Evidence map›Paper›PMID 36175870›Full record

ArticleBMC health services research2022

The impact of human resources for health on the health outcomes of Chinese people.

Jingjing Cheng, Xianming Kuang, Linghuang Zeng

Abstract read
In one paragraph

Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
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  10. Equity and trends in the allocation of health human resources in China from 2012 to 2021.Archives of public health = Archives belges de sante publique · 2024
    Article
  11. Article
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  14. Review
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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

3 authors.

Jingjing ChengSchool of Business Administration, Northeastern University, Shenyang, 110819, Liaoning, China. evercjjee@126.com.
Xianming KuangCenter for Economic Research, China Institute for Reform and Development, Haikou, 570311, Hainan, China.
Linghuang ZengHuman Resources Department, The First Affiliated Hospital of Hainan Medical University, Haikou, 570102, Hainan, China.

Funding

Hainan Federation of Social Science Circles HNSK(WT)18-139
6 · The paper itself

Abstract

Human resources for health (HRH) is a cornerstone in the medical system. This paper combined data envelopment analysis (DEA) with Tobit regression analysis to evaluate the efficiency of health care services in China over the years between 2007 and 2019. Efficiency was first estimated by using DEA with the choice of inputs and outputs being specific to health care services and residents' health status. Malmquist index model was selected for estimating the changes in total factor productivity of provinces and exploring whether their performance had improved over the years. Tobit regression model was then employed in which the efficiency score obtained from the DEA computations used as the dependent variable, and HRH was chosen as the independent variables. The results showed that all kinds of health personnel had a significantly positive impact on the efficiency, and more importantly, pharmacists played a critical role in affecting both the provincial and national efficiency. Therefore, the health sector should pay more attention to optimizing allocation of HRH and focusing on professional training of clinical pharmacists.

Indexed as

Asian PeopleEthnicityChinaEfficiencyEfficiency, OrganizationalHealth ResourcesHumansOutcome Assessment, Health CareWorkforceData envelopment analysis (DEA)Human resources for health (HRH)Malmquist indexResidents’ health statusTobit regression

Identifiers

PMID36175870
PMCPMC9521871

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.