Science Avenue Gaoxin District, Zhengzhou, People's Republic of China.
Xiaoli FuCollege of Public Health, Zhengzhou University, 100 Science Avenue Gaoxin District, Zhengzhou, People's Republic of China.
Clifford Silver TarimoCollege of Public Health, Zhengzhou University, 100 Science Avenue Gaoxin District, Zhengzhou, People's Republic of China.
Maisa KasangaCollege of Public Health, Zhengzhou University, 100 Science Avenue Gaoxin District, Zhengzhou, People's Republic of China.
Yanqing WangCollege of Public Health, Zhengzhou University, 100 Science Avenue Gaoxin District, Zhengzhou, People's Republic of China.
Jian WuCollege of Public Health, Zhengzhou University, 100 Science Avenue Gaoxin District, Zhengzhou, People's Republic of China. jianwu17@163.com.

Funding

National Key R&D Program of China 2018YFC0114501
6 · The paper itself

Abstract

backgroundTraditional medicine has been widely used to address relatively common illnesses. In this regard, Chinese government has been continually topping up its investments on public Traditional Chinese Medicine hospitals (PTHs) in recent years. This study aimed to assess the optimal scales and structure of the investments in Henan province by analyzing the contribution of Government Financial Investment (GFI) to the efficiency and revenue growth of PTHs as well as recommending proper investment strategies for implementation to policy-makers.

methodsThis study was a panel data study, conducted in Henan Province, China. By collecting 143 PTHs' operational data from the year 2005 to 2017, Barro Economic Growth (BEG) model, Stochastic Frontier Analysis (SFA) and Vector Autoregressive (VAR) model were used to assess the efficiency and PTHs revenue.

resultsThe study observed the positive contribution of GFI to PTHs' revenue growth (average MPG = 2.84), indicating that the GFI had not reached the required optimal level of "Barro Law". In order to maximize the input-output efficiency, the scales of GFI on Grade III, Grade II A, Grade II B PTHs need to be increased by - 5.96, 4.88 and 11.51%, respectively. The third year following the first investment may be a more essential period for conducting an effective GFI evaluation in Henan Province.

conclusionsGFI on PTHs usually has a long-term impact on PTHs. Governments can adjust its GFI policy so as to maximize the input-output efficiency.

Indexed as

Hospitals, PublicMedicine, Chinese TraditionalChinaGovernmentHumansInvestmentsFinancial investmentGovernmentRevenueTCM hospitals

Identifiers

PMID33632230
PMCPMC7908777

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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.