International comparisons of the technical efficiency of the hospital sector: Panel data analysis of OECD countries using parametric and non-parametric approaches

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.

Efficiency effects of public hospital closures in the context of public hospital reform: a multistep efficiency analysis

In the wake of hospital reforms introduced in 2011 in Turkey, public hospitals were grouped into associations with joint management and some shared operational and administrative functions, similar in some ways to hospital trusts in the English National Health Service. Reorganization of public hospitals effect hospital and market area characteristics and existence of hospitals. The objective of this study is to examine the effect of closure on competitive hospital performances. Using administrative data from Turkish Public Hospital Statistical Yearbooks for the years 2005 to 2007 and 2014 to 2017, we conducted a three-step efficiency analysis by incorporating data envelopment analysis (DEA) and propensity score matching techniques, followed by a difference-in-differences (DiD) regression. First, we used bootstrapped DEA to calculate the efficiency scores of hospitals that were located near hospitals that had been closed. Second, we used nearest neighbour propensity score matching to form control groups and ensure that any differences between these and the intervention groups could be attributed to being near a hospital that had closed rather than differences in hospital and market area characteristics. Lastly, we employed DiD regression analysis to explore whether being near a closed hospital had an impact on the efficiency of the surviving hospitals while considering the effect of the 2011 hospital reform policies. To shed light on a potential time lag between hospital closure and changes in efficiency, we used various periods for comparison. Our results suggest that the efficiency of public hospitals in Turkey increased in hospitals that were located near hospitals that closed in Turkey from 2011. Hospital closure improves the efficiency of competitive hospitals under hospital market reforms. Future studies may wish to examine the efficiency effects of government and private sector collaboration on competition in the hospital market.

Do VIP medical services damage efficiency? New evidence of medical institutions' total factor productivity using Chinese panel data

This study examines the causal impact of very important person (VIP) medical services on hospital total factor productivity in Deyang, a prefectural-level city in western China, spanning the years 2015-2020. This aims to offer empirical evidence and policy recommendations for the implementation of VIP practices in the medical field. A secondary unbalanced panel dataset of 416 observations was collected from the annual reports of the Health Commission and 92 eligible medical institutions were included. This study utilized a two-stage strategy. First, the Global Malmquist index was used to calculate the total factor productivity and its decomposition terms for hospitals from 2015 to 2020. In the second stage, two-way fixed effects models and Tobit models were used to identify the relationship between VIP medical services and hospital efficiency; instrumental variables were used to solve potential endogeneity problems in the model. The results showed that VIP medical services had a significantly negative impact on medical institutions' efficiency. The technological advances and pure technical efficiency related to VIP medical care may help explain these negative impacts, which were heterogeneous across groups divided by the nature of the hospital and the outside environment. It is imperative to prioritize the standardized provision of VIP medical services for medical institutions, optimize management and service process, enhance the training of clinical and scientific research capabilities of medical personnel, and scientifically allocate resources for both VIP and general medical services. This will help mitigate health inequality while improving the overall quality of medical services.

Regional differences of individual and allocation efficiencies of health resources in China

Background

The existing health resources and services are difficult to meet the needs of rapid economic development and the aging population in China. This paper evaluates the regional differences of individual and allocation efficiencies of health resources in China to explore ways to change the current situation.

Methods

The models of single-input single-output efficiency (SISOE), single-input multi-output efficiency (SIMOE), multi-input single-output efficiency (MISOE), and multi-input multi-output efficiency (MIMOE) were developed to calculate the individual and allocation efficiencies of health resources of China in this study.

Results

It was found that the efficiencies of the number of health institutions (NHI) in the eastern and western regions of China were relatively close, with values of 0.61 and 0.59, respectively, significantly higher than 0.49 in the middle region. The efficiencies of the number of health personnel (NHP) in the eastern, middle, and western regions were closer, with values of 0.77, 0.75, and 0.79, respectively. The efficiencies of the number of health institution beds (NHIB) in the eastern and western regions were very close, with values of 0.79 and 0.78, respectively, while that in the middle region was 0.72. The efficiencies of the total health expenditure (THE) were 0.72, 0.76, and 0.79 in the east, middle, and western regions, respectively. The efficiencies of the number of diagnosis and treatment persons (NDTP) were 0.81, 0.70, and 0.71 in the eastern, middle, and western regions, respectively, while the efficiencies of the number of inpatients (NI) were 0.75, 0.79, and 0.81, respectively. The efficiencies of the utilization rate of beds (URB) and the average days of hospitalization (ADH) in the three regions were below 0.51. The health resources allocation efficiencies (HRAEs) were 0.86, 0.83, and 0.87 in the eastern, middle, and western regions, respectively.

Conclusion

There were obvious regional differences in HRAE in China with the situation of "Middle Collapse." The main direct reason for the low HRAE in the middle region was the lower efficiencies of NHI, NHIB, URB, and ADH. It revealed that there was relatively blind expansion of health institutions and beds with lower health service quality in the middle region. Governments should make strategic adjustments to public health resources and increase the investment in medical technology and manpower in the middle region. Hospitals in the eastern region should strengthen inter-regional medical and health technical cooperation with partners in the middle region by establishing a tele-medical network. The models of SISOE, SIMOE, MISOE, and MIMOE put forward in this study are simple, reasonable, and useful for resource efficiency analysis, which makes it convenient to adopt targeted measures to upgrade the efficiency of resource allocation. This study provides a new perspective and method to understand the mechanism of regional differences in China's health resource allocation efficiency.

Exploring the association between primary care efficiency and health system characteristics across European countries: a two-stage data envelopment analysis

BACKGROUND

Primary care is widely seen as a core component of resilient and sustainable health systems, yet its efficiency is not well understood and there is a lack of evidence about how primary care efficiency is associated with health system characteristics. We examine this issue through the lens of diabetes care, which has a well-established evidence base for effective treatment and has previously been used as a tracer condition to measure health system performance.

METHODS

We developed a conceptual framework to guide the analysis of primary care efficiency. Using data on 18 European countries during 2010-2016 from several international databases, we applied a two-stage data envelopment analysis to estimate (i) technical efficiency of primary care and (ii) the association between efficiency and health system characteristics.

RESULTS

Countries varied widely in terms of primary care efficiency, with efficiency scores depending on the range of population characteristics adjusted for. Higher efficiency was associated with bonus payments for the prevention and management of chronic conditions, nurse-led follow-up, and a financial incentive or requirement for patients to obtain a referral to specialist care. Conversely, lower efficiency was associated with higher rates of curative care beds and financial incentives for patients to register with a primary care provider.

CONCLUSIONS

Our results underline the importance of considering differences in population characteristics when comparing country performance on primary care efficiency. We highlight several policies that could enhance the efficiency of primary care. Improvements in data collection would enable more comprehensive assessments of primary care efficiency across countries, which in turn could more effectively inform policymaking.

Analyzing the effect of health reforms on the efficiency of Ecuadorian public hospitals

This study aims to assess whether Ecuadorian health reforms carried out since 2008 have affected the efficiency performance of public hospitals in the country. We contribute to the literature by shedding new light on the effects on public healthcare efficiency for developing countries when policies move toward health equity and universal coverage. We follow a two-stage approach, wherein the first stage we make use of factor and cluster analysis to obtain three clusters of public hospitals based on their technological endowment; we exploit Data Envelopment Analysis for panel data in the second stage to estimate robust efficiency measures over time. Our innovative empirical strategy considers the heterogeneity of healthcare institutions in the analysis of their efficiency performance. The results show a significant decrease in the average efficiency of low and intermediate technology hospitals after the new constitution was adopted in 2008. The decline in efficiency coincides with the two reforms of 2010 and 2011 that brought on higher social security coverage.

