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Effect of integrated urban and rural residents medical insurance on the utilisation of medical services by residents in China: a propensity score matching with difference-in-differences regression approach

OBJECTIVES: In this study, we aim to evaluate the effect of urban and rural resident medical insurance scheme (URRMI) on the utilisation of medical services by urban and rural residents in the four pilot provinces. SETTING AND PARTICIPANTS: The sample used in this study is 13 305 individuals, includ...

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Autores principales: Su, Dai, Chen, Ying-chun, Gao, Hong-xia, Li, Hao-miao, Chang, Jing-jing, Jiang, Di, Hu, Xiao-mei, Lei, Shi-han, Tan, Min, Chen, Zhi-fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377539/
https://www.ncbi.nlm.nih.gov/pubmed/30782944
http://dx.doi.org/10.1136/bmjopen-2018-026408
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author Su, Dai
Chen, Ying-chun
Gao, Hong-xia
Li, Hao-miao
Chang, Jing-jing
Jiang, Di
Hu, Xiao-mei
Lei, Shi-han
Tan, Min
Chen, Zhi-fang
author_facet Su, Dai
Chen, Ying-chun
Gao, Hong-xia
Li, Hao-miao
Chang, Jing-jing
Jiang, Di
Hu, Xiao-mei
Lei, Shi-han
Tan, Min
Chen, Zhi-fang
author_sort Su, Dai
collection PubMed
description OBJECTIVES: In this study, we aim to evaluate the effect of urban and rural resident medical insurance scheme (URRMI) on the utilisation of medical services by urban and rural residents in the four pilot provinces. SETTING AND PARTICIPANTS: The sample used in this study is 13 305 individuals, including 2620 in the treatment group and 10 685 in the control group, from the 2011 and 2015 surveys of China Health and Retirement Longitudinal Study. OUTCOME MEASURES: Propensity score matching and difference-in-differences regression approach (PSM-DID) is used in the study. First, we match the baseline data by using kernel matching. Then, the average treatment effect of the four outcome variables are analysed by using the DID model. Finally, the robustness of the PSM-DID estimation is tested by simple model and radius matching. RESULTS: Kernel matching have improved the overall balance after matching. The URRMI policy has significantly reduced the need-but-not outpatient care and significantly increased outpatient care cost and inpatient care cost for rural residents, with DID value of −0.271, 0.090 and 0.256, respectively. After robustness test, the DID competing results of four outcome variables are consistent. CONCLUSIONS: URRMI has a limited effect on the utilisation of medical and health services by all residents, but the effect on rural residents is obvious. The government should establish a unified or income-matching payment standard to prevent, control the use of medical insurance funds and increase its efforts to implement URRMI integration in more regions to improve overall fundraising levels.
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spelling pubmed-63775392019-03-05 Effect of integrated urban and rural residents medical insurance on the utilisation of medical services by residents in China: a propensity score matching with difference-in-differences regression approach Su, Dai Chen, Ying-chun Gao, Hong-xia Li, Hao-miao Chang, Jing-jing Jiang, Di Hu, Xiao-mei Lei, Shi-han Tan, Min Chen, Zhi-fang BMJ Open Health Services Research OBJECTIVES: In this study, we aim to evaluate the effect of urban and rural resident medical insurance scheme (URRMI) on the utilisation of medical services by urban and rural residents in the four pilot provinces. SETTING AND PARTICIPANTS: The sample used in this study is 13 305 individuals, including 2620 in the treatment group and 10 685 in the control group, from the 2011 and 2015 surveys of China Health and Retirement Longitudinal Study. OUTCOME MEASURES: Propensity score matching and difference-in-differences regression approach (PSM-DID) is used in the study. First, we match the baseline data by using kernel matching. Then, the average treatment effect of the four outcome variables are analysed by using the DID model. Finally, the robustness of the PSM-DID estimation is tested by simple model and radius matching. RESULTS: Kernel matching have improved the overall balance after matching. The URRMI policy has significantly reduced the need-but-not outpatient care and significantly increased outpatient care cost and inpatient care cost for rural residents, with DID value of −0.271, 0.090 and 0.256, respectively. After robustness test, the DID competing results of four outcome variables are consistent. CONCLUSIONS: URRMI has a limited effect on the utilisation of medical and health services by all residents, but the effect on rural residents is obvious. The government should establish a unified or income-matching payment standard to prevent, control the use of medical insurance funds and increase its efforts to implement URRMI integration in more regions to improve overall fundraising levels. BMJ Publishing Group 2019-02-06 /pmc/articles/PMC6377539/ /pubmed/30782944 http://dx.doi.org/10.1136/bmjopen-2018-026408 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Health Services Research
Su, Dai
Chen, Ying-chun
Gao, Hong-xia
Li, Hao-miao
Chang, Jing-jing
Jiang, Di
Hu, Xiao-mei
Lei, Shi-han
Tan, Min
Chen, Zhi-fang
Effect of integrated urban and rural residents medical insurance on the utilisation of medical services by residents in China: a propensity score matching with difference-in-differences regression approach
title Effect of integrated urban and rural residents medical insurance on the utilisation of medical services by residents in China: a propensity score matching with difference-in-differences regression approach
title_full Effect of integrated urban and rural residents medical insurance on the utilisation of medical services by residents in China: a propensity score matching with difference-in-differences regression approach
title_fullStr Effect of integrated urban and rural residents medical insurance on the utilisation of medical services by residents in China: a propensity score matching with difference-in-differences regression approach
title_full_unstemmed Effect of integrated urban and rural residents medical insurance on the utilisation of medical services by residents in China: a propensity score matching with difference-in-differences regression approach
title_short Effect of integrated urban and rural residents medical insurance on the utilisation of medical services by residents in China: a propensity score matching with difference-in-differences regression approach
title_sort effect of integrated urban and rural residents medical insurance on the utilisation of medical services by residents in china: a propensity score matching with difference-in-differences regression approach
topic Health Services Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377539/
https://www.ncbi.nlm.nih.gov/pubmed/30782944
http://dx.doi.org/10.1136/bmjopen-2018-026408
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