scholarly journals Comparison of Inpatient Distribution among Different Medical Alliances in County Region: a Longitudinal Study on a healthcare reform in Rural China

2020 ◽  
Author(s):  
Yifan Ran ◽  
Hongxia Gao ◽  
Dan Han ◽  
Guilin Hou ◽  
Yingchun Chen ◽  
...  
Keyword(s):  
Health Inequality ◽  
Rural Areas ◽  
Rural China ◽  
Interrupted Time Series ◽  
T Test ◽  
Interrupted Time Series Analysis ◽  
Medical Institutions ◽  
Reform Period ◽  
Different Types ◽  
Township Hospitals

Abstract Background: China has launched the medical alliances (MAs) reform to drive the development of primary medical institutions and decrease health inequality in rural areas. Three different types of MAs were built to promote township hospitals in Y County. This study aims to evaluate the actual effect of China’s MAs reform in rural areas on inpatient distribution especially amongst different types of MAs.Methods：We obtain 2008–2015 claims data from the New Cooperative Medical Scheme (NCMS) in Y County, Hubei Province of China. We consider January 2008–December 2010 as the pre-reform period and January 2011–December 2015 as the post-reform period. We use independent sample t-test and single-group interrupted time series analysis (ITSA) to compare the number of inpatients per month in the three MAs, including three county and 10 township hospitals before and after the reform. We use paired t-test and multiple-group ITSA between seven township hospitals within MAs and seven township hospitals outside MAs.Results：The MAs reform in Y County increased the number of inpatients in county and township hospitals within MAs. After the reform, the number of inpatients per month in county hospitals had an upward trend, with a slope of 31.01 person/month (P < 0.000). Approximately 19.99 new inpatients were admitted to township hospitals monthly after the reform (P < 0.000). Furthermore, township hospitals within MAs had a substantial increase in the number of inpatients (10.45 new inpatients monthly) compared with those outside MAs. Conclusion: The MAs reform in Y County significantly improved the capability of medical institutions within MAs. After the reform, township hospitals within MAs had greater development advantages than those outside MAs. However, it also caused further imbalance in the county region, which contained the new health inequality risk.

scholarly journals Comparison of Inpatient Distribution among Different Medical Alliances in County Region: a Longitudinal Study on a healthcare reform in Rural China

2019 ◽  
Author(s):  
Yifan Ran ◽  
Hongxia Gao ◽  
Dan Han ◽  
Guilin Hou ◽  
Yingchun Chen ◽  
...  
Keyword(s):  
Health Inequality ◽  
Rural China ◽  
Interrupted Time Series ◽  
T Test ◽  
Interrupted Time Series Analysis ◽  
Multiple Group ◽  
Reform Period ◽  
Before And After ◽  
Cooperative Medical Scheme ◽  
Township Hospitals

Abstract Background: Three types of Medical Alliances (MAs) have been built in most county regions in China. These MAs are led by main three county hospitals to drive the development of township hospitals. This paper aims to evaluate the actual effect of China’s MAs reform in rural area on inpatient distribution especially among different categories of MAs. Methods：We obtained 2008-2015 claims data on enrolled residents from the New Cooperative Medical Scheme (NCMS) in Y County, Hubei Province of China. We considered January 2008–December 2010 as the pre-reform period and January 2011–December 2015 as the post-reform period. Independent sample t-test and single-group interrupted time series analysis (ITSA) were used to compare the number of inpatients per month in the three MAs including 3 county hospitals and 10 township hospitals before and after the reform. Paired t-test and multiple-group ITSA were used between township hospitals within MAs and outside MAs. Results：The MAs reform in Y County increased the number of inpatients and improved the service capacity of both county hospitals and township hospitals within MAs. After the reform, the number of inpatients per month in county hospitals had an upward trend, with a slope of 31.01 person/month (P < 0.000). Approximately 19.99 new inpatients were admitted to township hospitals monthly after the reform (P<0.000). Furthermore, township hospitals within MAs had a substantial increase in the number of inpatients (10.45 new inpatients monthly) compared with those outside MAs. Conclusion: The MAs reform in Y county effectively improved the capability of medical services in the county and decreased health inequality significantly. However, it also caused further imbalance in the county region in terms of the medical institutions among the three county hospitals and the different township hospitals, which contained the risk of new health inequality.