Respective healthcare system performances taking into account environmental quality: what are the re-rankings for OECD countries?

BACKGROUND

Efficiency analyses have been widely used in the literature to rank countries regarding their health system performances. However, little place has been given to the environmental aspect: two countries with the same characteristics could experience completely different healthcare system outcomes just because they do not face the same environmental quality situation, which is a major determinant of the health of inhabitants.

METHODS

Using a stochastic frontier model, this paper analyses the effect of environmental quality on health system outcomes in OECD countries, measured by life expectancy at birth.

RESULTS

We show that the healthcare system performance ranking of OECD countries changes significantly, depending on whether the environmental index is taken into account.

CONCLUSIONS

These findings, once again, underline the critical importance of the environment when addressing population health issues. In general, our results can be aligned with the messages of the One Health approach literature.

Uncertain Malmquist productivity index: An application to evaluate healthcare systems during COVID-19 pandemic

Evaluation of healthcare systems, as a key organization providing different health services, is essential. This issue becomes more crucial when occurring crises such as a pandemic. They need to keep track of their success in the face of the crisis to assess the effects of policy changes and their capability to respond to new challenges. The Malmquist Productivity Index (MPI) is measured to analyze the causes of productivity change between two periods of time. The estimation of the traditional MPI requires reliable and detailed information on the inputs and outputs of decision-making units. However, there are a lot of situations where input and/or output may be imprecise. It is not manageable to reliably measure certain measurement indices, such as quality of treatment or system flexibility. For such cases, experts are invited to model their opinion. Uncertainty theory is a mathematical branch rationally dealing with belief degrees. The primary objective of this study is to apply MPI concept in the nonparametric approach of data envelopment analysis to calculate the efficiency of systems over different periods of time under uncertain conditions. Accordingly, we consider the MPI when inputs and outputs are belief degrees of experts. Furthermore, the sensitivity of the model is analyzed to determine the reliability of the results to the variation of variables. Finally, as an illustrative example, we explore longitudinal efficiency of healthcare systems during COVID-19 pandemic. According to the results of our model, the majority of the countries have improved in the second period which can be the result of efforts to improve pandemic preparedness. The decomposition of MPI into efficiency changes and technical changes indicates that the rise in productivity is entirely related to the progressive change of the production frontier related to policymaking. This application attempts to demonstrate how crucial it is to take uncertainties into account when comparing the performance of different systems over periods of time. The developed model enables us to consider the uncertainty existing in COVID-19 pandemic. The proposed model can handle more accurately the uncertainty during the pandemic. Thus, the result could be more reliable, which can benefit decision-makers in regard to performance improvement.

Assessment of equity and efficiency of magnetic resonance imaging services in Henan Province, China

BACKGROUND

By evaluating equity and effectiveness, this study provides evidence-based knowledge for scientific decision-making and the optimization of magnetic resonance imaging (MRI) configuration and utilization at the provincial level.

METHODS

Using data from 2017, we applied a Gini coefficient to analyze the equity of MRI services in 11 sample cities in Henan province. An agglomeration degree was then applied to measure equity from the perspective of population and geography, and a data envelopment analysis was used to evaluate MRI efficiency.

RESULTS

The overall Gini coefficient of MRI allocation by population in the 11 sample cities is 0.117; however, equity varies considerably among the sample cities. The sample's comprehensive efficiency is only 0.732, indicating the overall ineffectiveness of provincial MRI utilization. The pure technical and scale efficiencies of four sample cities are below 1, indicating lower MRI effectiveness than the rest.

CONCLUSIONS

Although the overall equity of configuration at the provincial level is relatively good, equity varies at the municipal level. Our results demonstrate a low MRI utilization efficiency; accordingly, policymakers should dynamically adjust the policy based on equity and efficiency.

Data envelopment analysis to evaluate the efficiency of tobacco treatment programs in the NCI Moonshot Cancer Center Cessation Initiative

BACKGROUND

The Cancer Center Cessation Initiative (C3I) is a National Cancer Institute (NCI) Cancer Moonshot Program that supports NCI-designated cancer centers developing tobacco treatment programs for oncology patients who smoke. C3I-funded centers implement evidence-based programs that offer various smoking cessation treatment components (e.g., counseling, Quitline referrals, access to medications). While evaluation of implementation outcomes in C3I is guided by evaluation of reach and effectiveness (via RE-AIM), little is known about technical efficiency-i.e., how inputs (e.g., program costs, staff time) influence implementation outcomes (e.g., reach, effectiveness). This study demonstrates the application of data envelopment analysis (DEA) as an implementation science tool to evaluate technical efficiency of C3I programs and advance prioritization of implementation resources.

METHODS

DEA is a linear programming technique widely used in economics and engineering for assessing relative performance of production units. Using data from 16 C3I-funded centers reported in 2020, we applied input-oriented DEA to model technical efficiency (i.e., proportion of observed outcomes to benchmarked outcomes for given input levels). The primary models used the constant returns-to-scale specification and featured cost-per-participant, total full-time equivalent (FTE) effort, and tobacco treatment specialist effort as model inputs and reach and effectiveness (quit rates) as outcomes.

RESULTS

In the DEA model featuring cost-per-participant (input) and reach/effectiveness (outcomes), average constant returns-to-scale technical efficiency was 25.66 (SD = 24.56). When stratified by program characteristics, technical efficiency was higher among programs in cohort 1 (M = 29.15, SD = 28.65, n = 11) vs. cohort 2 (M = 17.99, SD = 10.16, n = 5), with point-of-care (M = 33.90, SD = 28.63, n = 9) vs. no point-of-care services (M = 15.59, SD = 14.31, n = 7), larger (M = 33.63, SD = 30.38, n = 8) vs. smaller center size (M = 17.70, SD = 15.00, n = 8), and higher (M = 29.65, SD = 30.99, n = 8) vs. lower smoking prevalence (M = 21.67, SD = 17.21, n = 8).

CONCLUSION

Most C3I programs assessed were technically inefficient relative to the most efficient center benchmark and may be improved by optimizing the use of inputs (e.g., cost-per-participant) relative to program outcomes (e.g., reach, effectiveness). This study demonstrates the appropriateness and feasibility of using DEA to evaluate the relative performance of evidence-based programs.

The effects of provider contract types and fiscal decentralization on the efficiency of the Polish hospital sector: A data envelopment analysis across 16 health regions

BACKGROUND

Expenditures on hospitals constitute a large proportion of total health expenditures. In Poland the share of hospital spending is higher than the European Union average. The efficiency of the Polish hospital sector merits investigation.

RESEARCH GOAL

The goal of this study is to estimate the relative technical efficiencies of Polish hospital regions, and to measure the impacts of provider contract types, fiscal decentralization, and the 2017 reform on the relative efficiencies.

