Efficiency of acute public hospitals in the region of Murcia, Spain

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.

Level of technical efficiency and associated factors among health centers in East Gojjam Zone, Northwest Ethiopia: an application of the data envelopment analysis

BACKGROUND

Besides the scarcity of resources, inefficient utilization of available health service resources has been the bottleneck to deliver quality health services in Ethiopia. However, Information regarding the efficiency of health service providers is limited in the country. Health service managers and policy makers must be well informed about the efficiency of health service providers and ways of using limited resources efficiently to make evidence-based decisions. This study aimed to assess the level of technical efficiency and associated factors among health centers in East Gojjam Zone, Northwest Ethiopia.

METHODS

A facility-based cross-sectional study was conducted among 27 randomly selected health centers in East Gojjam zone, Northwest Ethiopia, from October 30, 2022, to April 30, 2023. Using an interviewer-administered questionnaire and document review checklist, health centers' data was collected and entered to Epi-Data version 4.6. The data was exported to Microsoft office excel and Stata version 14 for analysis. A two-stage output-oriented data envelopment analysis with a variable return to scale assumption was employed to determine the level of technical efficiencies. Finally, the tobit regression model was applied to identify the associated factors at 5% level of significance.

RESULTS

In this study, 59.3% of the health centers were technically efficient. The mean technical efficiency score of the health centers was 0.899 ± 0.156. Inefficient health centers could provide more 22, 433 outpatient visits, 1,351 family planning visits, 155 referral services, 206 skilled deliveries and 385 fully vaccinations of children if they were technically efficient as their peer health centers for the same year. From the tobit regression, the catchment population and number of administrative staffs were statistically significant determinants of the technical efficiency of health centers.

CONCLUSIONS

The mean technical efficiency of the health centers in East Gojjam zone, Northwest Ethiopia was high. However, nearly half of the health centers were technically inefficient, which indicates the exitance of a space for further improvements in the productivity of these health centers. Employing excess number administrative staffs (above the optimal level) should be discouraged and selecting appropriate sites where the health centers to be constructed (to have large catchment population coverage) could improve the productivity of health centers.

Equity and efficiency of public hospitals' health resource allocation in Guangdong Province, China

Background

To better meet people’s growing demand for medical and health services, 21 cities in Guangdong Province were involved in the reform of public hospitals in 2017. This paper evaluates the equity and efficiency of public hospitals’ health resource allocation in Guangdong Province and explores ways to change the current situation.

Methods

Data were collected from the Guangdong Health Statistical Yearbook 2016–2020 and Guangdong Statistical Yearbook 2017–2021. The Gini coefficient (G), Theil index (T), and health resource density index (HRDI) were used to measure the equity of health resource allocation. An improved three-stage DEA method was applied in efficiency evaluation. The entropy weight method was employed to calculate the weight of different indicators to obtain a comprehensive indicator representing the overall volume of health resources in each city. A two-dimensional matrix was drawn between the HRDI of the comprehensive indicator and efficiency and the per capita government financial subsidies and efficiency to observe the coordination of equity and efficiency across regions.

Results

From 2016 to 2020, the G of public hospital, bed, and health technician allocation by population remained below 0.2, while that by geographical area ranged from 0.4 to 0.6; the G of government financial subsidies by population was above 0.4, while that by geographical area was greater than 0.7. The results for T showed that inequality mainly comes from intraregional differences, and the Pearl River Delta contributes most to the overall differences. Although the HRDI of the Pearl River Delta is far greater than that of other regions, obvious differences exist across cities in the region. Only 38.1% of cities were found to be efficient in 2020. The Pearl River Delta was in the first quadrant, and the other three regions were in the third quadrant, accounting for a large proportion.

Conclusion

The equity of government financial subsidies allocation was the worst, and there were distinct regional differences in the geographical distribution of health resources. The development of healthcare within the Pearl River Delta was highly unbalanced. The development of healthcare was uneven between the Pearl River Delta, eastern, western, and mountainous regions. In addition, most cities in the eastern, western, and mountainous regions bore the dual pressures of relatively insufficient health resources and inefficiency.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12939-022-01741-1.

