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Evaluation of health resource utilization efficiency in community health centers of Jiangsu Province, China

Overview of attention for article published in Human Resources for Health, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)

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1 blog
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Citations

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31 Dimensions

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87 Mendeley
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Title
Evaluation of health resource utilization efficiency in community health centers of Jiangsu Province, China
Published in
Human Resources for Health, February 2018
DOI 10.1186/s12960-018-0275-y
Pubmed ID
Authors

Xinglong Xu, Lulin Zhou, Henry Asante Antwi, Xi Chen

Abstract

While the demand for health services keep escalating at the grass roots or rural areas of China, a substantial portion of healthcare resources remain stagnant in the more developed cities and this has entrenched health inequity in many parts of China. At its conception, China's Deepen Medical Reform started in 2012 was intended to flush out possible disparities and promote a more equitable and efficient distribution of healthcare resources. Nearly half a decade of this reform, there are uncertainties as to whether the attainment of the objectives of the reform is in sight. Using a hybrid of panel data analysis and an augmented data envelopment analysis (DEA), we model human resources, material, finance to determine their technical and scale efficiency to comprehensively evaluate the transverse and longitudinal allocation efficiency of community health resources in Jiangsu Province. We observed that the Deepen Medical Reform in China has led to an increase concern to ensure efficient allocation of community health resources by health policy makers in the province. This has led to greater efficiency in health resource allocation in Jiangsu in general but serious regional or municipal disparities still exist. Using the DEA model, we note that the output from the Community Health Centers does not commensurate with the substantial resources (human resources, materials, and financial) invested in them. We further observe that the case is worst in less-developed Northern parts of Jiangsu Province. The government of Jiangsu Province could improve the efficiency of health resource allocation by improving the community health service system, rationalizing the allocation of health personnel, optimizing the allocation of material resources, and enhancing the level of health of financial resource allocation.

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 87 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 8%
Researcher 6 7%
Student > Doctoral Student 6 7%
Student > Bachelor 5 6%
Student > Master 4 5%
Other 17 20%
Unknown 42 48%
Readers by discipline Count As %
Medicine and Dentistry 9 10%
Nursing and Health Professions 8 9%
Economics, Econometrics and Finance 6 7%
Social Sciences 6 7%
Business, Management and Accounting 4 5%
Other 11 13%
Unknown 43 49%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 March 2018.
All research outputs
#4,169,998
of 25,382,440 outputs
Outputs from Human Resources for Health
#482
of 1,261 outputs
Outputs of similar age
#76,611
of 344,345 outputs
Outputs of similar age from Human Resources for Health
#13
of 17 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,261 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.3. This one has gotten more attention than average, scoring higher than 61% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 344,345 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.