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An economic-research-based approach to calculate community health-staffing requirements in Xicheng District, Beijing

Overview of attention for article published in Human Resources for Health, December 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (59th percentile)

Mentioned by

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4 tweeters

Citations

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2 Dimensions

Readers on

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3 Mendeley
Title
An economic-research-based approach to calculate community health-staffing requirements in Xicheng District, Beijing
Published in
Human Resources for Health, December 2016
DOI 10.1186/s12960-016-0152-5
Pubmed ID
Authors

Delu Yin, Tao Yin, Huiming Yang, Qianqian Xin, Lihong Wang, Ninyan Li, Xiaoyan Ding, Bowen Chen

Abstract

A shortage of community health professionals has been a crucial issue hindering the development of CHS. Various methods have been established to calculate health workforce requirements. This study aimed to use an economic-research-based approach to calculate the number of community health professionals required to provide community health services in the Xicheng District of Beijing and then assess current staffing levels against this ideal. Using questionnaires, we collected relevant data from 14 community health centers in the Xicheng District, including resident population, number of different health services provided, and service volumes. Through 36 interviews with family doctors, nurses, and public health workers, and six focus groups, we were able to calculate the person-time (equivalent value) required for each community health service. Field observations were conducted to verify the duration. In the 14 community health centers in Xicheng District, 1752 health workers were found in our four categories, serving a population of 1.278 million. Total demand for the community health service outstripped supply for doctors, nurses, and public health workers, but not other professionals. The method suggested that to properly serve the study population an additional 64 family doctors, 40 nurses, and 753 public health workers would be required. Our calculations indicate that significant numbers of new health professionals are required to deliver community health services. We established time standards in minutes (equivalent value) for each community health service activity, which could be applied elsewhere in China by government planners and civil society advocates.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 33%
Unknown 2 67%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 67%
Lecturer 1 33%
Readers by discipline Count As %
Arts and Humanities 1 33%
Nursing and Health Professions 1 33%
Medicine and Dentistry 1 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 13 December 2016.
All research outputs
#3,746,986
of 8,763,848 outputs
Outputs from Human Resources for Health
#439
of 573 outputs
Outputs of similar age
#119,125
of 300,693 outputs
Outputs of similar age from Human Resources for Health
#16
of 20 outputs
Altmetric has tracked 8,763,848 research outputs across all sources so far. This one has received more attention than most of these and is in the 56th percentile.
So far Altmetric has tracked 573 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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 300,693 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.