Empirical Analysis of Factors Influencing Healthcare Efficiency among Emerging Countries

Can public hospital reform reduce medical resource mismatches? Evidence from China

BACKGROUND

The mismatch of medical resources is a significant issue in global healthcare, undermining both service accessibility and system efficiency. In China, despite the implementation of the "Healthy China" strategy, persistent mismatches remain due to factors such as industrialization, urbanization, and population aging. This study empirically evaluates the impact of Public Hospital Reform (PHR) on mitigating these mismatches.

METHODS

A Difference-in-Differences (DD) approach is applied to panel data from 300 cities spanning 2010 to 2021, using the phased implementation of PHR as a quasi-natural experiment. This allows for a comparative analysis of changes in resource allocation between cities that adopted the reform and those that did not. Quantile regression assesses the effects of PHR across varying levels of resource mismatch, while mechanism tests investigate how PHR influences mismatches through cost reduction and supply expansion.

RESULTS

PHR is found to reduce medical resource mismatches by 13.9%, primarily driven by cost reductions and increased resource supply. The effects are more pronounced at both lower and higher levels of mismatch, with a limited impact at mid-levels. Furthermore, the reform's effectiveness diminishes as it is extended to more cities, suggesting a potential saturation effect.

CONCLUSIONS

This study demonstrates that PHR significantly alleviates medical resource mismatches in China. The findings underscore the need to focus on cost control and resource supply in future healthcare reforms, providing key insights for policymakers in developing countries facing similar healthcare resource challenges.

The Impact of Broadband Infrastructure Construction on Medical Resource Mismatch: Quasi-Natural Experiment From the Broadband China Policy

BACKGROUND

Whether the construction of broadband infrastructure can alleviate the problem of mismatched medical resources is crucial to the national information strategy, residents' well-being, and social equity. However, the academic community lacks a comprehensive theoretical analysis and rigorous empirical research on this issue.

OBJECTIVE

This study aims to construct a preliminary theoretical framework to scientifically assess the effects of broadband infrastructure development on the mitigation of health care resource mismatch from both theoretical and empirical perspectives, to explore the potential mechanisms of influence, and ultimately to develop several practical policy recommendations.

METHODS

We first used a theoretical analysis to propose testable theoretical hypotheses and establish a preliminary theoretical framework. Then, based on balanced panel data from 300 cities from 2010 to 2021, a 2-way fixed effects difference-in-differences model was used for empirical testing. Mechanism tests, robustness analyses, and heterogeneity analyses were further conducted.

RESULTS

The research findings demonstrate that the Broadband China Policy significantly reduces the degree of mismatch in medical resources by primarily using innovation effects and integration effects, resulting in a reduction of 13.2%. In addition, the heterogeneity analysis reveals that the central and eastern regions, cities with large populations, and areas with a high proportion of young people benefit more significantly.

CONCLUSIONS

This study fully confirms, both theoretically and empirically, that broadband infrastructure construction can effectively reduce the mismatch of medical resources not only by expanding the existing literature on the impact of broadband on public services but also by providing valuable opportunities for policy makers to optimize the allocation of medical resources.

Estimating the efficiency of primary health care services and its determinants: evidence from provincial panel data in China

Background

The efficiency of primary health care services is drawing increased attention worldwide, especially in developing countries. Health care reform in China has moved into the 'deep water zone' phase and is facing the dilemma of inefficiency in primary health care services, which is a critical challenge for universal health coverage.

Methods

In this study, we estimate the efficiency of primary health care services in China and its determinants. A combination of a super-SBM (Slack-Based Measure) model, a Malmquist productivity index model and a Tobit model is used to study provincial panel data, and the results demonstrate the inefficiency of primary health care services in China and the variations in efficiency values between regions.

Results

Over time, the productivity of primary health care services shows a decreasing trend, mainly due to slowing technology change. Financial support is needed to improve the efficiency of primary health care services, but it is worth noting that existing social health insurance coverage decreases efficiency, while economic development, urbanization and education also have a significant impact.

Conclusion

The findings suggest that increasing financial support should remain a priority in developing countries but that reasonable reimbursement design, appropriate payment methods and comprehensive supporting social health insurance policies are key to the next step of reform.