METHODS

Using data from 16 hospital regions in Poland for the years 2007 to 2019, we estimate relative technical efficiencies and their determinants using a two-stage approach. In the first stage, we apply Data Envelopment Analysis, in which we assume variable returns to scale and an output orientation. In the second stage we use a truncated regression with double bootstrapping.

RESULTS

Our findings are threefold. First, fiscal decentralization may reduce technical efficiency, but the results was not statistically significant. Second, efficiency tended to be higher in regions where a greater proportion of nurses and midwives were offered employment as opposed to consulting contracts. Contract types offered to physicians were not statistically significant. Third, the 2017 reforms seem to have had a positive impact on efficiency to date.

CONCLUSION

Policy makers may wish to consider offering less fiscal autonomy and control to regions and encouraging employment contracts with nurses and midwives.

Benchmarking the operational efficiency of Mexican hospitals – a longitudinal study

Purpose

This study aims to benchmark the operational efficiency of fifty-eight public hospitals across Mexico between 2015 and 2018 and identifies the most critical inputs affecting their efficiency. In doing so, the study analyzes the impact of policy changes in the Mexican healthcare system introduced in recent years.

Design/methodology/approach

To measure the operational efficiency of Mexican public hospitals, data envelopment analysis (DEA) window analysis variable returns to scale (VRS) methodology using longitudinal data collected from the National Institute for Transparency and Access to Information (IFAI). Hospital groups are developed and compared using a categorization approach according to their average and most recent efficiency.

Findings

Results show that most of the hospitals in the study fall in the moving ahead category. The hospitals in the losing momentum or falling behind categories are mostly large units. Hospitals with initially low efficiency scores have either increased their efficiency or at least maintained a steady improvement. Finally, the findings indicate that most hospitals classified as moving ahead focused on a single care area (cancer, orthopedic care, child care and trauma).

Research limitations/implications

This study examined the technical efficiency of the Mexican healthcare system over a four-year period. Contrary to conventional belief, results indicate that most public Mexican hospitals are managed efficiently. However, recent changes in public and economic policies that came into effect in the current administration (2018) will likely have long-lasting effects on the hospitals' operational efficiency, which could impact the results of this study.

Originality/value

To the best of authors’ knowledge, this is the first study that examines the efficiency of the complex Mexican healthcare system using longitudinal data.

Should we adjust health expenditure for age structure on health systems efficiency? A worldwide analysis

INTRODUCTION

Healthcare expenditure, a common input used in health systems efficiency analyses is affected by population age structure. However, while age structure is usually considered to adjust health system outputs, health expenditure and other inputs are seldom adjusted. We propose methods for adjusting Health Expenditure per Capita (HEpC) for population age structure on health system efficiency analyses and assess the goodness-of-fit, correlation, reliability and disagreement of different approaches.

METHODS

We performed a worldwide (188 countries) cross-sectional study of efficiency in 2015, using a stochastic frontier analysis. As single outputs, healthy life expectancy (HALE) at birth and at 65 years-old were considered in different models. We developed five models using as inputs: (1) HEpC (unadjusted); (2) age-adjusted HEpC; (3) HEpC and the proportion of 0-14, 15-64 and 65 + years-old; (4) HEpC and 5-year age-groups; and (5) HEpC ageing index. Akaike and Bayesian information criteria, Spearman's rank correlation, intraclass correlation coefficient and information-based measure of disagreement were computed.

RESULTS

Models 1 and 2 showed the highest correlation (0.981 and 0.986 for HALE at birth and HALE at 65 years-old, respectively) and reliability (0.986 and 0.988) and the lowest disagreement (0.011 and 0.014). Model 2, with age-adjusted HEpC, presented the lowest information criteria values.

CONCLUSIONS

Despite different models showing good correlation and reliability and low disagreement, there was important variability when age structure is considered that cannot be disregarded. The age-adjusted HE model provided the best goodness-of-fit and was the closest option to the current standard.

COVID-19 health policy evaluation: integrating health and economic perspectives with a data envelopment analysis approach

The COVID-19 pandemic is a global challenge to humankind. To improve the knowledge regarding relevant, efficient and effective COVID-19 measures in health policy, this paper applies a multi-criteria evaluation approach with population, health care, and economic datasets from 19 countries within the OECD. The comparative investigation was based on a Data Envelopment Analysis approach as an efficiency measurement method. Results indicate that on the one hand, factors like population size, population density, and country development stage, did not play a major role in successful pandemic management. On the other hand, pre-pandemic healthcare system policies were decisive. Healthcare systems with a primary care orientation and a high proportion of primary care doctors compared to specialists were found to be more efficient than systems with a medium level of resources that were partly financed through public funding and characterized by a high level of access regulation. Roughly two weeks after the introduction of ad hoc measures, e.g., lockdowns and quarantine policies, we did not observe a direct impact on country-level healthcare efficiency, while delayed lockdowns led to significantly lower efficiency levels during the first COVID-19 wave in 2020. From an economic perspective, strategies without general lockdowns were identified as a more efficient strategy than the full lockdown strategy. Additionally, governmental support of short-term work is promising. Improving the efficiency of COVID-19 countermeasures is crucial in saving as many lives as possible with limited resources.

Contribution of the Technical Efficiency of Public Health Programs to National Trends and Regional Disparities in Unintentional Childhood Injury in Japan

To achieve the Sustainable Development Goals, strengthening investments in health service inputs has been widely emphasized, but less attention has been paid to tackling variation in the technical efficiency of services. In this study, we estimated the technical efficiency of local public health programs for the prevention of unintentional childhood injury and explored its contribution to national trend changes and regional health disparities in Japan. Efficiency scores were estimated based on the Cobb-Douglas and translog production functions using a true fixed effects model in a stochastic frontier analysis to account for unobserved time-invariant heterogeneity across prefectures. Using public data sources, we compiled panel data from 2001 to 2017 for all 47 prefectures in Japan. We treated disability-adjusted life years (DALYs) as the output, coverage rates of public health programs as inputs, and caregivers' capacity and environmental factors as constraints. To investigate the contribution of efficiency to trend changes and disparities in output, we calculated the predicted DALYs with several measures of inefficiency scores (2001 average, yearly average, and prefecture-year-specific estimates). In the translog model, mean efficiency increased from 0.62 in 2001 to 0.85 in 2017. The efficiency gaps among prefectures narrowed until 2007 and then remained constant until 2017. Holding inefficiency score constant, inputs and constraints contributed to improvements in average DALYs and widened regional gaps. Improved efficiency over the years further contributed to improvements in average DALYs. Efficiency improvement in low-output regions and stagnated improvement in high-output regions offset the trend of widening regional health disparities. Similar results were obtained with the Cobb-Douglas model. Our results demonstrated that assessing the inputs, constraints, output, and technical efficiency of public health programs could provide policy leverage relevant to region-specific conditions and performance to achieve health promotion and equity.

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.

