Evidence map›Paper›PMID 35143557›Full record

ArticlePloS one2022

Unmasking unexpected health care inequalities in China using urban big data: Service-rich and service-poor communities.

Linzi Zheng, Lu Zhang, Ke Chen, Qingsong He

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 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

4 authors.

Linzi ZhengCollege of Public Administration, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0003-3409-268X
Lu ZhangSchool of Public Administration, Central China Normal University, Wuhan, China.
Ke ChenSchool of Civil and Hydraulic Engineering, Huazhong University of Science & Technology, Wuhan, China.
Qingsong HeCollege of Public Administration, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0001-9370-3335

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Geographic accessibility plays a key role in health care inequality but remains insufficiently investigated in China, primarily due to the lack of accurate, broad-coverage data on supply and demand. In this paper, we employ an innovative approach to local supply-and-demand conditions to (1) reveal the status quo of the distribution of health care provision and (2) examine whether individual households from communities with different housing prices can acquire equal and adequate quality health care services within and across 361 cities in China. Our findings support previous conclusions that quality hospitals are concentrated in cities with high administrative rankings and developmental levels. However, after accounting for the population size an "accessible" hospital serves, we discern "pro-poor" inequality in accessibility to care (denoted as GAPSD) and that GAPSD decreases along with increases in administrative rankings of cities and in community ratings. This paper is significant for both research and policy-making. Our approach successfully reveals an "unexpected" pattern of health care inequality that has not been reported before, and our findings provide a nationwide, detailed benchmark that facilitates the assessment of health and urban policies, as well as associated policy-making.

Indexed as

Big DataChinaCitiesCommunity Health ServicesHealthcare DisparitiesHealth ServicesHumansPoverty

Identifiers

PMID35143557
PMCPMC8830721

What OpenQuestion holds

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LicenceCC BY
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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.