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

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.

Healthcare efficiency assessment using DEA analysis in the Slovak Republic

A regional disparity is becoming increasingly important growth constraint. Policy makers need quantitative knowledge to design effective and targeted policies. In this paper, the regional efficiency of healthcare facilities in Slovakia is measured (2008-2015) using data envelopment analysis (DEA). The DEA is the dominant approach to assessing the efficiency of the healthcare system but also other economic areas. In this study, the window approach is introduced as an extension to the basic DEA models to evaluate healthcare technical efficiency in individual regions and quantify the basic regional disparities and discrepancies. The window DEA method was chosen since it leads to increased discrimination on results especially when applied to small samples and it enables year-by-year comparisons of the results. Two stable inputs (number of beds, number of medical staff), three variable inputs (number of all medical equipment, number of magnetic resonance (MR) devices, number of computed tomography (CT) devices) and two stable outputs (use of beds, average nursing time) were chosen as production variable in an output-oriented 4-year window DEA model for the assessment of technical efficiency in 8 regions. The database was made available from the National Health Information Center and the Slovak Statistical Office, as well as from the online databases Slovstat and DataCube. The aim of the paper is to quantify the impact of the non-standard Data Envelopment Analysis (DEA) variables as the use of medical technologies (MR, CT) on the results of the assessment of the efficiency of the healthcare facilities and their adequacy in the evaluation of the monitored processes. The results of the analysis have shown that there is an indirect dependence between the values of the variables over time and the results of the estimated efficiency in all regions. The regions that had low values of the variables over time achieved a high degree of efficiency and vice versa. Interesting knowledge was that the gradual addition of variables number of MR, number of CT and number of medical devices together, to the input side did not have a significant impact on the overall estimated efficiency of healthcare facilities.

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.

Expanding the breadth of Medicare: learning from Australia

The design of Australia’s Medicare programme was based on the Canadian scheme, adapted somewhat to take account of differences in the constitutional division of powers in the two countries and differences in history. The key elements are very similar: access to hospital services without charge being the core similarity, universal coverage for necessary medical services, albeit with a variable co-payment in Australia, the other. But there are significant differences between the two countries in health programmes – whether or not they are labelled as ‘Medicare’. This paper discusses four areas where Canada could potentially learn from Australia in a positive way. First, Australia has had a national Pharmaceutical Benefits Scheme for almost 70 years. Second, there have been hesitant extensions to Australia’s Medicare to address the increasing prevalence of people with chronic conditions – extensions which include some payments for allied health professionals, ‘care coordination’ payments, and exploration of ‘health care homes’. Third, Australia has a much more extensive system of support for older people to live in their homes or to move into supported residential care. Fourth, Australia has gone further in driving efficiency in the hospital sector than has Canada. Finally, the paper examines aspects of the Australian health care system that Canada should avoid, including the very high level of out-of-pocket costs, and the role of private acute inpatient provision.

The impact of healthcare reform on the efficiency of public county hospitals in China

BACKGROUND

The new round of Healthcare Reform in China has implemented over 3 years since 2009, and promoted greatly the development of public county hospitals. The purpose of this study is to evaluate county hospitals efficiency before and after the healthcare reform, and further assess the reform effectiveness through the comparative analysis of the efficiency.

METHODS

Data envelopment analysis (DEA) was employed to calculate the efficiency of 1105 sample hospitals which were selected from 31 provinces of China, also, Tobit regression was used to regress against those main external environmental factors.

RESULTS

Our results show that the scales and amounts of service of hospitals had increased sharply, however, the efficiency was relatively low and decreased slightly from 2008 to 2012. Thirteen (1.18%) in 2008 and six (0.54%) hospitals in 2012 were defined as technically efficient, and the average scores were 0.2916 and 0.2503. The technical efficiency average score of the post-reform was significantly less than that of the pre-reform (p < 0.001), and the score of eastern region was highest and the western was lowest among three regions of China.

CONCLUSIONS

It suggests the reform had not well improved county hospital efficiency although hospitals have reached a fair developing scale, and the corresponding policies and measures should be put into effect for improving efficiency, especially in the level and structure of health investment, operation and supervision mechanism of county hospitals.

Hospital Policy and Productivity - Evidence from German States

Total factor productivity (TFP) growth allows for additional healthcare services under restricted resources. We examine whether hospital policy can stimulate hospital TFP growth. We exploit variation across German federal states in the period 1993-2013. State governments decide on hospital capacity planning (number of hospitals, departments, and beds), ownership, medical students, and hospital investment funding. We show that TFP growth in German hospital care reflects quality improvements rather than increases in output volumes. Second-stage regression results indicate that reducing the length of stay is generally a proper way to foster TFP growth. The effects of other hospital policies depend on the reimbursement scheme: Under activity-based (German Diagnosis-related Group) hospital funding, scope-related policies (privatization and specialization) come with TFP growth. Under fixed daily rate funding, scale matters to TFP (hospital size and occupancy rates). Differences in capitalization in East and West Germany allow to show that deepening capital may enhance TFP growth if capital is scarce. We also show that there is less scope for hospital policies after large-scale restructurings of the hospital sector. Copyright © 2016 John Wiley & Sons, Ltd.

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.

Assessing physician productivity following Norwegian hospital reform: A panel and data envelopment analysis

BACKGROUND

Although health care reforms may improve efficiency at the macro level, less is known regarding their effects on the utilization of health care personnel. Following the 2002 Norwegian hospital reform, we studied the productivity of the physician workforce and the effect of personnel mix on this measure in all nineteen Norwegian hospitals from 2001 to 2013.

