Benchmarking urban acute care hospitals: Efficiency and quality perspectives

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.

Evaluation of healthcare efficiency in China: a three-stage data envelopment analysis of directional slacks-based measure

Background

A consensus on the changing pattern of healthcare efficiency in China is current absent. This study tried to identify temporal fluctuations in healthcare efficiency from 2012 to 2021, and conducted a comparative analysis on the performance of 31 regions in China using region-level balanced panel data.

Methods

Employing three-stage data envelopment analysis (DEA) as the analytical framework, we measured healthcare efficiency and its changes using the directional slacks-based measure and global Malmquist-luenberger (GML) indexes. We also decomposed the sources of healthcare inefficiency and extended our analysis to changes in healthcare efficiency across different primary medical service levels and regional economic development tiers.

Results

The average efficiency score of medical institutions (0.956) was slightly higher than that of hospitals (0.930). We found that the average GML indexes of medical institutions in China stood at 0.990, while the average technical change (TC) index was 0.995 and the average efficiency change (EC) index was 0.998 from 2012 to 2021. The GML indexes, TC indexes, and EC indexes of hospitals were 1.002, 1.009, and 0.994, respectively. The healthcare inefficiency for both inputs and desirable outputs in medical institutions was primarily attributed to the redundant numbers of institutions, outpatient visits slacks and inpatient surgery volume slacks, accounting for 50.040, 49.644, and 28.877%, respectively. The undesirable output inefficiency values of medical institutions concerning in-hospital mortality stood at 0.012, while the figure for hospital regarding the average length of stay (LOS) was 0.002. Additionally, healthcare efficiency in both medical institutions and hospitals exhibited an upward trend from 2012 to 2021, corresponding to an increase in the volume of primary medical services, primary medical staff, and the total gross domestic product (GDP).

Conclusion

Total factor productivity (TFP) of medical services declined in China from 2012 to 2021. The excessive number of medical institutions and the slack of medical service volumes were the main sources of healthcare inefficiency. Regions prioritizing primary medical services and boasting higher GDP levels exhibited superior healthcare efficiency. These findings are expected to inform policymakers' efforts in building a value-based and efficient health service system in China.

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.

Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region

Background

The objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019.

Methods

A nonparametric approach—that is, multistage data envelopment analysis (DEA)—was applied to a sample of 43 hospitals. We identified three categories of input: capital investments (Beds), labor (FTE), operating expenses. We selected five efficiency outputs (outpatient visits, inpatients, outpatient visit revenue, inpatient revenue, bed occupancy rate) and two quality outputs (mortality rate and inappropriate admission rate). Efficiency scores were estimated and decomposed into two components. Slack analysis was then conducted. Further, DEA efficiency scores were regressed on internal and external variables using a Tobit model. Finally, the Malmquist Productivity Index was applied.

Results

On average, the hospitals in the Veneto region operated at more than 95% efficiency. Technical and scale inefficiencies often occurred jointly, with 77% of inefficient hospitals needing a downsizing strategy to gain efficiency. The inputs identified as needing significant reductions were full-time employee (FTE) administrative staff and technicians. The size of the hospital in relation to the size of the population served and the length of patient stay were important factors for the efficiency score. The major cause of decreased efficiency over time was technical change (0.908) rather than efficiency change (0.974).

Conclusions

The study reveals improvements that should be made from both the policy and managerial perspectives. Hospital size is an important feature of inefficiency. On average, the results show that it is advisable for hospitals to reorganize nonmedical staff to enhance efficiency. Further, increasing technology investment could enable higher efficiency levels.

The Structural Characteristics of Economic Network and Efficiency of Health Care in China

With the rapid development of the economy of China, the interactivity between provinces and the mobility of the population is increasing. Some patients who could have received the same treatment in their residential areas still choose to receive services in areas with higher economic development and concentrated high-quality medical resources, resulting in a huge waste of medical resources. Blindly increasing medical resources everywhere does not necessarily increase the output effectively. In this study, the data envelopment analysis (DEA) model, social network analysis (SNA), cluster analysis, and regression analysis are used to analyze the structural characteristics of the economic network structure and efficiency of health care in China. The results show that indegree and eigenvector centrality have a significant positive correlation with the efficiency of health care, and the clustering coefficient has a significant negative correlation with the efficiency of health care in China. This study uses a k-means algorithm to classify 31 provinces into three groups and extract their characteristics. As for the supply of health care resources, the government should command and dispatch the resources in the whole country through a top-down design based on the characteristics of each province.

Assessing the performance of hospitals before and after the implementation of Iran's Health Sector Evolution Plan (HSEP) using the Pabon Lasso model