Output Targeting and Runway Utilization of Major International Airports: A Comparative Analysis Using DEA

The aviation industry is a prominent contributor to economic development. The existence of an airport hub that provides a worldwide transportation network generates economic growth, creates jobs, and facilitates international trade and tourism. This industry also helps in connecting different continents, countries, and cultures. This study utilizes the Data Envelopment Analysis models Charnes, Cooper, and Rhodes (CCR), Banker, Charnes, and Cooper (BCC), Slacks-Based Measure (SBM), and Epsilon Based Measure (EBM) in analyzing and evaluating the operational performance of the 21 major airports runway design during the years of 2016–2019 using the data of the International Civil Aviation Organization (ICAO) air transport statistics. The objective of this paper is to assess the efficiency of various airport runway configurations based on input factors such as number of runways, dimension of runways, airport area, and output factors such as annual number of flights and annual number of passengers. In the four applied models, the results indicated London Heathrow Airport (LHR) and Munich International Airport (MUC) are efficient in utilizing the runway during the considered periods. Surprisingly, airports in the Asian continent with a parallel runway design are more efficient than in North America and Europe. This study can be a valuable reference for operation managers in evaluating and benchmarking the performance of an airport with different types of runway configurations. Moreover, it can be used by decision-makers, investors, stakeholders, policymakers, private companies, and government agencies as a guideline suitable for an airport.

Economies of scale and optimal size of maternity services in Belgium: A Data Envelopment Analysis

This article uses a Data Envelopment Analysis to measure scale efficiency of maternity services in Belgium and estimate the minimum efficient scale in this context. Using administrative data for all maternity services in Belgium in 2016, the minimum efficient scale is estimated at 557 deliveries per year, which is above the currently prevailing norm of 400 deliveries per year. In particular, the closure of 17 small maternity services could improve efficiency without reducing accessibility. In addition to that, further efficiency gains could be attained by increasing the scale of maternity services up to at least 900 deliveries per year. Although most services are close to scale efficiency, the mean scale inefficiency level is 13% and low scores are mainly concentrated among the smallest services. These results are robust to changes in model specifications, bootstrapping and removal of outliers. In the current context of reform of the hospital and maternity landscape in Belgium, this study shows room for improvement and the possibility to generate substantial efficiency gains that could be reinvested in the healthcare system.

The Efficiency Evaluation of Municipal-Level Traditional Chinese Medicine Hospitals Using Data Envelopment Analysis After the Implementation of Hierarchical Medical Treatment Policy in Gansu Province, China

Background: Efficiency evaluation is an integral part of new medical reform and is necessary to solve the problem of limited and unbalanced medical resources. This study evaluated the efficiency of municipal-level Traditional Chinese Medicine hospitals by Data Envelopment Analysis application after a hierarchical medical treatment policy was implemented. We propose solutions to the problems existing in hospital operations and promote the utilization efficiency of medical resources in those hospitals. Methods: The sample included all municipal-level TCM hospitals in Gansu province from 2017 to 2019. The DEA-BCC model was employed to evaluate the relative efficiency of hospital operations, and the Manny-Whitney test was used to compare the input and output variables of technical efficiency efficient and inefficient hospitals. Results: From 2017 to 2019, the growth in the number of staff in secondary hospitals (25.88%) was lower than that in tertiary hospitals (31.98%). However, the increase in the number of beds (16.52%) in secondary hospitals was higher than that in tertiary hospitals (−0.30%). 5 (38.46%) achieved DEA efficient in secondary hospitals and 2 (40.00%) in tertiary hospitals. The means of technical efficiency, pure technical efficiency, and scale efficiency in secondary hospitals were 0.812, 0.887, and 0.908, respectively. The means in tertiary hospitals were 0.868, 0.926, and 0.935, respectively. The hospital areas were statistically different between the TE efficient and inefficient hospitals (P<0.05) in secondary hospitals. However, the number of outpatients between the two groups was statistically different (P<0.05) in tertiary hospitals. Conclusion: In this study, the medical and health services of municipal TCM hospitals in Gansu Province have made great progress. Due to the backward economy of Gansu Province, the classification of diagnosis and treatment of diseases was still based on Western medicine, resulting in the slow medical development of some municipal TCM hospitals. TCM hospitals should improve management efficiency, optimize hospital operation scale, improve the utilization efficiency of medical resources and promote efficient hospital development.

Efficiency of district hospitals in Zimbabwe: Assessment, drivers and policy implications

The Government of Zimbabwe is committed to making progress towards universal health coverage. Unmet health needs are huge and the health system suffers from serious dysfunctions and weaknesses. The situation is further complicated by a weak governance. To address these challenging issues, many of which would require an increase in public health expenditures, the government faces severe macroeconomic constraints. In this context, improving the efficiency of public health expenditures is of paramount importance. This study focuses on the efficiency of district hospitals, whose role is crucial for the strengthening of the health care system and achieving significant results in implementing the universal health coverage. Based on a sample of 31 district hospitals observed from 2015 to 2017 we use the double bootstrap procedure developed by Simar and Wilson to (a) estimate bias-adjusted DEA efficiency scores and to (b) investigate the factors associated with the previously calculated scores using truncated regression. The average efficiency of district hospitals is low and stagnant over 2015-2017. The findings suggest the existence of a significant room for maneuver to get more results with the resources spent. The analysis of the efficiency drivers shows the importance of both supply and demand-side factors, leading to several policy-oriented considerations. The study also highlights important shortcomings in the routine collection of basic data that need to be addressed by the Ministry of Health and Child Care.

Health system efficiency and democracy: A public choice perspective

Due to increasing demand and scarce financial resources for healthcare, health system efficiency has become a major topic in political and scientific debates. While previous studies investigating determinants of health system efficiency focused primarily on economic and social influence factors, the role of the political regime has been neglected. In addition, there is a lack of formal theoretical work on this specific topic, which ensures transparency and logical consistency of arguments and implications. Using a public choice approach, this paper provides a rigorous theoretical and empirical investigation of the relationships between health system efficiency and political institutions. We develop a simple principal-agent model describing the behavior of a government with respect to investments in population health under different political regimes. The main implication of the theoretical model is that governments under more democratic regimes put more effort in reducing embezzlement of health expenditure than non-democratic regimes. Accordingly, democratic countries are predicted to have more efficient health systems than non-democratic countries. We test this hypothesis based on a broad dataset including 158 countries over the period 1995-2015. The empirical results clearly support the implications of the theoretical model and withstand several robustness checks, including the use of alternative indicators for population health and democracy and estimations accounting for endogeneity. The empirical results also indicate that the effect of democracy on health system efficiency is more pronounced in countries with higher income levels. From a policy perspective, we discuss the implications of our findings in the context of health development assistance.

Efficiency Comparison of Public Hospitals under Different Administrative Affiliations in China: A Pilot City Case

This study seeks to measure the efficiency disparity and productivity change of tertiary general public hospitals in Wuhan city, central China from the perspective of administrative affiliations by using panel data from 2013 to 2017. Sample hospitals were divided into three categories, namely provincial hospitals, municipal hospitals, and other levels of hospitals. Data envelopment analysis with bootstrapping technique was used to estimate efficiency scores, and a sensitive analysis was performed by varying the specification of model by considering undesirable outputs to test robustness of estimation, and efficiency evolution analysis was carried out by using the Malmquist index. The results indicated that the average values of provincial hospitals and municipal hospitals have experienced efficiency improvement over the period, especially after the initiation of Pilot Public Hospital Reform, but hospitals under other affiliations showed an opposite trend. Meanwhile, differences of administrative subordination in technical efficiency of public hospitals emerged, and the disparity was likely to grow over time. The higher efficiency of hospitals affiliated with municipality, as compared with those governed by province and under other administrative affiliations, may be attributed to better governance and organization structure.

