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Improving the performance of social health insurance system through increasing outpatient expenditure reimbursement ratio: a quasi-experimental evaluation study from rural China

Overview of attention for article published in International Journal for Equity in Health, June 2018
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Title
Improving the performance of social health insurance system through increasing outpatient expenditure reimbursement ratio: a quasi-experimental evaluation study from rural China
Published in
International Journal for Equity in Health, June 2018
DOI 10.1186/s12939-018-0799-8
Pubmed ID
Authors

Yudong Miao, Jianqin Gu, Liang Zhang, Ruibo He, Sandeep Sandeep, Jian Wu

Abstract

China has set up a universal coverage social health insurance system since the 2009 healthcare reform. Due to the inadequate funds, the social health insurance system reimbursed the inpatient expenditures with much higher ratio than outpatient expenditure. The gap in reimbursement ratios resulted in a rapid rising hospitalization rate but poor health outcomes among the Chinese population. A redistribution of social health insurance funds has become one of the main challenges for the performance of Social Health Insurance. Two comparable counties, Dangyang County and Zhijiang County, in Hubei Province of China, were sampled as the intervention group and the control group, respectively. The Social Health Insurance Management Department of the intervention group budgeted 600 yuan per capita per year to the patients with 3rd stage hypertension to cover their outpatient expenditures. The outpatient spending in the control group were paid out-of-pocket. The inpatient expenditures reimbursement policies in both groups were not changed. Besides, the Social Health Insurance Management Department of the intervention group budgeted 100 yuan per patient per year to township physicians and hospitals to provide health management services for the patients. While, the health management services in the control group were still provided by health workers. A Propensity Score Matching model and Difference-in-differences model were used to estimate the net effects of the intervention in dimensions of medical services utilization, medical expenditures, SHI reimbursement, and health outcomes. One thousand, six hundred and seventy three pairs of patients were taken as valid subjects to conduct Difference-in-differences estimation after the Propensity Score Matching. The net intervention effect is to increase outpatient frequency by 3.3 (81.0%) times (P < 0.05), to decrease hospitalization frequency by 0.075 (- 60.0%) times (P < 0.05), and to increase the per capita total medical service utilization frequency by 3.225 (76.8%) times (P < 0.05). The per capita total medical expenditure decreased 394.2 (- 27.7%) yuan. The SHI reimbursed 90.3 yuan more per capita for the outpatient spending, but the per capita inpatient expenditure reimbursement and per capita total medical expenditure reimbursement decreased significantly by 282.6 (- 44.0%) yuan and 192.3 (- 28.5%) yuan, respectively (P < 0.05). The intervention reduced the per capita inpatient out-of-pocket expenditure and the per capita total out-of-pocket expenditure by 192.8 (- 36.7%) yuan and 201.9 (- 29.9%) yuan, respectively (P < 0.05). The intervention significantly decreased the diastolic blood pressure of the intervention group by 2.9 mmHg (P < 0.05) but had no significant impact on the systolic blood pressure (- 7.9 mmHg, P > 0.05). For China and countries attempting to establish a universal coverage SHI with inadequate funds, inpatient services were expensive but might not produce good health outcomes. Outpatient care for patients with chronic diseases should be fundamental, and outpatient expenditures should be reimbursed with a higher ratio.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 17%
Student > Ph. D. Student 10 16%
Student > Bachelor 5 8%
Researcher 4 6%
Professor > Associate Professor 3 5%
Other 10 16%
Unknown 20 32%
Readers by discipline Count As %
Nursing and Health Professions 10 16%
Medicine and Dentistry 9 14%
Economics, Econometrics and Finance 8 13%
Business, Management and Accounting 6 10%
Linguistics 1 2%
Other 6 10%
Unknown 23 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 June 2018.
All research outputs
#15,486,645
of 23,092,602 outputs
Outputs from International Journal for Equity in Health
#1,557
of 1,933 outputs
Outputs of similar age
#209,043
of 328,981 outputs
Outputs of similar age from International Journal for Equity in Health
#44
of 51 outputs
Altmetric has tracked 23,092,602 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,933 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.4. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 328,981 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.