A Survey of DEA Window Analysis Applications

This article aims to review, analyze, and classify the published research applications of the Data Envelopment Analysis (DEA) window analysis technique. The number of filtered articles included in the study is 109, retrieved from 79 journals in the web of science (WoS) database during the period 1996–2019. The papers are classified into 15 application areas: energy and environment, transportation, banking, tourism, manufacturing, healthcare, power, agriculture, education, finance, petroleum, sport, communication, water, and miscellaneous. Moreover, we present descriptive statistics related to the growth of publications over time, the journals publishing the articles, keyword terms used, length of articles, and authorship analysis (including institutional and country affiliations). To the best of the authors knowledge, this is the first survey reviewing the literature of the DEA window analysis applications in the 15 areas mentioned in the paper.

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.

Productivity analysis of regional-level hospital care in the Czech republic and Slovak Republic

Background

Providing hospital care is an essential objective of national health policies. The countries that share common history, when they emerged from the same health system and similar conditions in the early 1990s, after the division of Czechoslovakia, became the objects of evaluation of the development of technical efficiency of hospital care. The subsequent development of their health care system also was very similar, but no longer entirely identical. The article aims to identify the trends and disparities in the productivity of the capacities of hospital care on the regional level (NUTS III.) in the Czech Republic and the Slovak Republic in 2009–2018 before the COVID-19 pandemic using the multi-criteria decision methods.

Methods

The window analysis as a dynamic DEA method based on moving averages and also the Malmquist Index, that allows the evaluation of changes in relative efficiency and of changes in the production possibilities frontier have become the key methods for evaluating the over time efficiency evolution. To model technical efficiency, an output-oriented method assuming constant returns to scale was chosen. Aggregated input and output parameters for each region were the object of study.

Results

The results showed that differences in the efficiency trends in terms of the examined parameters among the individual regions are slightly greater in the Czech Republic than in the Slovak Republic. The least efficient regions are those where capital cities are located. Furthermore, the analysis showed that in 2018 all of the Slovak Republic regions improved its productivity compared to 2009 and that technological conditions had a significant impact on this improvement. The results of the Czech Republic regions show productivity improvement in 57% of the regions that, on the contrary, was due to changes in technical efficiency.

Conclusions

It should be recommended to the state- and regional-level governments to refrain from unilaterally preferring the orientation of public policies on the efficiency of the provision of hospital care, and rather focus on increasing the quality and availability of hospital care, especially in smaller, rural, and border regions, in the interest of population safety during pandemics and other emergencies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07471-y.

Regional Differences and Influencing Factors of Allocation Efficiency of Rural Public Health Resources in China

In the face of increasingly growing health demands and the impact of various public health emergencies, it is of great significance to study the regional differences in the allocation efficiency of the rural public health resources and its improvement mechanism. In this paper, the game competition relationship is included in the evaluation model, and the game cross-efficiency model is used to measure the allocation efficiency of the rural public health resources in 31 provinces of China from 2008 to 2017. Then, the Theil index model and the Gini index model are applied in exploring the regional differences in the allocation efficiency of rural public health resources and its sources. Finally, the bootstrap truncated regression model is used to analyze the influencing factors of the allocation efficiency of the rural public health resources in China. The results show that, first, the total allocation efficiency level of the rural public health resources in China from 2008 to 2017 is relatively low, and it presents a U-shaped trend, first falling and then rising. Second, the changing trend of the allocation efficiency of the rural public health resources in the eastern, central, and western regions of China is similar to that in the nationwide region, and it shows a gradient trend that “the allocation efficiency in the eastern region is high, the allocation efficiency in the western region is low, and the allocation efficiency in the Central region is at the medium level”. However, the gap among the three regions is continually narrowing. Third, the calculation results of the Theil index and the Gini index show that intra-regional differences are the major source of the regional differences in the allocation efficiency of the rural public health resources in China, and the inter-regional differences demonstrate an expansion trend. Finally, the improvement of the education level and the social support level will generally improve the allocation efficiency of the rural public health resources in China and its three regions. The increased governmental financial support and urbanization level will reduce the allocation efficiency of the rural public health resources in China and its three regions. The economic development level, the living conditions and the population density are the important influencing factors of the allocation efficiency differences of the rural public health resources in the three regions. Therefore, on the basis of ensuring the increase of the total supply of the rural public health resources, more attention should be paid to the improvement of the allocation efficiency. Moreover, on the basis of continually narrowing the inter-regional differences among the eastern, central, and western regions, more attention should be paid to the intra-regional differences of the allocation efficiency of the rural public health resources among the different provinces. The various economic and social policies should be constantly optimized to jointly improve the allocation efficiency of the rural public health resources.