Evidence map›Paper›PMID 37553692›Full record

ArticleHuman resources for health2023

Nephrology workforce in China: describing current status and evaluating the optimal capacity based on real-world data.

Jingyi Wu, Qing Li, Chenlu Bao, Chao Yang, Pengfei Li, Luxia Zhang

Abstract read
In one paragraph

Article in Human resources for health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
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  7. Review
  8. Expanding the global nephrology workforce.Nature reviews. Nephrology · 2024
    Article
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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.

Jingyi WuAdvanced Institute of Information Technology, Peking University, No.233 Yonghui Road, Xiaoshan District, Hangzhou, 311215, Zhejiang, China.ORCID http://orcid.org/0000-0002-3519-3952
Qing LiAdvanced Institute of Information Technology, Peking University, No.233 Yonghui Road, Xiaoshan District, Hangzhou, 311215, Zhejiang, China.
Chenlu BaoAdvanced Institute of Information Technology, Peking University, No.233 Yonghui Road, Xiaoshan District, Hangzhou, 311215, Zhejiang, China.
Chao YangAdvanced Institute of Information Technology, Peking University, No.233 Yonghui Road, Xiaoshan District, Hangzhou, 311215, Zhejiang, China.
Pengfei LiAdvanced Institute of Information Technology, Peking University, No.233 Yonghui Road, Xiaoshan District, Hangzhou, 311215, Zhejiang, China. pfli@aiit.org.cn.
Luxia ZhangAdvanced Institute of Information Technology, Peking University, No.233 Yonghui Road, Xiaoshan District, Hangzhou, 311215, Zhejiang, China. zhanglx@bjmu.edu.cn.ORCID http://orcid.org/0000-0003-2349-2936

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aims to characterize the current status of the nephrology workforce in China and evaluate its optimal capacity based on real-world patient mobility data.

methodsData on nephrologists in China were collected from two prominent online healthcare platforms using web crawlers and natural language processing techniques. Hospitalization records of patients with chronic kidney disease (CKD) from January 2014 to December 2018 were extracted from a national administrative database in China. City-level paths of patient mobility were identified. Effects of nephrology workforce on patient mobility were analyzed using multivariate Poisson regression models.

resultsAltogether 9.13 nephrologists per million population (pmp) were in practice, with substantial city-level variations ranging from 0.16 to 88.79. The ratio of nephrologists to the estimated CKD population was 84.57 pmp. Among 6 415 559 hospitalizations of patients with CKD, 21.3% were cross-city hospitalizations and 7441 city-level paths of patient mobility with more than five hospitalizations were identified. After making adjustment for healthcare capacity, healthcare insurance, economic status, and travel characteristics, the Poisson regression models revealed that the number of nephrologists in both the source city (incidence rate ratio [IRR] 0.99, per 1 pmp increase) and destination city (IRR 1.07, per 1 pmp increase) were independently associated with patient mobility. An IRR plateau was observed when the number of nephrologists exceeded 12 pmp in the source city, while a rapidly increasing IRR was observed beyond 20 pmp in the destination city.

conclusionsThe nephrology workforce in China exhibits significant geographic variations. Based on local healthcare needs, an optimal range of 12-20 nephrologists pmp is suggested.

Indexed as

NephrologyRenal Insufficiency, ChronicHumansMobility LimitationRenal DialysisWorkforceHealth policyNephrology workforcePatient mobilityWorkforce capacity

Identifiers

PMID37553692
PMCPMC10410773

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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.