Background: The health sector evolution plan was implemented in 2014 in government hospitals across the country as a part of the universal health coverage achievement programs. This study assessed the performance of hospitals before and after the implementation of this plan, using the Pabon Lasso model. Methods: The population of this study consisted of the hospitals of the country in the 2013-2015 time frame; overall, 874 hospitals (94.5% of the population) were included in the study. In order to assess performance, we used the Pabon Lasso model and hospital performance indicators (Average Length of Stay, Bed Turnover, and Bed Occupancy Rate). The data were collected from the Hospital Information System and provincial deputies of curative affairs and were then analyzed using the descriptive indicators of mean, frequency, and median in SPSS 22. Also, Paired Student T-test and ANOVA were used to compare the performance of different groups of hospitals before and after the implementation of the health sector evolution plan. Results: The implementation of the health sector evolution plan has led to a significant improvement in the three performance indicators in the hospitals of the country. Before the implementation of the health sector evolution plan, the most inefficient, inefficient, fairly efficient, and most efficient zones included 31%, 18%, 17%, and 33% of the studied hospitals, respectively. However, the implementation of the health sector evolution plan changed the percentages to 29%, 21%, 20%, and 30%, respectively. Teaching hospitals, which are governmental and are mostly located in capital cities of the provinces, were overall more inefficient than non-teaching hospitals. Conclusion: The number of the most efficient and most inefficient hospitals has decreased, and the number of average performance hospitals has increased after the implementation of the health sector evolution plan. Therefore, the health sector evolution plan has not led to an overall increase or decrease in the performance of hospitals but has reduced the difference in the performance of hospitals. Equal support of government hospitals along with financial protection against health expenses, improves the performance indicators of hospitals and reduces performance differences among them.

Multilevel Analysis of the Relationship between Ownership Structure and Technical Efficiency Frontier in the Spanish National Health System Hospitals

Objective: To evaluate the relationship between the ownership structure of hospitals and the possibility of their being positioned on the frontier of technical efficiency in the economic crisis period 2010–2012, adjusting for hospital variables and regional characteristics in the areas where the Spanish National Health System (SNHS) hospitals are located. Methods: 230 National Health System hospitals were studied over the two-year period 2010–2012 according to their ownership structure—public hospitals, private hospitals and public–private partnership (PPP)—data envelopment analysis orientated to inputs was used to measure the overall technical efficiency, pure efficiency and efficiency of scale. A generalised linear mixed model (GLMM) with binomial distribution and logit link function was used to analyse the hospital and regional variables associated with positioning on the frontier. Results: There are substantial differences between the average pure technical efficiency of public, private and PPP hospitals, as well as a greater number of PPP models being positioned on the efficiency frontier (91.67% in 2012). The odds of being positioned on the frontier are 41.7 times higher in PPP models than in public hospitals. The average annual household income per region is related to the greater odds of hospitals being positioned on the frontier of efficiency. Conclusions: During the most acute period of recession in the Spanish economy, PPP formulas favoured hospital efficiency, by increasing the odds of being positioned on the frontier of efficiency when compared to private and public hospitals. The position on the frontier of efficiency of a hospital is related to the wealth of its region.

Assessment of technical efficiency of public hospitals in Turkey

BACKGROUND

Turkish public hospitals have been subjected to health care reform because of increasing cost pressure, inequities in access to health care, poor quality of care and limited patient responsiveness in the last three decades. This study investigates the impact of recent hospital reforms on the efficiency of public hospitals.

METHODS

The study provides a comprehensive evaluation of the efficiency of Turkish hospitals by using Data Envelopment Analysis (DEA). The estimation of efficiency of 669 public hospitals of Turkey is performed by an output-oriented model of DEA under the assumption of variable return-to-scale by using data collected from the Ministry of Health (MoH) over the period 2013-17.

RESULTS

The average efficiency score is equal to 0.83 for all MoH hospitals. Considering the hospital type, the efficiency scores of training and research hospitals are higher than those of the general and branch hospitals. In addition, considering the hospital size, huge-scale hospitals have the highest efficiency score in all years. Moreover, overcrowded regions such as Marmara and South-eastern Anatolia regions had higher efficiency scores than other geographical regions.

CONCLUSIONS

The results indicate that recent health reforms did not significantly enhance hospital efficiency. Thus, policymakers and managers should take the necessary precautions to increase hospital efficiency.

Technical efficiency of public district hospitals in Bangladesh: a data envelopment analysis

BACKGROUND

District hospitals (DHs) provide secondary level of healthcare to a wide range of population in Bangladesh. Efficient utilization of resources in these secondary hospitals is essential for delivering health services at a lower cost. Therefore, we aimed to estimate the technical efficiency of the DHs in Bangladesh.

METHODS

We used input-oriented data envelopment analysis method to estimate the variable returns to scale (VRS) and constant returns to scale (CRS) technical efficiency of the DHs using data from Local Health Bulletin, 2015. In this model, we considered workforce as well as number of inpatient beds as input variables and number of inpatient, outpatient, and maternal services provided by the DHs as output variables. A Tobit regression model was applied for assessing the association of institutional and environmental characteristics with the technical efficiency scores.

RESULTS

The average scale, VRS, and CRS technical efficiency of the DHs were estimated to 85%, 92%, and 79% respectively. Population size, poverty headcount, bed occupancy ratio, administrative divisions were significantly associated with the technical efficiency of the DHs. The mean VRS and CRS technical efficiency demonstrated that the DHs, on an average, could reduce their input mix by 8% and 21% respectively while maintaining the same level of output.

CONCLUSION

Since the average technical efficiency of the DHs was 79%, there is little scope for overall improvements in these facilities by adjusting inputs. Therefore, we recommend to invest further in the DHs for improvement of services. The Ministry of Health and Family Welfare (MoHFW) should improve the efficiency in resource allocation by setting an input-mix formula for DHs considering health and socio-economic indicators (e.g., population density, poverty, bed occupancy ratio). The formula can be designed by learning from the input mix in the more efficient DHs. The MoHFW should conduct this kind of benchmarking study regularly to assess the efficiency level of health facilities which may contribute to reduce the wastage of resources and consequently to provide more affordable and accessible public hospital care.

