Evidence map›Paper›PMID 37089514›Full record

ArticleFrontiers in public health2023

Perspectives and evaluation on the effect of financial burden relief of medical insurance for people with catastrophic diseases and its influencing factors.

Pengfei Guo, Yinghua Qin, Rizhen Wang, Jiacheng Li, Jingjing Liu, Kexin Wang, Ye Li, Zheng Kang, Yanhua Hao, Huan Liu and 4 more

Open access · goldAbstract 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
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

14 authors at 1 institution in 1 country.

Pengfei GuoDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Yinghua QinDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Rizhen WangDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Jiacheng LiDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Jingjing LiuDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Kexin WangDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Ye LiDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Zheng KangDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Yanhua HaoDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Huan LiuDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Hong SunDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Yu CuiDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Linghan ShanDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Qunhong WuDepartment of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang, China.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Catastrophic disease sufferers face a heavy financial burden and are more likely to fall victim to the "illness-poverty-illness" cycle. Deeper reform of the medical insurance system is urgently required to alleviate the financial burden of individuals with catastrophic diseases. Methods: Data were obtained from a cross-sectional questionnaire survey conducted in Heilongjiang in 2021, and logistic regression and restricted cubic spline model was used to predict the core factors related to medical insurance that alleviate the financial burden of people with catastrophic diseases. Results: Overall, 997 (50.92%) medical insurance-related professionals negatively viewed financial burden relief for people with catastrophic diseases. Factors influencing its effectiveness in relieving the financial burden were: whether or not effective control of omissions from medical insurance coverage (OR = 4.04), fund supervision (OR = 2.47) and degree of participation of stakeholders (OR = 1.91). Besides, the reimbursement standards and the regional and population benefit package gap also played a role. The likelihood of financial burden relief increased by 21 percentage points for each unit increase in the level of stakeholder discourse power in reform. Conclusion: China's current medical insurance policies have not yet fully addressed the needs of vulnerable populations, especially the need to reduce their financial burden continuously. Future reform should focus on addressing core issues by reducing the uninsured, enhancing the width and depth of medical insurance coverage, improving the level and capacity of medical insurance governance that provides more discourse power for the vulnerable population, and building a more responsive and participatory medical insurance governance system.

Indexed as

Health ExpendituresInsurance, HealthCross-Sectional StudiesFinancial StressHumansPovertyChinafinancial burdeninfluencing factorsmedical insurancepeople with catastrophic diseases

Identifiers

PMID37089514
PMCPMC10117759
OpenAlexW4362671745

What OpenQuestion holds

Textmetadata
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.