scholarly journals Can unsuccessful treatment in primary medical institutions influence patients’ choice? A retrospective cluster sample study from China

BMJ Open ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. e022304 ◽  
Author(s):  
Yadong Niu ◽  
Liang Zhang ◽  
Ting Ye ◽  
Yan Yan ◽  
Yan Zhang
Keyword(s):  
Rural China ◽  
Exact Matching ◽  
Cluster Sample ◽  
Unsuccessful Treatment ◽  
Medical Institutions ◽  
Registration Number ◽  
Potential Risks ◽  
Township Hospitals ◽  
High Level ◽  
Study Setting

ObjectiveChina has been attempting to control the patients’ choice of high-level medical institutions through series measures of first point of contact at primary medical institutions, but the outcome is considered poor. We aim to analyse whether unsuccessful treatment in primary medical institutions can lead to the patients’ choice of high-level medical institutions.DesignA retrospective cluster sample study.SettingThe study setting was in Macheng city, Hubei province.ParticipantsThe respondents are township–county (TC) patients (patients who first went to township hospitals and then county hospitals within 30 days for the same disease) who experienced unsuccessful treatment in primary medical institutions. A total of 2090 TC patients were screened out based on the New Rural Cooperative Medical System database in 2013.Main outcome measuresThe choice of patients between township hospitals (primary medical institutions) and county hospitals was observed. We compared TC patients’ ratio of choosing county hospitals (RoCC) before TC experience with after TC experience. Thereafter, we compared RoCC of TC patients and non-TC patients (patients who did not experience TC) based on coarsened exact matching.ResultsThe ratio of TC for outpatient in township hospitals is 0.68% and that of TC for inpatient in township hospitals is 3.37%. RoCC for TC disease increased from 20.8% to 35.5% (p<0.001), RoCC for other disease increased from 35% to 37.3% (p=0.01). TC patients had significantly higher RoCC than non-TC patients (p<0.001).ConclusionsPatients’ choice of high-level medical institutions is highly associated with the experience of unsuccessful treatment in primary medical institutions. Moreover, people likely select high-level medical institutions thereafter regardless of conditions in rural China. Unsuccessful treatment in primary medical institutions is inevitable for patients. Thus, additional measures should be considered in lowering the potential risks for patients when treatments fail.Trial registration numberChiCTR-OOR-14005563.

scholarly journals Impact of guidance publication on primary care prescribing rates of simple analgesia: an interrupted time series analysis in England

2020 ◽  
pp. bjgp20X714101
Author(s):  
Hannah Reichel ◽  
Rhian Stanbrook ◽  
Hans Johnson ◽  
William Proto ◽  
Mary Shantikumar ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Time Series Analysis ◽  
Health Inequality ◽  
Implementation Intentions ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Practice Level ◽  
Series Analysis ◽  
The Impact

Abstract Background: In March 2018, NHS England published guidance for Clinical Commissioning Groups (CCGs; NHS bodies that commission health services for local areas) to encourage implementation of policy to reduce primary care prescriptions of over-the-counter medications, including simple analgesia. Aims: To investigate: the impact of guidance publication on prescribing rates of simple analgesia (oral paracetamol, oral ibuprofen and topical non-steroidal anti-inflammatory drugs [NSAIDS]) in primary care; CCG implementation intentions; and whether it has created a health inequality based on socioeconomic status. Design and Setting: Interrupted time series analysis of primary care prescribing data in England. Methods: Practice-level prescribing data from January 2015 to March 2019 were obtained from NHS Digital. Interrupted time series analyses assessed the association of guidance publication with prescribing rates. The association between practice-level prescribing rates and Index of Multiple Deprivation score (a marker of socioeconomic deprivation) before and after publication was quantified using multivariable Poisson regression. Freedom of information requests were submitted to all CCGs. Results: There was a 4% reduction in prescribing of simple analgesia following guidance publication (adjusted incidence rate ratio [aIRR] 0.96, 95% CI 0.92-0.99, p=0.027), adjusting for underlying time trend and seasonality. Practice-level prescribing rates were greater in more deprived areas. There was considerable diversity across CCGs in whether or how they chose to implement the guidance. Conclusion: Guidance publication was associated with a small reduction in the prescribing rates of simple analgesia across England, without evidence of creating an additional health inequality.

