Health Insurance and Long-Term Care Services for the Disabled Elderly in China: Based on CHARLS Data.

CHARLS data LTC formal care health insurance informal care long-term care the disabled elderly

Journal

Risk management and healthcare policy
ISSN: 1179-1594
Titre abrégé: Risk Manag Healthc Policy
Pays: England
ID NLM: 101566264

Informations de publication

Date de publication:
2020
Historique:
received: 09 10 2019
accepted: 11 02 2020
entrez: 13 3 2020
pubmed: 13 3 2020
medline: 13 3 2020
Statut: epublish

Résumé

This paper aimed to explore the relationship between the different factors, especially health insurance, and the availability of long-term care (LTC) services, among the disabled elderly. Based on the data of China Health and Retirement Longitudinal Study (CHARLS), the logistic regression model was utilized to evaluate the influence of the different factors, especially health insurance, on the availability of long-term care services. Our findings show some interesting results. Firstly, the findings suggest that informal long-term care (LTC) services for elderly persons with disabilities heavily depend on a family member from different health insurance groups. About 80.733% of the disabled elderly depend on a family member as their primary caregivers. Secondly, other influence factors such as income and area of residence were also significantly related to the availability of long-term rental services. Thirdly, Health insurance is a very important factor influencing the availability of Long-term care services both in urban and rural areas (p<0.001) but Income is the most interesting variable. Based on our results, the growth and integration of formal long-term care (LTC) services should be facilitated. Firstly, policymakers can encourage formal long-term care (LTC) services from a variety of sources to work together to increase overall supply capability. Secondly, the long-term living security needs of people who do not have health insurance should be regulated through subsidies according to the economic status.

Identifiants

pubmed: 32161509
doi: 10.2147/RMHP.S233949
pii: 233949
pmc: PMC7051854
doi:

Types de publication

Journal Article

Langues

eng

Pagination

155-162

Informations de copyright

© 2020 Chen et al.

Déclaration de conflit d'intérêts

The authors report no conflicts of interest in this work.

Références

Lancet. 2015 Feb 7;385(9967):563-75
pubmed: 25468158
Int J Environ Res Public Health. 2019 Apr 03;16(7):
pubmed: 30987107
Int J Environ Res Public Health. 2019 Aug 01;16(15):
pubmed: 31374880
J Med Econ. 2019 Jun;22(6):605-611
pubmed: 30913934
J Aging Soc Policy. 2013;25(2):181-96
pubmed: 23570510
Healthcare (Basel). 2019 Aug 21;7(3):
pubmed: 31438602
BMC Public Health. 2013 Apr 08;13:313
pubmed: 23566211
Arch Gerontol Geriatr. 2016 Nov-Dec;67:21-7
pubmed: 27395377
J Am Med Dir Assoc. 2009 Sep;10(7):472-7
pubmed: 19716063
Healthcare (Basel). 2019 Dec 03;7(4):
pubmed: 31816957
Can J Aging. 2015 Sep;34(3):290-304
pubmed: 26300189
Gerontologist. 2001 Jun;41(3):293-304
pubmed: 11405425

Auteurs

Linhong Chen (L)

Department of Applied Statistics, School of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067, People's Republic of China.
Department of Public Administration, School of Public Administration, Sichuan University, Chengdu 610065, People's Republic of China.

Xiaolu Zhang (X)

Department of Trade Economics, School of Economics, Chongqing Technology and Business University, Chongqing 400067, People's Republic of China.

Xiaocang Xu (X)

Department of Economics, Research Center for Economy of Upper Reaches of the Yangtse River/School of Economics, Chongqing Technology and Business University, Chongqing 400067, People's Republic of China.

Classifications MeSH