Technical efficiency and its influencing factors in Malaysian hospital pharmacy services

Various pharmacy services are offered in public health facilities, ranging from distributive activities (dispensing) to patient-oriented services (pharmaceutical care). These activities are monitored through indicators established at the national level. In Malaysia, the indicators have not been transformed into a measurement of hospital pharmacy service efficiency. The main objectives of this study were to assess the relative performance of hospital pharmacy services and to investigate the factors that may affect the performance levels. Double-bootstrap data envelopment analysis was applied to measure the technical efficiency levels of 124 public hospital pharmacies in 2014. An input-oriented variable returns to scale model was adopted in the study, while bootstrap truncated regression was conducted to identify the factors that may explain the differences in the efficiency levels. The average bias-corrected technical efficiency score varies according to the hospital size (0.84, 0.78 and 0.82 in small, medium and large hospitals, respectively). The hospital size, hospital age, urban location and information technology are important determinants of the efficiency levels. The study contributes to establishing baseline technical efficiency information for public hospital pharmacy services in Malaysia. The measurement of hospital pharmacy efficiency can guide future policy making to improve performance and ensure the optimum level of available resources.

Fuzzy DEA-based classifier and its applications in healthcare management

Nonlinear fuzzy classification models have better classification performance than linear fuzzy classifiers. In many nonlinear fuzzy classification problems, piecewise-linear fuzzy discriminant functions can approximate nonlinear fuzzy discriminant functions. In this paper, we first build fuzzy classifier based on data envelopment analysis (DEA) for incremental separable fuzzy training data, which can be widely applied in the healthcare management with fuzzy attributes, then we apply the proposed fuzzy DEA-based classifier in the diagnosis of Coronary with fuzzy symptoms and the classification of breast cancer dataset with fuzzy disturbance. Numerical experiments show the proposed fuzzy DEA-based classifier is accurate and robust.

A methodology to design a performance management system in preventive care

Background

Preventive care has gained increasing attention in health reforms around the world due to its ability to reduce the burden of disease and to save health costs. Nevertheless, there is a gap in terms of the development of reliable systems to measure and evaluate performance of preventive care in order to support decision-making and increase service outcomes. The aim of this study is to define a methodology for designing a performance management system (PMS) in order to effectively support the planning, control and evaluation of preventive care and to identify the factors that influence such a process.

Methods

The methodology is based on the participatory action research approach, which implies collaboration between researchers and practitioners. The study was articulated in four phases and carried out in an Italian regional healthcare system that was undergoing a major reorganization process.

Results

The findings provide insights into the peculiarities that affect preventive care and highlight two categories of critical factors: general issues regarding the process and specific issues regarding preventive care. The first category includes the importance of interactions between academics, physicians and policy-makers, the impact of workloads and red tape on employee involvement and the increased conservation mechanisms during periods of institutional change. The second category concerns the strong heterogeneity of preventive activities within health organizations, the huge amount of regulations and the incompleteness of information systems.

Conclusion

The development of a PMS for preventive care can best be served by collaborative methods that involve academics, professionals and policy-makers, whose roles and responsibilities must be clearly defined, and by an improvement in transparency and communication within organizations in order to enhance the involvement of different professionals at appropriate times and in appropriate ways. Key recommendations that may improve the maintenance and use of information systems are proposed to policy-makers.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3837-8) contains supplementary material, which is available to authorized users.

Organizational Factors Associated With Technical Efficiency of Nursing Care in US Intensive Care Units

BACKGROUND

Few studies have evaluated technical efficiency of nursing care, and no such studies have been conducted in intensive care units (ICUs).

PURPOSE

To explore relative technical efficiency of US ICUs and identify organizational factors associated with efficiency in providing quality of nursing care.

METHODS

A total of 404 adult ICUs from the 2014 National Database of Nursing Quality Indicators were included. Data envelopment analysis was used to estimate technical efficiency, and multilevel modeling was employed to determine effects of organizational factors on efficiency.

RESULTS

Nurse-to-patient ratio showed the strongest positive correlation with technical efficiency. Units in non-Magnet and small-size hospitals had higher technical efficiency than those in Magnet and medium- or large-size hospitals.

CONCLUSIONS

A higher nurse-to-patient ratio greatly improved technical efficiency of nursing care in ICUs and the effect differed between hospitals. Administrators and policy makers can translate the study findings into management strategies to provide efficient nursing care in ICUs.

Quality and resource efficiency in hospital service provision: A geoadditive stochastic frontier analysis of stroke quality of care in Germany

We specify a Bayesian, geoadditive Stochastic Frontier Analysis (SFA) model to assess hospital performance along the dimensions of resources and quality of stroke care in German hospitals. With 1,100 annual observations and data from 2006 to 2013 and risk-adjusted patient volume as output, we introduce a production function that captures quality, resource inputs, hospital inefficiency determinants and spatial patterns of inefficiencies. With high relevance for hospital management and health system regulators, we identify performance improvement mechanisms by considering marginal effects for the average hospital. Specialization and certification can substantially reduce mortality. Regional and hospital-level concentration can improve quality and resource efficiency. Finally, our results demonstrate a trade-off between quality improvement and resource reduction and substantial regional variation in efficiency.