scholarly journals Is There a Difference in the Utilisation of Inpatient Services Between Two Typical Payment Methods of Health Insurance? Evidence from the New Rural Cooperative Medical Scheme in China

2019 ◽  
Vol 16 (8) ◽  
pp. 1410 ◽  
Author(s):  
Dai Su ◽  
Yingchun Chen ◽  
Hongxia Gao ◽  
Haomiao Li ◽  
Jingjing Chang ◽  
...  
Keyword(s):  
Interrupted Time Series ◽  
P Value ◽  
Interrupted Time Series Analysis ◽  
Payment Systems ◽  
Payment Methods ◽  
Compensation Ratio ◽  
Inpatient Services ◽  
Cooperative Medical Scheme ◽  
The Difference ◽  
Township Hospitals

This study aimed to evaluate the effects of the differences between two typical payment methods for the new rural cooperative medical scheme (NRCMS) in China on the utilisation of inpatient services. Interrupted time-series analysis (ITSA) and propensity score matching (PSM) were used to measure the difference between two typical payment methods for the NRCMS with regard to the utilisation of inpatient services. After the reform was formally implemented, the level and slope difference after reform compared with pre-intervention (distribution of inpatients in county hospitals (DIC), distribution of inpatients in township hospitals (DIT) and the actual compensation ratio of inpatients (ARCI)) were not statistically significant. Kernel matching obtained better results in reducing the mean and median of the absolute standardised bias of covariates of appropriateness of admission (AA), appropriateness of disease (AD). The difference in AA and AD of the matched inpatients between two groups was −0.03 (p-value = 0.042, 95% CI: −0.08 to 0.02) and 0.21 (p-value < 0.001, 95% CI: −0.17 to 0.25), respectively. The differences in the utilisation of inpatient services may arise owing to the system designs of different payment methods for NRCMS in China. The causes of these differences can be used to guide inpatients to better use medical services, through the transformation and integration of payment systems.

scholarly journals Factors Associated With Hospitalization Costs of Coronary Heart Disease in Township Hospitals in Rural China

2019 ◽  
Vol 56 ◽  
pp. 004695801988695
Author(s):  
Qun Wang ◽  
Shuo Zhang ◽  
Yaling Wang ◽  
Xichun Zhang ◽  
Ying Zhang
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Rural Areas ◽  
Care Delivery ◽  
Rural China ◽  
Health Care Delivery System ◽  
Factors Associated ◽  
Hospitalization Costs ◽  
The Government ◽  
Township Hospitals

In large proportions of rural areas in many developing countries, health care delivery system is less developed and is less likely to be equipped to conduct sophisticated treatment for coronary heart disease (CHD) patients locally. This study aims at describing the status quo of and exploring factors associated with hospitalization costs of CHD in township hospitals where only drug therapy was available for CHD conditions. We collected data of inpatients with CHD from discharge records from 10 township hospitals in rural Liaoning from December 2013 to December 2014. We used multilevel linear regression to analyze the factors associated with CHD hospitalization costs. A total of 4635 inpatients were included in the analysis. We found that the average hospitalization costs were 6249.97 RMB (US$1012.47) with the average of 8.89 days of hospitalization in township hospitals in Liaoning. Age, gender, length of stay, the number of times of admissions, by which route was hospitalized, and type of CHD were all the factors significantly associated with hospitalization costs of CHD in township hospitals. The factors associated with hospitalization costs of CHD in township hospitals in rural China showed some different features from the existing studies. When the government designs the related policy, the policy makers need to consider the specific feature of hospitalization costs of CHD in township hospitals in rural areas.