Measuring the efficiency of the healthcare sector in Poland – a window-DEA evaluation

Purpose

The main aim of the study was to measure and assess the efficiency of the healthcare system in Poland.

Design/methodology/approach

An output-oriented Data Envelopment Analysis model with a 2-years window analysis extension was used between 2013 and 2018. The analysis was completed with a determination of the sources of productivity changes (between the first and last year of the study period) and factors that influence efficiency.

Findings

Efficient regions have been identified and the spatial diversity in their efficiency was confirmed. The study identified individual efficiency trends together with “all-windows” best and worst performers. Using panel modeling, it was confirmed that the efficiency of health protection is influenced by, among others, accreditation certificates, the length of the waiting list or the number of medical personnel.

Research limitations/implications

Although the analysis was conducted at the voivodeship level (NUTS2), which was fully justified, it would be equally important to analyze data with a lower aggregation level. It would be extremely valuable from the perspective of difficulties faced by the healthcare system in Poland.

Practical implications

The identification of areas and problems affecting the efficiency of the healthcare system in Poland may also be a hint for other countries with similar system solutions that also struggle with the same problems.

Originality/value

The paper explains the efficiency of the country's healthcare system while also paying attention to changes in its level, factors influencing it, spatial diversity and impact on the sector functioning.

Measuring operational efficiency of isolation hospitals during COVID-19 pandemic using data envelopment analysis: a case of Egypt

Purpose

This study used Data Envelopment Analysis (DEA) to measure and evaluate the operational efficiency of 26 isolation hospitals in Egypt during the COVID-19 pandemic, as well as identifying the most important inputs affecting their efficiency.

Design/methodology/approach

To measure the operational efficiency of isolation hospitals, this paper combined three interrelated methodologies including DEA, sensitivity analysis and Tobit regression, as well as three inputs (number of physicians, number of nurses and number of beds) and three outputs (number of infections, number of recoveries and number of deaths). Available data were analyzed through R v.4.0.1 software to achieve the study purpose.

Findings

Based on DEA analysis, out of 26 isolation hospitals, only 4 were found efficient according to CCR model and 12 out of 26 hospitals achieved efficiency under the BCC model, Tobit regression results confirmed that the number of nurses and the number of beds are common factors impacted the operational efficiency of isolation hospitals, while the number of physicians had no significant effect on efficiency.

Research limitations/implications

The limits of this study related to measuring the operational efficiency of isolation hospitals in Egypt considering the available data for the period from February to August 2020. DEA analysis can also be an important benchmarking tool for measuring the operational efficiency of isolation hospitals, for identifying their ability to utilize and allocate their resources in an optimal manner (Demand vs Capacity Dilemma), which in turn, encountering this pandemic and protect citizens' health.

Originality/value

Despite the intensity of studies that dealt with measuring hospital efficiency, this study to the best of our knowledge is one of the first attempts to measure the efficiency of hospitals in Egypt in times of health' crisis, especially, during the COVID-19 pandemic, to identify the best allocation of resources to achieve the highest level of efficiency during this pandemic.

Investigating the link between medical urgency and hospital efficiency - Insights from the German hospital market

With hospital budgets remaining tight and healthcare expenditure rising due to demographic change and advances in technology, hospitals continue to face calls to contain costs and allocate their resources more efficiently. In this context, efficiency has emerged as an increasingly important way for hospitals to withstand competitive pressures in the hospital market. Doing so, however, can be challenging given unpredictable fluctuations in demand, a prime example of which are emergencies, i.e. urgent medical cases. The link between medical urgency and hospitals' efficiency, however, has been neglected in the literature to date. This study therefore aims to investigate the relationship between hospitals' urgency characteristics and their efficiency. Our analyses are based on 4094 observations from 1428 hospitals throughout Germany for the years 2015, 2016, and 2017. We calculate an average urgency score for each hospital based on all cases treated in that hospital per year and also investigate the within-hospital dispersion of medical urgency. To analyze the association of these urgency measures with hospitals' efficiency we use a two-stage double bootstrap data envelopment analysis approach with truncated regression. We find a negative relationship between the urgency score and hospital efficiency. When testing for non-linear effects, the results reveal a u-shaped association, indicating that having either a high or low overall urgency score is beneficial in terms of efficiency. Finally, our results reveal that higher within-hospital urgency dispersion is negatively related to efficiency.

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.

Health systems efficiency in Eastern Mediterranean Region: a data envelopment analysis

BACKGROUND

One of the most important issues in public policy and welfare state is health care. Poor management leads to the waste of resources, including money, human resources, facilities, and equipment.

AIMS

This paper seeks to answer the question of which eastern Mediterranean countries are more effective in allocating their health resources, and does Iran, in relation to those countries, have an effective health system.

METHODS

This study examined technical efficiency among eastern Mediterranean countries in 2018. Data were extracted from Global Health Observatory data World Health Organization. We applied input-oriented Data Envelopment Analysis (DEA) models to estimate efficiency scores. Inputs are Physicians density per 10,000 populations, Total hospital beds per 10,000 populations, Current expenditure on health, % of gross domestic product and outputs are infant survival rate and Life expectancy.

RESULTS

The most efficient health systems in the eastern Mediterranean were Bahrain, Egypt, Iran, Lebanon, Morocco, Oman, Pakistan, Qatar, Tunisia and the United Arab Emirates. The inefficient countries are Iraq, Jordan, Kuwait, Libya, Palestine and Saudi Arabia.

CONCLUSIONS

Among the efficient countries, one category of high-entry countries such as Bahrain and Qatar with high input especially in health expenditure had higher output. The second group of countries with lower inputs such as Iran and Morocco has been able to produce similar output with other countries. Also, inefficiency in countries such as Saudi Arabia can be attributed to this with higher input such as health expenditure has lower output such life expectancy and infant survival rate.

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

OBJECTIVE

To evaluate the efficiency of county public hospitals in Shandong Province following China's new medical reform and compare the efficiency of hospitals with different bed sizes for improving efficiency.

DESIGN AND SETTING

This was a cross-sectional study on the efficiency and size of 68 county public hospitals in China in 2017.

OUTCOME MEASURES

Data envelopment analysis was used to calculate the efficiency scores of hospitals and to analyse the slack values of inefficient hospitals. The actual number of open beds, doctors, nurses and total expenditure were selected as inputs, and the total number of annual visits, discharges and total income were selected as outputs. The Kruskal-Wallis H test was employed to compare the efficiency of hospitals with different bed sizes. The χ² test was used to compare the returns to scale (RTS) of hospitals with different bed sizes.

RESULTS

Twenty (29.41%) hospitals were efficient. There were 27 hospitals with increasing returns to scale, 23 hospitals with constant returns to scale and 18 hospitals with decreasing returns to scale (DRS). The differences in technical efficiency (p=0.248, p>0.05) and pure technical efficiency (p=0.073, p>0.05) were not statistically significant. However, the differences in scale efficiency (p=0.047, p<0.05) and RTS (p<0.001) were statistically significant. Hospitals with DRS began to appear at 885 beds. All sample hospitals with more than 1100 beds were already saturated and some hospitals even had a negative scale effect.

CONCLUSIONS

The government and hospital managers should strictly control the bed size in hospitals and make hospitals resume operating in the interests of public welfare. Interventions that rationally allocate health resources and improve the efficiency of medical workers are conducive to solving redundant inputs and insufficient outputs.