Measuring efficiency of community health centers: a multi-model approach considering quality of care and heterogeneous operating environments

Over 1300 federally-qualified health centers (FQHCs) in the US provide care to vulnerable populations in different contexts, addressing diverse patient health and socioeconomic characteristics. In this study, we use data envelopment analysis (DEA) to measure FQHC performance, applying several techniques to account for both quality of outputs and heterogeneity among FQHC operating environments. To address quality, we examine two formulations, the Two-Model DEA approach of Shimshak and Lenard (denoted S/L), and a variant of the Quality-Adjusted DEA approach of Sherman and Zhou (denoted S/Z). To mitigate the aforementioned heterogeneities, a data science approach utilizing latent class analysis (LCA) is conducted on a set of metrics not included in the DEA, to identify latent typologies of FQHCs. Each DEA quality approach is applied in both an aggregated (including all FQHCs in a single DEA model) and a partitioned case (solving a DEA model for each latent class, such that an FQHC is compared only to its peer group). We find that the efficient frontier for the aggregated S/L approach disproportionately included smaller FQHCs, whereas the aggregated S/Z approach's reference set included many larger FQHCs. The partitioned cases found that both the S/L and S/Z aggregated models disproportionately disfavored (different) members of certain classes with respect to efficiency scores. Based on these results, we provide general insights into the trade-offs of using these two models in conjunction with a clustering approach such as LCA.

Quality and technical efficiency do not evolve hand in hand in Spanish hospitals: Observational study with administrative data

Objective

Recent evidence on the Spanish National Health System (SNHS) reveals a considerable margin for hospital efficiency and quality improvement. However, those studies do not consider both dimensions together. This study aims at jointly studying both technical efficiency (TE) and quality, classifying the public SNHS hospitals according to their joint performance.

Methods

Stochastic frontier analysis is used to estimate TE and multilevel logistic regressions to build a low-quality composite measure (LQ), which considers in-hospital mortality and safety events. All hospitalizations discharged in Spain in 2003 and 2013, in 179 acute-care general hospitals, were studied. Four scenarios of resulting performance were built setting yearly medians as thresholds for the overall sample, and according to hospital-complexity strata.

Results

Overall, since 2003, median TE improved and LQ reduced -from TE₂₀₀₃:0.89 to TE₂₀₁₃:0.93 and, from LQ₂₀₀₃:42.6 to LQ₂₀₁₃:27.7 per 1,000 treated patients. The time estimated coefficient showed technical progress over the period. TE across hospitals showed scarce variability (CV₂₀₀₃:0.08 vs. CV₂₀₁₃:0.07), not so the rates of LQ (CV₂₀₀₃:0.64 vs. CV₂₀₁₃:0.76). No correlation was found between TE values and LQ rates. When jointly considering technical efficiency and quality, hospitals dealing with the highest clinical complexity showed the highest chance to be placed in optimal scenarios, also showing lesser variability between hospitals.

Conclusions

Efficiency and quality have improved in Spanish public hospitals. Not all hospitals experiencing improvements in efficiency equally improved their quality. The joint analysis of both dimensions allowed identifying those optimal hospitals according to this trade-off.

Strategies of High-Performing Teaching Hospitals

Teaching hospitals are large and complex, and under constant financial pressure. In this study, we examine the financial performance of 80 large teaching hospitals in the 20 largest cities in the U.S. over the last five years, to identify which strategic and operational management factors separate high-performing hospitals from lower-performing ones. Results suggest that growth strategies should continue to be sought for improving long-term financial condition. Operational efficiency was less important than market share, economic status of surrounding community, hospital size, and teaching intensity. This study's findings should help guide strategic planning for teaching hospitals.

Impact of Medicare Advantage penetration and hospital competition on technical efficiency of nursing care in US intensive care units

This study aimed to evaluate technical efficiency of US intensive care units and determine the effects of environmental factors on technical efficiency in providing quality of nursing care. Data were obtained from the 2014 National Database of Nursing Quality Indicators and the Centers for Medicare and Medicaid Services. Data envelopment analysis was used to estimate technical efficiency for each intensive care unit. Multilevel modeling was used to determine the effects of environmental factors on technical efficiency. Overall, Medicare Advantage penetration and hospital competition in a market did not create pressure for intensive care units to become more efficient by reducing their inputs. However, these 2 environmental factors showed positive influences on technical efficiency in intensive care units with certain levels of technical efficiency. The implications of the study results for management strategies and health policy may vary according to the levels of technical efficiency in intensive care units. Further studies are needed to examine why and how intensive care units with particular levels of technical efficiency are differently affected by certain environmental factors.

Equity and efficiency of medical service systems at the provincial level of China's mainland: a comparative study from 2009 to 2014

BACKGROUND

The astonishing economic achievements of China in the past few decades have remarkably increased not only the quantity and quality of medical services but also the inequalities in health resources allocation across regions and inefficiency of the medical service delivery.

METHODS

A descriptive analysis was used to compare the inequities in inputs and outputs of the provincial medical service systems, a non-radial super-efficiency data envelopment analysis model was then used to estimate the efficiency, and a regression analysis of the panel data was used to explore the determinants.

RESULTS

The inputs and outputs of most provincial medical service systems increased gradually from 2009 to 2014. Overall, the eastern region allocated more human and capital resources than the other two regions, and produced more than 50% of the total outpatient and emergency room visits, whereas the western region produced more inpatient services (about 30% of the total volume of inpatient services) according to the distribution of the population. The average efficiency scores of the provincial medical systems in China's mainland were 0.895, 0.927, 0.929, 0.963, 0.977 and 0.968 from 2009 to 2014, with a slight average improvement of 1.60%. The efficiency score of each provincial medical service system varied greatly from one another: Tibet (1.475 ± 0.057) performed extremely well, whereas several others including Heilongjiang (0.579 ± 0.001) performed poorly. Furthermore, the proportion of high-class medical facilities was negatively associated with efficiency, whereas the proportion of the vulnerable population, the per capita Gross Domestic Product, the proportion of the illiterate population and the improvement of primary health care had positive effects on efficiency.

