Evidence map›Paper›PMID 36578006›Full record

ArticleHealth research policy and systems2022

Effects of incentive-based population policies on sustainability of China's recent maternity insurance system reform: a system dynamics simulation.

Xiaotian Zhang, Xiaoyun Liu, Wanxin Wang, Lulin Zhou, Yang Wang, Mingyue Li

Abstract read
In one paragraph

Article in Health research policy and systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

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3citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

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

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xiaotian ZhangChina Centre for Health Development Studies, Peking University, Beijing, 100191, People's Republic of China. xiaotian_zhang@hsc.pku.edu.cn.ORCID http://orcid.org/0000-0002-2813-9237
Xiaoyun LiuChina Centre for Health Development Studies, Peking University, Beijing, 100191, People's Republic of China.
Wanxin WangTunbridge Wells Hospital, Tonbridge Rd, Royal Tunbridge Wells, TN2 4QJ, United Kingdom.
Lulin ZhouSchool of Management, Hospital Management and Health Policy Research, Centre for Medical Insurance, Jiangsu University, Jiangsu, People's Republic of China.
Yang WangChina Centre for Health Development Studies, Peking University, Beijing, 100191, People's Republic of China.
Mingyue LiChina Centre for Health Development Studies, Peking University, Beijing, 100191, People's Republic of China.

Funding

China Postdoctoral Science Foundation 2022M710247National Social Science Foundation of China 19FGLB006
6 · The paper itself

Abstract

backgroundThis paper seeks to assess the sustainability of the reformed maternity insurance system and the extent to which China's current maternity insurance system can support different levels of fertility incentives in the future. Our findings will serve as a reference for countries in a similar demographic predicament and those about to face it.

methodsThis study used a combination of qualitative and quantitative methods. In the qualitative assessment, we used a grounded theory model to generalize the factors influencing the sustainability of maternity insurance funds. For the quantitative analysis, we used a novel and comprehensive system dynamics model to visualize the status of the combined operation of maternity and health insurance. Data are mainly derived from the historical data of the Statistical Yearbook of Jiangsu Province and the National Bureau of Statistics of China.

resultsIn the short term, fertility incentive payments can be set to motivate people to have children. It is therefore recommended that when the scope of the fertility incentive policy is limited to two children, and an average amount above RMB 10 000 could be set, it would be prudent to set the amount at a level not exceeding RMB 10 000 when the scope of the fertility incentive policy is for all newborns. In the long term, a system of incentives for childbirth should be built from education policy, house price regulation, tax relief and childcare services.

conclusionOur research not only highlights the significance of improving the resilience of maternity insurance by combining maternity insurance and health insurance funds, but also suggests a way to economically incentivize beneficiaries to have children so as to mitigate the decline in China's birth rate and cope with the crisis of an ageing population.

Indexed as

InsuranceMotivationChildChinaDemographyDeveloping CountriesFemaleHumansInfant, NewbornPopulation DynamicsPregnancyPublic PolicyEconomic incentivesFertility rateGrounded theoryRisk resistanceSustainable developmentSystem dynamics model

Identifiers

PMID36578006
PMCPMC9797110

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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.