Evidence map›Paper›PMID 27846902›Full record

ArticleInternational journal for equity in health2016

Effects of asymmetric medical insurance subsidy on hospitals competition under non-price regulation.

Chan Wang, Pu-Yan Nie

Abstract read
In one paragraph

Article in International journal for equity in health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Success of Big Infectious Disease Reimbursement Policy in China.Inquiry : a journal of medical care organization, provision and financing
    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

2 authors.

Chan WangInstitute of Industrial Economics, Jinan University, Guangzhou, 510632, People's Republic of China. wangchan0512@163.com.
Pu-Yan NieGuangdong University of Finance & Economics, Guangzhou, 510320, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPoor medical care and high fees are two major problems in the world health care system. As a result, health care insurance system reform is a major issue in developing countries, such as China. Governments should take the effect of health care insurance system reform on the competition of hospitals into account when they practice a reform. This article aims to capture the influences of asymmetric medical insurance subsidy and the importance of medical quality to patients on hospitals competition under non-price regulation.

methodsWe establish a three-stage duopoly model with quantity and quality competition. In the model, qualitative difference and asymmetric medical insurance subsidy among hospitals are considered. The government decides subsidy (or reimbursement) ratios in the first stage. Hospitals choose the quality in the second stage and then support the quantity in the third stage. We obtain our conclusions by mathematical model analyses and all the results are achieved by backward induction.

resultsThe importance of medical quality to patients has stronger influence on the small hospital, while subsidy has greater effect on the large hospital. Meanwhile, the importance of medical quality to patients strengthens competition, but subsidy effect weakens it. Besides, subsidy ratios difference affects the relationship between subsidy and hospital competition. Furthermore, we capture the optimal reimbursement ratio based on social welfare maximization. More importantly, this paper finds that the higher management efficiency of the medical insurance investment funds is, the higher the best subsidy ratio is.

conclusionsThis paper states that subsidy is a two-edged sword. On one hand, subsidy stimulates medical demand. On the other hand, subsidy raises price and inhibits hospital competition. Therefore, government must set an appropriate subsidy ratio difference between large and small hospitals to maximize the total social welfare. For a developing country with limited medical resources and great difference in hospitals such as China, adjusting the reimbursement ratios between different level hospitals and increasing medical quality are two reasonable methods for the sustainable development of its health system.

Indexed as

Economics, HospitalChinaDelivery of Health CareFees and ChargesGovernmentHealthcare FinancingHealth Care ReformHospitalsHumansInsurance, HealthMedical AssistanceNational Health ProgramsGame theoryManagement efficiencyMedical insurance subsidyQuality competition

Identifiers

PMID27846902
PMCPMC5109695

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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.