CONCLUSION

Inequity in health resources allocation and service provision existed across the regions, but not all the gaps have begun to narrow since 2009. The difference of efficiency was great among provincial medical service systems but minor across regions, and the score changed very little over time. More importantly, the central region held the lowest average efficiency score in the past 6 years, while the western region held the largest average efficiency score at the first 5 years, which should receive enough attention of the government and decision-makers. In practice, efficiency was related to many complicated factors, indicating that the improvement of efficiency is a complex and iterative process that requires the strong cooperation of many sectors.

Integrated Analysis of Healthcare Efficiency: A Systematic Review

Data Envelopment Analysis (DEA) has been used as a performance measurement tool in efficiency assessment of healthcare systems. However, over the years, researchers and health practitioners presented the theoretical and methodological limitations of DEA that limits the full view of healthcare efficiency. To address these limitations, a commonly used strategy is to integrate other statistical methods and techniques with DEA to provide better efficiency evaluation. This paper reviews 57 studies with DEA applications in the healthcare industry to illustrate the integrated analysis of healthcare efficiency. With DEA as the central method, regression models in conjunction with statistical tests are commonly used. Input-oriented radial DEA models using predominantly capacity-related inputs and activity-related outputs and following either constant return to scale or variable return to scale assumptions are mostly applied to measure healthcare efficiency.

Factors Related to Healthcare Service Quality in Long-term Care Hospitals in South Korea: A Mixed-methods Study

Objectives

The environment of long-term care hospitals (LTCHs) is critical to the management of the quality of their services and to patient safety, as highlighted by international studies. However, there is a lack of evidence on this topic in South Korea. This study aimed to examine the factors affecting healthcare quality in LTCHs and to explore the effectiveness of their quality management.

Methods

This study used a mixed methods approach with quantitative data collected in a national survey and qualitative data from semi-structured interviews with practice-based managers. The samples included 725 nationally representative LTCHs in South Korea for the quantitative analysis and 15 administrators for the in-depth interviews.

Results

A higher installation rate of patient-safety and hygiene-related facilities and staff with longer-tenures, especially nurses, were more likely to have better healthcare quality and education for both employees and patients.

Conclusion

The need for patient-safety- and hygiene-related facilities in LTCHs that serve older adults reflects their vulnerability to certain adverse events (e.g., infections). Consistent and skillful nursing care to improve the quality of LTCHs can be achieved by developing relevant educational programs for staff and patients, thereby strengthening the relationships between them.

A robust analysis of hospital efficiency and factors affecting variability

The objectives of this paper are to use data envelopment analysis to measure hospital inefficiency in a way that accounts for patient outcomes and to study the association between organizational factors, such as hospital-physicians integration level and teaching status, and market competition with hospital inefficiency. We apply the robust data envelopment analysis approach to a sample of private (both not-for-profit and for-profit) hospitals operating in the United States. Our data envelopment analysis model includes mortality and readmission rates as bad outputs and admissions, surgeries, emergency room, and other visits as good outputs. Therefore, our measurement of hospital inefficiency accounts for quality. We then use a subsampling regression analysis to determine the predictors of hospital inefficiency. For-profit, fully integrated and teaching hospitals were more efficient than their counterparts. Also hospitals located in more competitive markets were more efficient than those located in less competitive markets. Incorporating quality in the measurement of hospital efficiency is key for producing valid efficiency scores. Hospitals in less competitive markets need to improve their efficiency levels. Moreover, high levels of hospital physician integration might be instrumental in ensuring that hospitals achieve their efficiency goals.

Evaluating the Relationship between Productivity and Quality in Emergency Departments

BACKGROUND

In the United States, emergency departments (EDs) are constantly pressured to improve operational efficiency and quality in order to gain financial benefits and maintain a positive reputation.

OBJECTIVES

The first objective is to evaluate how efficiently EDs transform their input resources into quality outputs. The second objective is to investigate the relationship between the efficiency and quality performance of EDs and the factors affecting this relationship.

METHODS

Using two data sources, we develop a data envelopment analysis (DEA) model to evaluate the relative efficiency of EDs. Based on the DEA result, we performed multinomial logistic regression to investigate the relationship between ED efficiency and quality performance.

RESULTS

The DEA results indicated that the main source of inefficiencies was working hours of technicians. The multinomial logistic regression result indicated that the number of electrocardiograms and X-ray procedures conducted in the ED and the length of stay were significantly associated with the trade-offs between relative efficiency and quality. Structural ED characteristics did not influence the relationship between efficiency and quality.

CONCLUSIONS

Depending on the structural and operational characteristics of EDs, different factors can affect the relationship between efficiency and quality.

Efficiency and optimal size of hospitals: Results of a systematic search

Background

National Health Systems managers have been subject in recent years to considerable pressure to increase concentration and allow mergers. This pressure has been justified by a belief that larger hospitals lead to lower average costs and better clinical outcomes through the exploitation of economies of scale. In this context, the opportunity to measure scale efficiency is crucial to address the question of optimal productive size and to manage a fair allocation of resources.