scholarly journals The Association of Stay-at-Home Orders and the Spread of COVID-19 in Rural and Urban United States

2021 ◽  
Author(s):  
David H Jiang ◽  
Darius J Roy ◽  
Benjamin D Pollock ◽  
Nilay D Shah ◽  
Rozalina G McCoy
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Poisson Model ◽  
Interrupted Time Series ◽  
Mixed Effects ◽  
Limited Data ◽  
Interrupted Time Series Analysis ◽  
Rural And Urban ◽  
Intermediate Measure ◽  
At Home

Background: Throughout the spring of 2020, stay-at-home orders were imposed to curb the spread of COVID-19. There is limited data on the effectiveness of stay-at-home orders, particularly in rural as compared to urban areas. Objective: To examine the association between stay-at-home order implementation and the incidence of COVID-19 in rural vs. urban counties. Design: Interrupted time series analysis using a mixed effects zero-inflated Poisson model. Participants: 3,142 U.S. counties. Interventions: Stay-at-home orders. Main Measures: COVID-19 daily incidence (primary) and mobility (secondary and intermediate measure of stay-at-home effectiveness) Key Results: Stay-at-home orders were implemented later (median March 30 vs. March 28) and were shorter (median 35 vs. 54 days) in rural than urban counties. Indoor mobility was, on average, 2.6-6.9% higher in rural than urban counties both during and after stay-at-home orders. Compared to the baseline (pre-stay-at-home) period, the number of new COVID-19 cases increased under stay-at-home by IRR 1.60 (95% CI, 1.57-1.64) in rural and 1.36 (95% CI, 1.30-1.42) in urban counties. For each day under stay-at-home orders, the number of new cases changed by a factor of 0.982 (95% CI 0.981-0.982) in rural and 0.952 (95% CI, 0.951-0.953) in urban counties compared to prior to stay-at-home. Each day after stay-at-home orders expired, the number of new cases changed by a factor of 0.995 (95% CI, 0.994-0.995) in rural and 0.997 (95% CI, 0.995-0.999) in urban counties compared to prior to stay-at-home. Conclusion: Stay-at-home orders decreased mobility and slowed the spread of COVID-19, but less effectively in rural than in urban counties. This necessitates a critical reevaluation of how stay-at-home orders are designed, communicated, and implemented in rural areas.

An Analysis of Restraints on Effective Demand for Loans in Rural China

2018 ◽  
Vol 6 (8) ◽  
pp. 107
Author(s):  
Wenjie Ma ◽  
Minxin He ◽  
Xinyu Zhong ◽  
Shengsong Huang
Keyword(s):  
Economic Growth ◽  
Migrant Workers ◽  
Rural Areas ◽  
Financial Services ◽  
Rural China ◽  
Strong Support ◽  
Effective Demand ◽  
Second Child ◽  
Factors Influencing ◽  
First Choice

China’s overall economic growth is, to a great extent, hindered by the lack of economic growth in rural areas. Based on data from the Thousand-Village Survey (2015) of 31 provinces conducted by Shanghai University of Finance and Economics, we conduct this empirical study to analyze the current state of rural financial services and the factors influencing effective demand for loans in rural China. Looking at the demand side, in 2014, only 13.91% farmers had loans, and only 15.53% of them made financial institutions their first choice when they needed loans. Clearly, there is still much to do with regard to inclusive finance. From the perspective of the supply side, only 43.86% of dispersed loans can be categorized as productive loans, further reflecting that the financial services industry does not provide strong support for rural economic growth. Further study shows that the main factors influencing effective demand for productive loans are the population age structure and the rate at which migrant workers return home. Therefore, the "Second-Child" policy and policies that encourage migrant workers to go back home to start businesses are of vital importance in order to raise effective financial demand in rural China.

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