Efficiency Measurement Using Data Envelopment Analysis (DEA) in Public Healthcare: Research Trends from 2017 to 2022

With the shifting healthcare environment, the importance of public healthcare systems is being emphasized, and the efficiency of public healthcare systems has become a critical research agenda. We reviewed recent research on the efficiency of public healthcare systems using DEA, which is one of the leading methods for efficiency analysis. Through a systematic review, we investigated research trends in terms of research purposes, specific DEA techniques, input/output factors used for models, etc. Based on the review results, future research directions are suggested. The results of this paper provide valuable information and guidelines for future DEA research on public healthcare systems.

Impact of the development of information society on healthcare efficiency: Empirical evidence from 31 Chinese provinces

The development of information society has deeply changed the style of the healthcare service delivery and medical information access. This study aims to investigate how the information society development affects the efficiency of healthcare system in China, and explore provincial disparities in the impact. Based on the two-stage Data Envelopment Analysis (DEA) framework, this paper uses a panel data from 31 Chinese provinces from 2014 to 2017 to estimate efficiency of healthcare service and analyze the influence of the development of information society on efficiency. With the information society index (ISI) increased from 0.423 to 0.488 during the sample period, the healthcare efficiency experienced a slight decrease from 0.892 to 0.869. Moreover, the pure technical efficiency (PTE) is much lower than the scale efficiency (SE), and thus is the key to enhance the overall technical efficiency (TE). The time-fixed Tobit regression analysis suggests that information society development leads to a significant increase in PTE, but results in a decrease in SE, and therefore has little effect on TE. Further analysis reveals that the impact differs sharply between low-efficiency and high-efficiency provinces. For the low-efficiency provinces, the TE increases significantly with the development of the information society, mainly due to a considerable increase in PTE. In contrast, the TE decreases for the high-efficiency provinces, mainly caused by a decrease in SE. This paper highlights the importance of information infrastructure investment in healthcare system and the application of emerging information technologies to breakout the time and space boundaries of healthcare services in improving overall efficiency. In inefficient provinces, it is also necessary to properly control the growth of healthcare inputs.

Dynamic Performance Assessment of Hospitals by Applying Credibility-Based Fuzzy Window Data Envelopment Analysis

The goal of the current research is to propose the credibility-based fuzzy window data envelopment analysis (CFWDEA) approach as a novel method for the dynamic performance evaluation of hospitals during different periods under data ambiguity and linguistic variables. To reach this goal, a data envelopment analysis (DEA) method, a window analysis technique, a possibilistic programming approach, credibility theory, and chance-constrained programming (CCP) are employed. In addition, the applicability and efficacy of the proposed CFWDEA approach are illustrated utilizing a real data set to evaluate the performance of hospitals in the USA. It should be explained that three inputs including the number of beds, labor-related expenses, patient care supplies, and other expenses as well as three outputs including the number of outpatient department visits, the number of inpatient department admissions, and overall patient satisfaction level, are considered for the dynamic performance appraisal of hospitals. The experimental results show the usefulness of the CFWDEA method for the evaluation and ranking of hospitals in the presence of fuzzy data, linguistic variables, and epistemic uncertainty.

Evaluation of the Efficiency of European Health Systems Using Fuzzy Data Envelopment Analysis

Many studies that assess efficiency in health systems are based on output mean values. That approach ignores the representativeness of the average statistic, which can become a serious problem in estimation. To solve this question, this research contributes in three different ways: the first aim is to evaluate the technical efficiency in the management of European health systems considering a set of DEA (Data Envelopment Analysis) and FDEA (Fuzzy Data Envelopment Analysis) models. A second goal is to assess the bias in the estimation of efficiency when applying the conventional DEA. The third objective is the evaluation of the statistical relationship between the bias in the efficiency estimation and the macroeconomic variables (income inequality and economic freedom). The main results show positive correlations between DEA and FDEA scores. Notwithstanding traditional DEA models overestimate efficiency scores. Furthermore, the size of the bias is positively related to income inequality and negative with economic freedom in the countries evaluated.