Methods and findings

This paper analyses the stance of existing research on scale efficiency and optimal size of the hospital sector. We performed a systematic search of 45 past years (1969–2014) of research published in peer-reviewed scientific journals recorded by the Social Sciences Citation Index concerning this topic. We classified articles by the journal’s category, research topic, hospital setting, method and primary data analysis technique. Results showed that most of the studies were focussed on the analysis of technical and scale efficiency or on input / output ratio using Data Envelopment Analysis. We also find increasing interest concerning the effect of possible changes in hospital size on quality of care.

Conclusions

Studies analysed in this review showed that economies of scale are present for merging hospitals. Results supported the current policy of expanding larger hospitals and restructuring/closing smaller hospitals. In terms of beds, studies reported consistent evidence of economies of scale for hospitals with 200–300 beds. Diseconomies of scale can be expected to occur below 200 beds and above 600 beds.

Identifying congestion levels, sources and determinants on intensive care units: the Portuguese case

Healthcare systems are facing a resources scarcity so they must be efficiently managed. On the other hand, it is commonly accepted that the higher the consumed resources, the higher the hospital production, although this is not true in practice. Congestion on inputs is an economic concept dealing with such situation and it is defined as the decreasing of outputs due to some resources overuse. This scenario gets worse when inpatients' high severity requires a strict and effective resources management, as happens in Intensive Care Units (ICU). The present paper employs a set of nonparametric models to evaluate congestion levels, sources and determinants in Portuguese Intensive Care Units. Nonparametric models based on Data Envelopment Analysis are employed to assess both radial and non-radial (in)efficiency levels and sources. The environment adjustment models and bootstrapping are used to correct possible bias, to remove the deterministic nature of nonparametric models and to get a statistical background on results. Considerable inefficiency and congestion levels were identified, as well as the congestion determinants, including the ICU specialty and complexity, the hospital differentiation degree and population demography. Both the costs associated with staff and the length of stay are the main sources of (weak) congestion in ICUs. ICUs management shall make some efforts towards resource allocation to prevent the congestion effect. Those efforts shall, in general, be focused on costs with staff and hospital days, although these congestion sources may vary across hospitals and ICU services, once several congestion determinants were identified.

Nurses' perspectives on how operational leaders influence function-focused care for hospitalised older people

AIMS

To explore nurses' perspectives on how leaders influence function-focused care, defined as care that preserves and restores older people's functional abilities.

BACKGROUND

Hospitalised older people are at risk of functional decline. Although leaders have the potential to influence function-focused care, few studies have explored nurses' perspectives on how leaders influence function-focused care.

METHODS

Thirteen focus groups were held with 57 acute care nurses. Semi-structured questions prompted discussion on nurses' perspectives, needs and strategies to meet their needs. Data were thematically analysed.

RESULTS

Three themes were identified: (1) the emphasis in hospitals is on moving older people quickly through the system, not supporting their functioning; (2) leaders are generally seen as too disconnected from practice to design system efficiency initiatives that support older people's functioning and nurses' provisioning of function-focused care; and (3) leadership strategies to better support nurses in providing function-focused care to older people in the context of system efficiency.

CONCLUSIONS

Leaders should connect with practice to devise age-sensitive efficiency initiatives that support function-focused care. Nurses need support from leaders in four areas to provide function-focused care to older people in the current hospital context.

IMPLICATIONS

The findings provide direction on how leaders can facilitate function-focused care in the current health-care environment emphasising system efficiency.

Evaluation of performance and impacts of maternal and child health hospital services using Data Envelopment Analysis in Guangxi Zhuang Autonomous Region, China: a comparison study among poverty and non-poverty county level hospitals

BACKGROUND

As the core of the county-level Maternal and Child Health Hospitals (MCHH) in rural areas of China, the service efficiency affects the fairness and availability of healthcare services. This study aims to identify the determinants of hospital efficiency and explore how to improve the performance of MCHH in terms of productivity and efficiency.

METHODS

Data was collected from a sample of 32 county-level MCHHs of Guangxi in 2014. Firstly, we specified and measured the indicators of the inputs and outputs which represent hospital resources expended and its profiles respectively. Then we estimated the efficiency scores using Data Envelopment Analysis (DEA) for each hospital. Efficiency scores were decomposed into technical, scale and congestion components, and the potential output increases and/or input reductions were also estimated in this model, which would make relatively inefficient hospitals more efficient. In the second stage, the estimated efficiency scores are regressed against hospital external and internal environment factors using a Tobit model. We used DEAP (V2.1) and R for data analysis.

RESULTS

The average scores of technical efficiency, net technical efficiency (managerial efficiency) and scale efficiency of the hospitals were 0.875, 0.922 and 0.945, respectively. Half of the hospitals were efficient, and 9.4 % and 40.6 % were weakly efficient and inefficient, respectively. Among the low-productiveness hospitals, 61.1 % came from poor counties (Poor counties in this article are in the list of key poverty-stricken counties at the national level, published by The State Council Leading Group Office of Poverty Alleviation and Development, 2012). The total input indicated that redundant medical resources in poverty areas were significantly higher than those in non-poverty areas. The Tobit regression model showed that the technical efficiency was proportional to the total annual incomes, the number of discharge patients, and the number of outpatient and emergency visits, while it was inversely proportional to total expenditure and the actual number of open beds. Technical efficiency was not associated with number of health care workers.

