Evidence map›Paper›PMID 37006575›Full record

ArticleFrontiers in public health2023

Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China.

Enhong Dong, Xiaoting Sun, Ting Xu, Shixiang Zhang, Tao Wang, Lufa Zhang, Weimin Gao

Abstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
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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

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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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

7 authors.

Enhong DongDepartment of Health Management, School of Nursing and Health Management, Shanghai University of Medicine and Health Science, Shanghai, China.
Xiaoting SunCollege of Public Health and Family Medicine, Shanghai Tongji Hospital, Tongji University School of Medicine, Shanghai, China.
Ting XuDepartment of Health Management, School of Nursing and Health Management, Shanghai University of Medicine and Health Science, Shanghai, China.
Shixiang ZhangEmergency Medical Rescue Technology Research Institute, Shanghai University of Medicine and Health Science, Shanghai, China.
Tao WangDepartment of Emergency Medicine, Shanghai Tongji Hospital, Tongji University School of Medicine, Shanghai, China.
Lufa ZhangInstitute of Healthy Yangtze River Delta, Shanghai Jiao Tong University, Shanghai, China.
Weimin GaoDepartment of Pharmacy, School of Pharmaceutical Sciences and Yunnan Key Laboratory of Pharmacology for Natural Products, Kunming Medical University, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The study aimed to measure time trends of inequalities of the geographical distribution of health facilities and workforce in Shanghai from 2010 to 2016 and used a spatial autocorrelation analysis method to precisely detect the priority areas for optimizing health resource reallocation in metropolises like Shanghai in developing countries. Methods: The study used secondary data from the Shanghai Health Statistical Yearbook and the Shanghai Statistical Yearbook from 2011 to 2017. Five indicators on health resources, namely, health institutions, beds, technicians, doctors, and nurses, were employed to quantitatively measure the healthcare resource in Shanghai. The Theil index and the Gini coefficient were applied to assess the global inequalities in the geographic distribution of these resources in Shanghai. Global and local spatial autocorrelation was performed using global Moran's index and local Moran's index to illustrate the spatial changing patterns and identify the priority areas for two types of healthcare resource allocation. Results: Shanghai's healthcare resources showed decreasing trends of inequalities at large from 2010 to 2016. However, there still existed an unchanged over-concentration distribution in healthcare facilities and workforce density among districts in Shanghai, especially for doctors at the municipal level and facility allocation at the rural level. Through spatial autocorrelation analysis, it was found that there exhibited a significant spatial autocorrelation in the density distribution of all resources, and some identified priority areas were detected for resource re-allocation policy planning. Conclusion: The study identified the existence of inequality in some healthcare resource allocations in Shanghai from 2010 to 2016. Hence, more detailed area-specific healthcare resource planning and distribution policies are required to balance the health workforce distribution at the municipal level and institution distribution at the rural level, and particular geographical areas (low-low and low-high cluster areas) should be focused on and fully considered across all the policies and regional cooperation to ensure health equality for municipal cities like Shanghai in developing countries.

Indexed as

Delivery of Health CareHealth WorkforceChinaHealth FacilitiesHumansLongitudinal Studiesdistributionhealthcare resourceinequalityspatial autocorrelation analysisTheil index

Identifiers

PMID37006575
PMCPMC10060654

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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.