Efficiency and scale effect of county public hospitals in Shandong Province, China: a cross-sectional study

Coverage of influenza vaccination and influencing factors among healthcare workers in Shandong Province, China, 2021-2022

Healthcare workers (HCWs) are at increased risk of exposure to the influenza virus in their daily clinical and disease prevention activities, making them a high-risk group for influenza infection. However, the vaccination rate among HCWs has always been low. This study investigated influenza vaccination uptake and willingness among HCWs in the context of the COVID-19 pandemic. The analysis revealed that the influenza vaccination uptake among HCWs was 67.5%, with 79.6% willing to receive the influenza vaccine in 2022/2023 A significant majority (92.7%) agreed that the COVID-19 pandemic increased their willingness to receive the influenza vaccine, and 94.8% agreed with the necessity of receiving the influenza vaccine even after COVID-19 vaccination. Binary logistic regression model identified key factors that influence vaccination intentions. HCWs who perceived a high risk of influenza and its threat to health, found vaccination convenient, and believed in the safety of the influenza vaccine were more likely to be vaccinated. Conversely, the high price of the influenza vaccine was a barrier, whereas those who considered the vaccine affordable were more likely to be vaccinated. Although Changchun Changsheng vaccine incident (The Changchun Changsheng Biotechnology Company was found to have violated good manufacturing practices in 2018, leading to widespread distribution of subpotent vaccines in China.) may not significantly impact the vaccination uptake among healthcare workers, some HCWs still harbor doubts about vaccine safety, which remains a key reason for vaccine hesitancy. This study emphasizes the importance of the strict monitoring and management of vaccines, conducting clinical studies to support vaccine safety, and implementing free influenza vaccine policies, workplace vaccination requirements, and organized mass vaccinations. Educational efforts to increase HCWs' understanding of influenza and influenza vaccines are crucial to increasing vaccination uptake. Furthermore, implementing comprehensive intervention measures is essential to effectively improve the influenza vaccination uptake.

Resource allocation efficiency in 68 county-level traditional Chinese medicine hospitals in China: a data envelopment analysis

OBJECTIVE

Analysing and evaluating how efficiently health resources are allocated to county-level Traditional Chinese Medicine (TCM) hospitals in Zhejiang Province, this study aims to provide empirical evidence for improving operational efficiency and optimising resource allocation in these hospitals.

DESIGN AND SETTING

The study employed a three-stage Data Envelopment Analysis (DEA) model to assess efficiency, using data from 68 county-level TCM hospitals. Four input and five output variables related to TCM services were selected for the analysis.

RESULTS

The first-stage DEA results indicated that in 2022, the technical efficiency (TE) of TCM hospitals in Zhejiang Province was 0.788, the pure technical efficiency (PTE) was 0.876 and the scale efficiency (SE) was 0.903. The classification of hospitals into four groups based on the bed size showed statistically significant differences in returns to scale (p<0.001). The Stochastic Frontier Analysis regression results were significant at the 1% level across four regressions, showing that environmental variables such as per capita GDP, population density and the number of hospitals impacted efficiency. In the third stage DEA, after adjusting the input variables, the TE, PTE and SE improved to 0.809, 0.833 and 0.917, respectively. The adjusted mean TE rankings by region were West (0.860) > East (0.844) > South (0.805) > North (0.796) > Central (0.731).

CONCLUSION

There is an imbalance between the inputs and outputs of county-level TCM hospitals. Each region must consider factors such as the local economy, population and medical service levels, along with the specific development characteristics of hospitals, to reasonably determine the scale of county-level TCM hospital construction. Emphasis should be placed on improving hospital management and technical capabilities, coordinating regional development, promoting the rational allocation and efficient use of TCM resources and enhancing the efficiency of resource allocation in county-level TCM hospitals.

Applications of data envelopment analysis in acute care hospitals: a systematic literature review, 1984-2022

This study reviews scholarly publications on data envelopment analysis (DEA) studies on acute care hospital (ACH) efficiency published between 1984 and 2022 in scholarly peer-reviewed journals. We employ systematic literature review (SLR) method to identify and analyze pertinent past research using predetermined steps. The SLR offers a comprehensive resource that meticulously analyzes DEA methodology for practitioners and researchers focusing on ACH efficiency measurement. The articles reviewed in the SLR are analyzed and synthesized based on the nature of the DEA modelling process and the key findings from the DEA models. The key findings from the DEA models are presented under the following sections: effects of different ownership structures; impacts of specific healthcare reforms or other policy interventions; international and multi-state comparisons; effects of changes in competitive environment; impacts of new technology implementations; effects of hospital location; impacts of quality management interventions; impact of COVID-19 on hospital performance; impact of teaching status, and impact of merger. Furthermore, the nature of DEA modelling process focuses on use of sensitivity analysis; choice of inputs and outputs; comparison with Stochastic Frontier Analysis; use of congestion analysis; use of bootstrapping; imposition of weight restrictions; use of DEA window analysis; and exogenous factors. The findings demonstrate that, despite several innovative DEA extensions and hospital applications, over half of the research used the conventional DEA models. The findings also show that the most often used inputs in the DEA models were labor-oriented inputs and hospital beds, whereas the most frequently used outputs were outpatient visits, followed by surgeries, admissions, and inpatient days. Further research on the impact of healthcare reforms and health information technology (HIT) on hospital performance is required, given the number of reforms being implemented in many countries and the role HIT plays in enhancing care quality and lowering costs. We conclude by offering several new research directions for future studies.