CONCLUSION

The overall operational efficiency of the county-level MCHHs in Guangxi was low and needs to be improved. Regional economic differences affect the performances of hospitals. Health administrations should adjust and optimize the resource investments for the different areas. For the hospitals in poverty areas, policy-makers should not only consider the hardware facilities investment, but also the introduction of advanced techniques and high-level medical personnel to improve their technical efficiency.

Analyzing demand-side efficiency in global health: an application to maternal care in Vietnam

This article investigates demand-side efficiency in global health-or the efficiency with which health system users convert public health resources into health outcomes. We introduce and explain the concept of demand-side efficiency as well as quantitative methods to empirically estimate it. Using a robust nonparametric form of technical efficiency analysis, we estimate demand side efficiency and its social determinants. We pilot these methods looking at how efficiently pregnant women in Northern Vietnam convert public health resources into appropriate maternal care as defined by national policy. We find that women who live in non-mountainous geographies, who are formally employed, who are pregnant with a boy and who are ethnic minorities are all more likely to be efficient at achieving appropriate care. We find no significant association between wealth or education and efficiency. Our results suggest that, in the Vietnamese context, women who are the most likely to achieve appropriate maternal care, are not necessarily the most likely to do so efficiently. Women who live in non-mountainous geographies and who are formally employed are both more likely to achieve appropriate care and to do so efficiently. Yet ethnic minority women, who do not systematically achieve better care, are more likely to be efficient or to achieve better care when compared with those with the same endowment of public health resources. On the methodological level, the pilot highlights that this approach can provide useful information for policy by identifying which groups of people are more and less likely to be efficient. By understanding which groups are more likely to be efficient-and in turn how and why-it may be possible to devise policies to promote the drivers of, or conversely address the constraints to, optimizing demand-side efficiency.

Evaluating Technical Efficiency of Nursing Care Using Data Envelopment Analysis and Multilevel Modeling

Data envelopment analysis (DEA) is an advantageous non-parametric technique for evaluating relative efficiency of performance. This article describes use of DEA to estimate technical efficiency of nursing care and demonstrates the benefits of using multilevel modeling to identify characteristics of efficient facilities in the second stage of analysis. Data were drawn from LTCFocUS.org , a secondary database including nursing home data from the Online Survey Certification and Reporting System and Minimum Data Set. In this example, 2,267 non-hospital-based nursing homes were evaluated. Use of DEA with nurse staffing levels as inputs and quality of care as outputs allowed estimation of the relative technical efficiency of nursing care in these facilities. In the second stage, multilevel modeling was applied to identify organizational factors contributing to technical efficiency. Use of multilevel modeling avoided biased estimation of findings for nested data and provided comprehensive information on differences in technical efficiency among counties and states.

Benchmarking hospitals through a web based platform

Purpose

– In a context of international economic crisis the improvement in the efficiency and productivity of public services is seen as a way to maintain high-quality levels at lower costs. Increased productivity can be promoted through benchmarking exercises, where key performance indicators (KPIs), individually or aggregated, are used to compare health units. The purpose of this paper is to describe a benchmarking platform, called Hospital Benchmarking (HOBE), where hospital’s services are used as the unit of analysis.

Design/methodology/approach

– HOBE platform includes a set of managerial indicators through which hospital services’ are compared. The platform also benchmarks services through aggregate service indicators, and provides an aggregate measure of hospital’s performance based on a composite indicator of the service’s performances. These aggregate indicators were obtained through data envelopment analysis (DEA).

Findings

– Some results are presented for Portuguese hospitals for the trial years of 2008 and 2009, for which data is publicly available. Details for the service-level analysis are provided for a sample hospital, as well as details on the aggregate performance resulting from services performances.

Practical implications

– HOBE’s features and outcomes show that the platform can be used to guide management actions and to support the design of health policies by administrative authorities, provided that good quality and timely data are available, and that hospitals are involved in the design of the KPIs.

Originality/value

– The platform is innovative in the sense that it bases its analysis on hospital’s services, which are in general more comparable among hospitals than indicators of hospital overall performance. In addition, it makes use of DEA to aggregate performance indicators, allowing for user choice in the inputs and outputs to be aggregated, and it proposes a novel model to aggregate service’s efficiencies into a single measure of hospital performance.

A Multi-Method Study of the Geriatric Learning Needs of Acute Care Hospital Nurses in Ontario, Canada

Older people are at risk of experiencing functional decline and related complications during hospitalization. In countries with projected increases in age demographics, preventing these adverse consequences is a priority. Because most Canadian nurses have received little geriatrics content in their basic education, understanding their learning needs is fundamental to preparing them to respond to this priority. This two-phased multi-method study identified the geriatrics learning needs and strategies to address the learning needs of acute care registered nurses (RNs) and registered practical nurses (RPNs) in the province of Ontario, Canada. In Phase I, a survey that included a geriatric nursing knowledge scale was completed by a random sample of 2005 Ontario RNs and RPNs. Average scores on the geriatric nursing knowledge scale were in the "neither good nor bad" range, with RNs demonstrating slightly higher scores than RPNs. In Phase II, 33 RN and 24 RPN survey respondents participated in 13 focus group interviews to help confirm and expand survey findings. In thematic analysis, three major themes were identified that were the same in RNs and RPNs: (a) geriatric nursing is generally regarded as simple and custodial, (b) older people's care is more complex than is generally appreciated, and (c) in the current context, older people's care is best learned experientially and in brief on-site educational sessions. Healthcare providers, policy-makers, and educators can use the findings to develop educational initiatives to prepare RNs and RPNs to respond to the needs of an aging hospital population.