The Efficiency of Primary Health Care Institutions in the Counties of Hunan Province, China: Data from 2009 to 2017

This study aimed to estimate the efficiency and its influencing factors of Primary Health Care Institutions (PHCIs) in counties in Hunan Province, China, and put forward feasible suggestions for improving the efficiency of PHCIs in Hunan Province. We applied the Input-Oriented Data Envelopment Analysis (DEA) method and the Malmquist Index Model to estimate the efficiency of PHCIs in 86 counties in Hunan Province from 2009 to 2017. Then, the Tobit model was used to estimate the factors that influence the efficiency of PHCIs. Since the implementation of the new health-care reform in 2009, the number of health resources in PHCIs in Hunan Province has increased significantly, but most counties’ PHCIs remain inefficient. The efficiency of PHCIs is mainly affected by the total population, city level, the proportion of health technicians and the proportion of beds, but the changes in per capita GDP have not yet played a significant role in influencing efficiency. In the future, the efficiency of PHCIs should be improved by increasing medical technology skills and enthusiasm of health technicians and by improving the payment policies of medical insurance funds.

Provision of health care services and regional diversity in Germany: insights from a Bayesian health frontier analysis with spatial dependencies

The German health care system is among the most patient-oriented systems in Europe. Nevertheless, distinct utilisation patterns, access barriers due to socio-economic profiles, and potentials of misallocation of medical resources lead to disparities in the provision of health care services. We analyse how a possible over- and undersupply of services and the utilisation of and the access to the health care system relate to regional variations in the population's well-being. For this purpose, we employ a recent Bayesian stochastic frontier approach that allows for spatial dependence structures. Our results indicate that patient migration plays an important role in contributing to regional differences in the utilisation of the medical infrastructure. As a consequence, policy should take spatial patterns of health care utilisation into account to improve the allocation of medical resources.

Technical efficiency of provincial public healthcare in South Africa

Background

Forty-nine million people or 83 per cent of the entire population of 59 million rely on the public healthcare system in South Africa. Coupled with a shortage of medical professionals, high migration, inequality and unemployment; healthcare provision is under extreme pressure. Due to negligence by the health professionals, provincial health departments had medical-legal claims estimated at R80 billion in 2017/18. In the same period, provincial health spending accounted for 33 per cent of total provincial expenditure of R570.3 billion or 6 per cent of South Africa’s Gross Domestic Product. Despite this, healthcare outcomes are poor and provinces are inefficient in the use of the allocated funds. This warrants a scientific investigation into the technical efficiency of the public health system.

Methods

The study uses data envelopment analysis (DEA) to assess the technical efficiency of the nine South African provinces in the provision of healthcare. This is achieved by determining, assessing and comparing ways that individual provinces can benchmark their performance against peers to improve efficiency scores. DEA compares firms operating in homogenous conditions in the usage of multiple inputs to produce multiple outputs. Therefore, DEA is ideal for measuring the technical efficiency of provinces in the provision of public healthcare. In DEA methodology, the firms with scores of 100 per cent are technically efficient and those with scores lower than 100 per cent are technically inefficient. This study considers six DEA models using the 2017/18 total health spending and health staff as inputs and the infant mortality rate as an output. The first three models assume the constant returns to scale (CRS) while the last three use the variable return to scale (VRS) both with an input-minimisation objective.

Results

The study found the mean technical efficiency scores ranging from 35.7 to 87.2 per cent between the health models 1 and 6. Therefore, inefficient provinces could improve the use of inputs within a range of 64.3 and 20.8 per cent. The Gauteng province defines the technical efficiency frontiers in all the six models. The second-best performing province is the North West province. Other provinces like KwaZulu-Natal, Limpopo and the Eastern Cape only perform well under the VRS. The other three provinces are inefficient.

Conclusions

Based on the VRS models 4 to 6, the study presents three policy options. Policy option 1 (model 4): the efficiency gains from addressing health expenditure wastage in four inefficient provinces amounts to R17 billion. Policy option 2 (model 5): the potential savings from the same provinces could be obtained from reducing 17,000 health personnel, advisably, in non-core areas. In terms of Policy option 3 (model 6), three inefficient provinces should reduce 6940 health workers while the same provinces, inclusive of KwaZulu-Natal could realise health expenditure savings of R61 million. The potential resource savings from improving the efficiency of the inefficient provinces could be used to refurbish and build more hospitals to alleviate pressure on the public health system. This could also reduce the per capita numbers per public hospital and perhaps their performance as overcrowding is reportedly negatively affecting their performance and health outcomes. The potential savings could also be used to appoint and train medical practitioners, specialists and researchers to reduce the alarming numbers of medical legal claims. Given the existing challenges, South Africa is not ready to implement the National Health Insurance (NHI) Scheme, as it requires additional financial and human resources. Instead, huge improvements in public healthcare provision could be achieved by re-allocating the resources ‘saved’ through efficiency measures by increasing the quality of public healthcare and extending healthcare to more recipients.

Going beyond health efficiency: What really matters?

Both citizens and policymakers demand the best possible results from a country's healthcare system. It is of utmost importance to accurately and objectively assess the efficiency of a healthcare system and to note the key indicators, where resources are lost, and possibilities for improvement. This paper evaluates the efficiency of health systems in 38 countries, mainly members of the Organization for Economic Co-operation and Development, using data envelopment analysis (DEA). In the first stage, bootstrapped Ivanovic distance is used to generate weights for the indicators, thus taking into consideration different country's goals, but not to the extent of reducing the possibility of comparison. The analysis shows that human resources are the most important health system resource and countries should pay special attention to developing and employing competent medical workers. The reorganization of human resources and the funds allocated to them could also increase efficiency. The second stage examines environmental indicators to find the causes of inefficiency. No proof is found that any one basic health system funding model produces better health outcomes than the others. Obesity is identified as a major issue.

Evaluation of resource utilization efficiency in obstetrics and gynecology units in China: A three-stage data envelopment analysis of the Shanxi province

In China, health care resources for expectant mothers and children are still not utilized to full efficiency, with health requirements still not being met. The purpose of this study is to critically examine the efficiency of gynecology and obstetrics hospital (OB/GYN) units in Shanxi province of China, with the overarching objective of exploring methods for improving their efficiency. We employ the three-stage data envelopment analysis (DEA) model to measure the efficiency of 134 OB/GYN units in Shanxi. The results show that the technical efficiency and scale efficiency scores of the sample units were low (0.48 and 0.54, respectively). The efficiency of the OB/GYN units varies by region, city, and county and by type of unit. We conclude that the main reason for the low efficiency of OB/GYN units in Shanxi province lies in the unreasonable scale. The government should, therefore, allocate health resources more reasonably, improving the efficiency of different regions, cities, and counties, as well as different types of OB/GYN units.

The economic efficiency of clinical laboratories in public hospitals: A case study in Iran

Introduction

Clinical laboratories are identified as one of the most important and expensive units of the health system. Therefore, it is essential to pay attention to these units' cost efficiency. This study purpose was to evaluate the economic efficiency of hospitals' laboratory units affiliated to Urmia University of Medical Sciences (UMSU), in order to assess their performance.

Methods

This research was a descriptive‐analytic study that was accomplished in 2017. The statistical population of the study included all of the hospitals' clinical laboratories affiliated to UMSU. Moreover, DEA method and Deap_2.1 software were used to analyze data. In this study, technical and allocative efficiencies of the studied laboratory units were also calculated in addition to the determination of the economic efficiency of the laboratories.