Effects of medical consortium policy on health services: an interrupted time-series analysis in Sanming, China

Objectives

China has implemented reforms to enhance the operational efficiency of three-level medical services through medical consortiums (MCs). This study evaluated the impact of MCs reform on health services in Sanming, China.

Methods

An interrupted time-series analysis (ITSA) was conducted to assess the impact of MCs on changes in health service levels and trends across the overall situation of MCs and different institutional types within MCs, including county hospitals and grassroots medical institutions. The evaluation focused on various indicators such as outpatient and emergency visits, inpatients, average length of stay, occupancy rate of hospital beds, and hospital bed turnover times. Monthly data were collected from April 2015 to June 2019 through reports on the Sanming Municipal Health Commission website and the Sanming public hospital management monitoring platform.

Results

After the intervention of MCs reform, a significant increase was observed in the total number of inpatients (β3 = 174.28, p < 0.05). However, no statistically significant change was observed in the total number of outpatient and emergency visits (β3 = 155.82, p = 0.91). Additionally, the implementation of MCs reform led to an amplification in service volumes provided by county hospitals, with significant increases in the number of outpatient and emergency visits (β3 = 1376.54, p < 0.05) and an upward trend in the number of inpatients (β3 = 98.87, p < 0.01). However, no significant changes were observed under the MCs policy for grassroots medical institutions regarding the number of outpatient and emergency visits (β3 = -1220.72, p = 0.22) and number of inpatients (β3 = 75.42, p = 0.09).

Conclusion

The Sanming MCs reform has achieved some progress in augmenting service volumes. Nevertheless, it has not led to an increase in service volumes at the grassroots medical institutions. There persists an insufficiency in the efficiency of services and a need for further improvement in primary healthcare. To address these concerns, it is imperative for county hospitals to offer targeted assistance that can enhance motivation among grassroots medical institutions. Besides the MCs should explore initiatives, including improved management of medical equipment, allocation of funding, and personnel resources.

Configurational Paths to Higher Efficiency in County Hospital: Evidence From Qualitative Comparative Analysis

Background

The efficient operation of county-level medical institutions is a significant guarantee in constructing Chinese rural tertiary care service networks. However, it is still unclear how to increase the efficiency of county hospitals under the interaction of multiple factors. In this study, 35 county general hospitals in China were selected to explore the configuration paths of county hospitals' high and poor efficiency status under the Environment-Structure-Behavior (ESB) framework and provide evidence-based recommendations for measures to enhance its efficiency.

Methods

Data envelopment analysis with the bootstrapping procedure was used to estimate the technical efficiency value of case hospitals. A fuzzy-set qualitative comparative analysis approach was carried out to explore the configuration of conditions to the efficiency status.

Results

Antecedent configurations affecting the efficiency status of county hospitals were identified based on the ESB analytical framework. Three high-efficiency configuration paths can be summarized as structural optimization, capacity enhancement, and government support. Another three types of paths, namely insufficient capacity, aggressive expansion, and poor decision-making, will lead to inefficient configurations.

Conclusion

Qualitative comparative analysis is necessary when exploring complex causality. The efficiency situation of county hospitals results from a combination of influencing factors instead of the effect of a single one. There is no solitary configuration for high efficiency that applies to all healthcare units. Any measures aimed at efficiency promotion should be discussed within the framework of a case-specific analysis.

Do China rural traditional Chinese medicine hospitals provide efficient healthcare to the people? Empirical study from 2013 to 2018 using data envelopment analysis

Rural traditional Chinese medicine hospitals bear responsibilities of providing efficient medical services for rural residents. Efficiency assessments have previously been conducted in single province. This study aimed to investigate the technical efficiency of rural traditional Chinese medicine hospitals across China from 2013 to 2018, with the application of super slack-based measure data envelopment analysis. In total, 1219 hospitals covering 28 provinces were included as sample hospitals. Overall, hospitals performed technically less efficiently but presented with an increasing trend. Redundancy and insufficiency existed in health input and output variables, respectively. Notably, optimizing input variables was found to make more substantial improvement in hospital efficiency. Provincial and regional disparities were also observed in hospital efficiency. In conclusion, rural traditional Chinese medicine hospitals have experienced slight improvement in efficiency during the study period, however, their efficiency was still in a relatively low level with ample room for improvement. Meanwhile, regional coordinated development should also be noticed in this process.