Technical efficiency and productivity of Chinese county hospitals: an exploratory study in Henan province, China

OBJECTIVES

Chinese county hospitals have been excessively enlarging their scale during the healthcare reform since 2009. The purpose of this paper is to examine the technical efficiency and productivity of county hospitals during the reform process, and to determine whether, and how, efficiency is affected by various factors.

SETTING AND PARTICIPANTS

114 sample county hospitals were selected from Henan province, China, from 2010 to 2012.

OUTCOME MEASURES

Data envelopment analysis was employed to estimate the technical and scale efficiency of sample hospitals. The Malmquist index was used to calculate productivity changes over time. Tobit regression was used to regress against 4 environmental factors and 5 institutional factors that affected the technical efficiency.

RESULTS

(1) 112 (98.2%), 112 (98.2%) and 104 (91.2%) of the 114 sample hospitals ran inefficiently in 2010, 2011 and 2012, with average technical efficiency of 0.697, 0.748 and 0.790, respectively. (2) On average, during 2010-2012, productivity of sample county hospitals increased by 7.8%, which was produced by the progress in technical efficiency changes and technological changes of 0.9% and 6.8%, respectively. (3) Tobit regression analysis indicated that government subsidy, hospital size with above 618 beds and average length of stay assumed a negative sign with technical efficiency; bed occupancy rate, ratio of beds to nurses and ratio of nurses to physicians assumed a positive sign with technical efficiency.

CONCLUSIONS

There was considerable space for technical efficiency improvement in Henan county hospitals. During 2010-2012, sample hospitals experienced productivity progress; however, the adverse change in pure technical efficiency should be emphasised. Moreover, according to the Tobit results, policy interventions that strictly supervise hospital bed scale, shorten the average length of stay and coordinate the proportion among physicians, nurses and beds, would benefit hospital efficiency.

Efficiency of health care in state correctional institutions

Little is known about the efficiency of health care in correction settings. This article reports an efficiency analysis of health care in state correctional institutions (SCIs) in a single, mid-Atlantic state from 2003 to 2006. A two-stage data envelopment analysis was used to estimate the technical efficiency of prison health care and determine inmate and institutional characteristics that were associated with efficiency. Our output variable was the number of infirmary inpatient days for each year of study. The input variable for the first stage was the sum of personnel medical staff costs and other medical operating costs. SCIs with more white prisoners, older prisoners, and higher proportions of inmates with parole violations were significantly less efficient in their provision of health care than other SCIs. There were no SCI characteristics that were predictive of efficiency. These results suggest that healthcare efficiency in corrections may decline as the prison population continues to age.

Validating and determining the weight of items used for evaluating clinical governance implementation based on analytic hierarchy process model

BACKGROUND

The purpose of implementing a system such as Clinical Governance (CG) is to integrate, establish and globalize distinct policies in order to improve quality through increasing professional knowledge and the accountability of healthcare professional toward providing clinical excellence. Since CG is related to change, and change requires money and time, CG implementation has to be focused on priority areas that are in more dire need of change. The purpose of the present study was to validate and determine the significance of items used for evaluating CG implementation.

METHODS

The present study was descriptive-quantitative in method and design. Items used for evaluating CG implementation were first validated by the Delphi method and then compared with one another and ranked based on the Analytical Hierarchy Process (AHP) model.

RESULTS

The items that were validated for evaluating CG implementation in Iran include performance evaluation, training and development, personnel motivation, clinical audit, clinical effectiveness, risk management, resource allocation, policies and strategies, external audit, information system management, research and development, CG structure, implementation prerequisites, the management of patients' non-medical needs, complaints and patients' participation in the treatment process. The most important items based on their degree of significance were training and development, performance evaluation, and risk management. The least important items included the management of patients' non-medical needs, patients' participation in the treatment process and research and development.

CONCLUSION

The fundamental requirements of CG implementation included having an effective policy at national level, avoiding perfectionism, using the expertise and potentials of the entire country and the coordination of this model with other models of quality improvement such as accreditation and patient safety.

Explaining hospital performance via the cube one framework

Purpose

– The purpose of this paper is to introduce a relatively new theoretical perspective – the Cube One framework – which along with the Cube One Input-Output model provide a conceptual explanation of overall hospital performance. Further, this framework provides information pertinent to organizational improvement.

Design/methodology/approach

– Multiple sources of data, including the US Department of Health and Human Services’ Centers for Medicare & Medicaid Services (CMS) patient satisfaction ratings, the “US News & World Report’s Best Hospitals” (disaggregated) ratings, the American Hospital Directory efficiency metrics, and Glassdoor employee satisfaction ratings, were used to test five hypotheses.

Findings

– Three sets of capabilities: patient-, employee-, and efficiency-related were positively associated with hospital performance. The model explained 38 percent of the variance in hospital performance.

Practical implications

– By adopting a multi-disciplinary, three-dimensional approach, the framework allows hospital leadership to diagnose areas for improving overall performance.

Social implications

– Hospitals have divergent stakeholders such as patients, patient’s families, employees, government agencies, insurance companies, administrators, boards of directors, and the community. Management capabilities regarding patients, employees, and the organization itself are crucial to the success of hospitals and all who depend on them.

Originality/value

– By utilizing a three-dimensional approach, the Cube One framework views performance from multiple perspectives.