Results

The average economic efficiency of clinical laboratories calculated by DEA in 2017 was 0.676. This value was lower than the allocative and technical efficiency scores, which indicates that these units could attain full efficiency by reducing their costs without having any effect on output values. Moreover, about 14 percent of the clinical laboratory units were economically efficient. In addition, it is noteworthy to state that, from total of university hospital laboratories, only three hospitals had no economic excess or deficiency values of inputs.

Conclusion

Considering that 76% of laboratory units have not been economically efficient, it is necessary for the laboratory managers to consider optimum allocating of resources, with respect to the cost of laboratory equipment and inputs in order to increase their units' economic efficiency.

Is capital investment in Australian hospitals effectively funding patient access to efficient public hospital care?

Objective This study asks ‘Is capital investment in Australian public hospitals effectively funding patient access to efficient hospital care?’ Methods The study drew information from semistructured interviews with senior health infrastructure officials, literature reviews and World Health Organization (WHO) reports. To identify which systems most effectively fund patient access to efficient hospitals, capital allocation systems for 17 Organisation for Economic Cooperation and Development (OECD) countries were assessed. Results Australian government objectives (equitable access to clinically appropriate, efficient, sustainable, innovative, patient-based) for acute health services are not directly addressed within Australian capital allocation systems for hospitals. Instead, Australia retains a prioritised hospital investment system for institutionally based asset replacement and capital planning, aligned with budgetary and political priorities. Australian systems of capital allocation for public hospitals were found not to match health system objectives for allocative, productive and dynamic efficiency. Australia scored below average in funding patient access to efficient hospitals. The OECD countries most effectively funding patient access to efficient hospital care have transitioned to diagnosis-related group (DRG) aligned capital funding. Measures of effective capital allocation for hospitals, patient access and efficiency found mixed government–private–public partnerships performed poorly with inferior access to capital than DRG-aligned systems, with the worst performing systems based on private finance. Conclusion Australian capital allocation systems for hospitals do not meet Australian government standards for the health system. Transition to a diagnosis-based system of capital allocation would align capital allocation with government standards and has been found to improve patient access to efficient hospital care. What is known about the topic? Very little is known about the effectiveness of Australian capital allocation for public hospitals. In Australia, capital is rarely discussed in the context of efficiency, although poor built capital and inappropriate technologies are acknowledged as limitations to improving efficiency. Capital allocated for public hospitals by state and territory is no longer reported by Australian Institute of Health and Welfare due to problems with data reliability. International comparative reviews of capital funding for hospitals have not included Australia. Most comparative efficiency reviews for health avoid considering capital allocation. The national review of hospitals found capital allocation information makes it difficult to determine ’if we have it right’ in terms of investment for health services. Problems with capital allocation systems for public hospitals have been identified within state-based reviews of health service delivery. The Productivity Commission was unable to identify the cost of capital used in treating patients in Australian public hospitals. Instead, building and equipment depreciation plus the user cost of capital (or the cost of using the money invested in the asset) are used to estimate the cost of capital required for patient care, despite concerns about accuracy and comparability. What does this paper add? This is the first study to review capital allocation systems for Australian public hospitals, to evaluate those systems against the contemporary objectives of the health systems and to assess whether prevailing Australian allocation systems deliver funds to facilitate patient access to efficient hospital care. This is the first study to evaluate Australian hospital capital allocation and efficiency. It compares the objectives of the Australian public hospitals system (for universal access to patient-centred, efficient and effective health care) against a range of capital funding mechanisms used in comparable health systems. It is also the first comparative review of international capital funding systems to include Australia. What are the implications for practitioners? Clinical quality and operational efficiency in hospitals require access for all patients to technologically appropriate hospitals. Funding for appropriate public hospital facilities, medical equipment and information and communications technology is not connected to activity-based funding in Australia. This study examines how capital can most effectively be allocated to provide patient access to efficient hospital care for Australian public hospitals. Capital investment for hospitals that is patient based, rather than institutionally focused, aligns with higher efficiency.

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

Aim: To evaluate the level of efficiency of public acute hospitals situated in the region of Murcia (Spain). Materials & methods: Data from nine acute general hospitals of Murcia's Health Service (SMS by its Spanish acronym) were analyzed over the 2012-2014 period. The data were extracted from the In-patient Health Establishment Statistics of the Ministry of Health, Social Services and Equality, from the National Health Service (SNS) portal and the SMS portal. To this end, the data envelopment analysis (DEA)-window method was used, since this extension of the basic DEA model allows to compare the efficiency of a small number of units over different years and analyze changes in efficiency over time. In addition, the model was complemented by smooth bootstrapping and a superefficiency analysis to improve the quality of the data interpretation. Four inputs were used (number of beds, number of operating rooms, personnel costs and operating costs), two undesirable outputs (average stay and rate of return) and three desirable outputs (weighted discharges, emergencies and surgical interventions). Results: The average level of inefficiency was 1.58% over the study period, with a good evolution between 2012 (3.53%) and 2014 (0.20%). This improvement was also reflected in the number of efficient hospitals that rose from two in 2012 to eight in 2014. Moreover, the slack levels detected were small. Conclusion: The management of the public hospitals analyzed was favorable, both regarding average level of efficiency and the number of hospitals qualified as efficient. However, the analysis revealed several ways to increase efficiency by reducing specific inputs and nondesirable outputs (mainly operating and personnel costs as well as average length of stay) while increasing desirable outputs (mostly the number of surgical interventions). To finish, specific policy measures are suggested to improve the performance of these hospitals.

Road map for progress and attractiveness of Iranian hospitals by integrating self-organizing map and context-dependent DEA

Hospitals play an important role in healthcare systems and usually stay on the end node of the healthcare chain. Thus, determining their road map to get close to the desired efficiency frontier and developing short-term and long-term plans could help to manage costs and resources, efficiently. As the efficiency frontier depends on the size of the hospital and the complexity of its structure, the homogeneity in benchmarking must be considered. For tackling this problem, the self-organizing map (SOM) is used to create homogeneous groups. On the other hand, data envelopment analysis (DEA) is a well-known methodology for evaluating decision-making units. Each unit obtains the efficiency score based on the ratio of weighted outputs to weighted inputs, where each unit can take the desirable weights for inputs and outputs to provide the maximum value. One of the problems of DEA is the selection of the reference set and distinguishing between the efficient hospitals. To overcome these problems, the context-depended DEA has been applied and the progress and attractiveness of hospitals are obtained. To evaluate the capability of the proposed approach, data of 288 Iranian hospitals are utilized. By applying SOM the hospitals are clustered into appropriate homogeneous groups and by applying context-dependent DEA, the road map for progress and attractiveness of each hospital is determined. In other words, using the proposed approach the hospitals are able to determine the short and long-term goals according to their strategic plans.