The efficiency of provincial government health care expenditure after China's new health care reform

OBJECTIVE

We aim to estimate the total factor productivity and analyze factors related to the Chinese government's health care expenditure in each of its provinces after its implementation of new health care reform in the period after 2009.

MATERIALS AND METHODS

We use the Malmquist DEA model to measure efficiency and apply the Tobit regression to explore factors that influence the efficiency of government health care expenditure. Data are taken from the China statistics yearbook (2004-2020).

RESULTS

We find that the average TFP of China's 31 provincial health care expenditure was lower than 1 in the period 2009-2019. We note that the average TFP was much higher after new health care reform was implemented, and note this in the eastern, central and western regions. But per capita GDP, population density and new health care reform implementation are found to have a statistically significant impact on the technical efficiency of the provincial government's health care expenditure (P<0.05); meanwhile, region, education, urbanization and per capita provincial government health care expenditure are not found to have a statistically significant impact.

CONCLUSION

Although the implementation of the new medical reform has improved the efficiency of the government's health expenditure, it is remains low in 31 provinces in China. In addition, the government should consider per capita GDP, population density and other factors when coordinating the allocation of health care input.

SIGNIFICANCE

This study systematically analyzes the efficiency and influencing factors of the Chinese government's health expenditure after it introduced new health care reforms. The results show that China's new medical reform will help to improve the government's health expenditure. The Chinese government can continue to adhere to the new medical reform policy, and should pay attention to demographic and economic factors when implementing the policy.

Determinants of hospital inefficiency. The case of Polish county hospitals

Local hospitals play a crucial role in the healthcare system. In this study, the efficiency of Polish county hospitals is assessed by considering characteristics of hospitals that may determine their performance, such as the form of ownership, size, and staff structure. The main goal was to analyze the effect of three possible determinants on efficiency: ownership, the presence of an Emergency Department, and the presence of an Intensive Care Unit. The study covered different subgroups of hospitals and different approaches of inputs and outputs. An input-oriented radial super-efficiency DEA model under variable returns to scale was used for the efficiency analysis, and then differences between distributions of efficient and inefficient units were evaluated using a Chi-square test. A Kruskal-Wallis test was also used to analyze differences in mean efficiency. Inefficiency scores were regressed with hospital characteristics to test for other determinants. These results did not confirm differences in efficiency concerning ownership. However, in some subgroups of hospitals, running an Emergency Department or an Intensive Care Unit had a significant effect. Tobit regression results provided additional insight into how an Emergency Department or Intensive Care Unit can affect efficiency. Both cases had an effect of increasing inefficiency, and the data suggested that the department/unit size plays an important role.

Efficiency and productivity of county-level traditional Chinese medicine hospitals in Hubei Province, China: A retrospective study based on 17 years of panel data

BACKGROUND

The county-level traditional Chinese medicine hospitals have significantly expanded in recent decades. This study aims to assess the changes in the efficiency and productivity of the county-level traditional Chinese medicine hospitals and explore the possible causes of such changes.

METHODS

Sixty one hospitals spanning from 2001 to 2017 were selected as samples in this study. And a slacks-based measure of super-efficiency in Data Envelopment Analysis and Malmquist index were used to respectively measure the changes in the efficiency and productivity.

RESULTS

The scale of sample hospitals in Hubei continuously expanded from 2001 to 2017. The mean values of technical efficiency, pure technical efficiency and scale efficiency in 2017 were 0.686, 0.74 and 0.933, respectively. The technical efficiency changes in 2017 was 1.97 times that of 2001, and the technological changes in 2017 was 1.45 times that of 2001.

CONCLUSIONS

The medical environment and resources have been greatly improved due to the expansion of the sample hospitals, but the technical efficiency value indicates that the operation efficiency of sample hospitals still needs to be significantly improved. Decision-makers are advised to attach importance to the efficiency of operation management and consider the impact of multiple factors on the change in productivity.

The effect of Iran's health transformation plan on hospital performance: Kerman province

Iran has performed Health Transformation Plan (HTP) from 2014 to obtain its defined goals. This study assesses and compares university and non-university hospitals' efficiency and productivity in Kerman provinces, Iran. The data of 19 selected hospitals, two years before and two years after Health Transformation Plan, was collected in this cross-sectional study. These data included the variables of physician and nurse number, and active beds as inputs and bed occupancy rate and inpatient admission adjusted with the length of stay as outputs. Data Envelopment Analysis method used to measure hospital efficiency. Malmquist Productivity Index is used to measure the efficiency change model before and after the plan. The efficiency and effect of the plan on hospitals' efficiency and productivity were assessed using R software. The results indicated that all hospitals' average efficiency before the HTP was 0.843 and after the HTP was increased to 0.874. However, it was not significant (P>0.05). Productivity also had a decreasing trend. Based on the DEA method results, it was found that university and non-university hospitals' efficiency and productivity did not increase significantly after the HTP. Therefore, it is recommended that attention be paid to hospitals' performance indicators regarding how resources are allocated and decisions made.