Evidence map›Paper›PMID 34527390›Full record

ArticleSafety and health at work2021

Occupational Health Protection for Health Workers in China With Lessons Learned From the UK: Qualitative Interview and Policy Analysis.

Huan Xu, Min Zhang, Alan Hudson

Abstract read
In one paragraph

Article in Safety and health at work, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 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

3 authors.

Huan XuChevening Visiting Fellow, University of Oxford, UK.
Min ZhangSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences/Peking Union Medical College, China.
Alan HudsonProgrammes in Leadership and Public Policy, University of Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealthcare settings have been recognized among the most hazardous places to work. Based on the five categories of occupational hazards that were identified by the ILO and WHO, this study aimed to analyze policy framework relevant to occupational health protection of health workers (HWs) in public health service in China, then discussed how to share the experience of the National Health Service (NHS) England for improvement.

methodsBased on policy learning theories, policy analysis and qualitative interview were used in this study.

resultsIn the Chinese public health service, at least five laws related to the regulation of occupational health protection for HWs; however, enforcement of relevant laws was separated and multi-centered; the national monitoring system, which targeted to occupational hazards and health outcome for HWs in China, had yet to be developed; the top three priorities were workplace violence, bloodborne pathogens, and musculoskeletal disorders; national strategies included Security Hospital, and Healthy China 2030. In NHS England, three laws were fundamental; several monitoring systems had been set up, including NHS Staff Survey, Commissioning for Quality and Innovation incentive scheme; mental health, musculoskeletal problem, and nutrition disorder and overweight were raised great concern; Health and Safety, and NHS Healthy Workforce Program were critical nationwide strategies.

conclusionThere were several similarities as well as differences between the Chinese public health system and NHS England, which laid foundation of learning by China. Recommendations of improving occupational health policies in China were provided, based on the lessons learned from the NHS England.

Indexed as

Chinahealth workerNational Health Serviceoccupational health and safetypublic health service

Identifiers

PMID34527390
PMCPMC8430442

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Registered trials

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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.