Cross-efficiency evaluation in the presence of flexible measures with an application to healthcare systems

In recent years, most countries around the world have struggled with the consequences of budget cuts in health expenditure, obliging them to utilize their resources efficiently. In this context, performance evaluation facilitates the decision-making process in improving the efficiency of the healthcare system. However, the performance evaluation of many sectors, including the healthcare systems, is, on the one hand, a challenging issue and on the other hand a useful tool for decision- making with the aim of optimizing the use of resources. This study proposes a new methodology comprising two well-known analytical approaches: (i) data envelopment analysis (DEA) to measure the efficiencies and (ii) data science to complement the DEA model in providing insightful recommendations for strategic decision making on productivity enhancement. The suggested method is a first attempt to combine two DEA extensions: flexible measure and cross-efficiency. We develop a pair of benevolent and aggressive scenarios aiming at evaluating cross-efficiency in the presence of flexible measures. Next, we perform data mining cluster analysis to create groups of homogeneous countries. Organizing the data in similar groups facilitates identifying a set of benchmarks that perform similarly in terms of operating conditions. Comparing the benchmark set with poorly performing countries we can obtain attainable goals for performance enhancement which will assist policymakers to strategically act upon it. A case study of healthcare systems in 120 countries is taken as an example to illustrate the potential application of our new method.

Examination of differences in health indicators between efficient and inefficient countries

OBJECTIVE

This study determined whether there is a statistically significant difference between efficient and inefficient Organization for Economic Co-operation and Development (OECD) countries in terms of health indicators using fuzzy data envelopment analysis (FDEA).

METHODS

In the study, FDEA was performed with three input variables directly affecting health, four environmental factors considered to indirectly affect health, and two output variables. Literature research was used to determine appropriate variables. In FDEA, three different α-cut levels were used. The hypotheses regarding whether there was a statistically significant difference between efficient and inefficient countries in input and output variables were tested for all α-cut levels of upper bound efficiency values.

RESULTS

In terms of health indicators, 17 countries were efficient at α-cut 0 and 0.5. At α-cut 1, 18 countries were efficient. There was only a statistically significant difference between the efficient and inefficient countries in "the number of physicians."

CONCLUSION

This study shows the number of physicians was the most important determinant affecting the efficiency of a country's healthcare system. Inefficient countries had a greater mean for number of physicians. Thus, inefficient countries consume more resources than efficient ones.

Efficiency Measurement in Health Facilities: A Systematic Review in Low- and Middle-Income Countries

BACKGROUND

Limited healthcare resources in low- and middle-income countries (LMICs) have led policy-makers to improve healthcare efficiency. Therefore, it is essential to understand how efficiency has been measured in the LMIC setting.

OBJECTIVE

This paper reviews methodologies used for efficiency studies in health facilities in LMICs.

METHODS

We searched MEDLINE, Embase, Global Health, EconLit and ProQuest Dissertations and Theses databases to Week 6 in 2018. We included all types of quantitative analysis studies relating to the measurement of the efficiency of services at health facilities in LMICs. We extracted data from eligible studies, and assessed the validity for each study. Because of the substantial heterogeneity of the studies, results were presented narratively.

RESULTS

A total of 137 papers were eligible for inclusion. These articles covered a wide range of health facility types, with more than half of the studies relating to hospitals. Our systematic review showed that there is an increasing trend in efficiency measurements in LMICs using various methods. Most studies employed data envelopment analysis as an efficiency measurement method. The studies typically included physical inputs and health services as outputs. Sixty-one percent of the studies analysed the contextual variables of the health facility efficiency.

CONCLUSION

This review highlights the potential for methodological improvement and policy impacts in efficiency measurements.

Firm Efficiency and Returns-to-Scale in the Honey Bee Pollination Services Industry

While the demand for pollination services have been increasing, continued declines in honey bee, Apis mellifera L. (Hymenoptera: Apidae), colonies have put the cropping sector and the broader health of agro-ecosystems at risk. Economic factors may play a role in dwindling honey bee colony supply in the United States, but have not been extensively studied. Using data envelopment analysis (DEA), we measure technical efficiency, returns to scale, and factors influencing the efficiency of those apiaries in the northern Rocky Mountain region participating in the pollination services market. We find that, although over 25% of apiaries are technically efficient, many experience either increasing or decreasing returns to scale. Smaller apiaries (under 80 colonies) experience increasing returns to scale, but a lack of available financing may hinder them from achieving economically sustainable colony levels. Larger apiaries (over 1,000 colonies) experience decreasing returns to scale. Those beekeepers may have economic incentivizes to decrease colony numbers. Using a double bootstrap method, we find that apiary location and off-farm employment influence apiary technical efficiency. Apiaries in Wyoming are found to be more efficient than those in Utah or Montana. Further, engagement in off-farm employment increases an apiary's technical efficiency. The combined effects of efficiency gains through off-farm employment and diseconomies of scale may explain, in part, the historical decline in honey bee numbers.

[Multilevel analysis of the technical efficiency of hospitals in the Spanish National Health System by property and type of management]

OBJECTIVE

To analyze technical efficiency by type of property and management of general hospitals in the Spanish National Health System (2010-2012) and identify hospital and regional explanatory variables.

METHOD

230 hospitals were analyzed combining data envelopment analysis and fixed effects multilevel linear models. Data envelopment analysis measured overall, technical and scale efficiency, and the analysis of explanatory factors was performed using multilevel models.

RESULTS

The average rate of overall technical efficiency of hospitals without legal personality is lower than hospitals with legal personality (0.691 and 0.876 in 2012). There is a significant variability in efficiency under variable returns (TE) by direct, indirect and mixed forms of management. The 29% of the variability in TE es attributable to the Region. Legal personality increased the TE of the hospitals by 11.14 points. On the other hand, most of the forms of management (different to those of the traditional hospitals) increased TE in varying percentages. At regional level, according to the model considered, insularity and average annual income per household are explanatory variables of TE.

DISCUSSION

Having legal personality favours technical efficiency. The regulatory and management framework of hospitals, more than public or private ownership, seem to explain technical efficiency. Regional characteristics explain the variability in TE.

The Determinants of the Technical Efficiency of Acute Inpatient Care in Canada

OBJECTIVE

To evaluate the technical efficiency of acute inpatient care at the pan-Canadian level and to explore the factors associated with inefficiency-why hospitals are not on their production frontier.

DATA SOURCES/STUDY SETTING

Canadian Management Information System (MIS) database (CMDB) and Discharge Abstract Database (DAD) for the fiscal year of 2012-2013.

STUDY DESIGN

We use a nonparametric approach (data envelopment analysis) applied to three peer groups (teaching, large, and medium hospitals, focusing on their acute inpatient care only). The double bootstrap procedure (Simar and Wilson 2007) is adopted in the regression.

DATA COLLECTION/EXTRACTION METHODS

Information on inpatient episodes of care (number and quality of outcomes) was extracted from the DAD. The cost of the inpatient care was extracted from the CMDB.

PRINCIPAL FINDINGS

On average, acute hospitals in Canada are operating at about 75 percent efficiency, and this could thus potentially increase their level of outcomes (quantity and quality) by addressing inefficiencies. In some cases, such as for teaching hospitals, the factors significantly correlated with efficiency scores were not related to management but to the social composition of the caseload. In contrast, for large and medium nonteaching hospitals, efficiency related more to the ability to discharge patients to postacute care facilities. The efficiency of medium hospitals is also positively related to treating more clinically noncomplex patients.

CONCLUSIONS

The main drivers of efficiency of acute inpatient care vary by hospital peer groups. Thus, the results provide different policy and managerial implications for teaching, large, and medium hospitals to achieve efficiency gains.