METHODS

We used panel analysis and non-parametric data envelopment analysis (DEA) to study physician productivity defined as patient treatments per full-time equivalent (FTE) physician. Resource variables were FTE and salary costs of physicians, nurses, secretaries, and other personnel. Patient metrics were number of patients treated by hospitalization, daycare, and outpatient treatments, as well as corresponding diagnosis-related group (DRG) scores accounting for differences in patient mix. Research publications and the fraction of residents/FTE physicians were used as proxies for research and physician training.

RESULTS

The number of patients treated increased by 47% and the DRG scores by 35%, but there were no significant increases in any of the activity measures per FTE physician. Total DRG per FTE physician declined by 6% (p < 0.05). In the panel analysis, more nurses and secretaries per FTE physician correlated positively with physician productivity, whereas physician salary was neutral. In 2013, there was a 12%-80% difference between the hospitals with the highest and lowest physician productivity in the differing treatment modalities. In the DEA, cost efficiency did not change in the study period, but allocative efficiency decreased significantly. Bootstrapped estimates indicated that the use of physicians was too high and the use of auxiliary nurses and secretaries was too low.

CONCLUSIONS

Our measures of physician productivity declined from 2001 to 2013. More support staff was a significant variable for predicting physician productivity. Personnel mix developments in the study period were unfavorable with respect to physician productivity.

[Analysis of the technical efficiency of hospitals in the Spanish National Health Service]

OBJECTIVE

To analyse the technical efficiency and productivity of general hospitals in the Spanish National Health Service (NHS) (2010-2012) and identify explanatory hospital and regional variables.

METHODS

230 NHS hospitals were analysed by data envelopment analysis for overall, technical and scale efficiency, and Malmquist index. The robustness of the analysis is contrasted with alternative input-output models. A fixed effects multilevel cross-sectional linear model was used to analyse the explanatory efficiency variables.

RESULTS

The average rate of overall technical efficiency (OTE) was 0.736 in 2012; there was considerable variability by region. Malmquist index (2010-2012) is 1.013. A 23% variability in OTE is attributable to the region in question. Statistically significant exogenous variables (residents per 100 physicians, aging index, average annual income per household, essential public service expenditure and public health expenditure per capita) explain 42% of the OTE variability between hospitals and 64% between regions. The number of residents showed a statistically significant relationship. As regards regions, there is a statistically significant direct linear association between OTE and annual income per capita and essential public service expenditure, and an indirect association with the aging index and annual public health expenditure per capita.

DISCUSSION

The significant room for improvement in the efficiency of hospitals is conditioned by region-specific characteristics, specifically aging, wealth and the public expenditure policies of each one.

Efficiency and productivity measurement of rural township hospitals in China: a bootstrapping data envelopment analysis

OBJECTIVE

Township hospitals (THs) are important components of the three-tier rural healthcare system of China. However, the efficiency and productivity of THs have been questioned since the healthcare reform was implemented in 2009. The objective of this study is to analyse the efficiency and productivity changes in THs before and after the reform process.

SETTING AND PARTICIPANTS

A total of 48 sample THs were selected from the Xiaogan Prefecture in Hubei Province from 2008 to 2014.

OUTCOME MEASURES

First, bootstrapping data envelopment analysis (DEA) was performed to estimate the technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of the sample THs during the period. Second, the bootstrapping Malmquist productivity index was used to calculate the productivity changes over time.

RESULTS

The average TE, PTE and SE of the sample THs over the 7-year period were 0.5147, 0.6373 and 0.7080, respectively. The average TE and PTE increased from 2008 to 2012 but declined considerably after 2012. In general, the sample THs experienced a negative shift in productivity from 2008 to 2014. The negative change was 2.14%, which was attributed to a 23.89% decrease in technological changes (TC). The sample THs experienced a positive productivity shift from 2008 to 2012 but experienced deterioration from 2012 to 2014.

CONCLUSIONS

There was considerable space for TE improvement in the sample THs since the average TE was relatively low. From 2008 to 2014, the sample THs experienced a decrease in productivity, and the adverse alteration in TC should be emphasised. In the context of healthcare reform, the factors that influence TE and productivity of THs are complex. Results suggest that numerous quantitative and qualitative studies are necessary to explore the reasons for the changes in TE and productivity.

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.

Achieving value for money in health: a comparative analysis of OECD countries and regional countries

OBJECTIVE

To measure efficiency gains in health sector over the years 1995 to 2013 in OECD, EU, non-member European countries.

METHODS

An output-oriented DEA model with variable return to scale, and residuals estimated by regression equations were used to estimate efficiencies of health systems. Slacks for health care outputs and inputs were calculated by using DEA multistage method of estimating country efficiency scores.

RESULTS

Better health outcomes of countries were related with higher efficiency. Japan, France, or Sweden were found to be peer-efficient countries when compared to other developed countries like Germany and United States. Increasing life expectancy beyond a certain high level becomes very difficult to achieve. Despite declining marginal productivity of inputs on health outcomes, some developed countries and developing countries were found to have lowered their inefficiencies in the use of health inputs. Although there was no systematic relationship between political system of countries and health system efficiency, the objectives of countries on social and health policy and the way of achieving these objectives might be a factor increasing the efficiency of health systems.

CONCLUSIONS

Economic and political stability might be as important as health expenditure in improving health system goals. A better understanding of the value created by health expenditures, especially in developed countries, will require analysis of specific health interventions that can increase value for money in health. Copyright © 2016 John Wiley & Sons, Ltd.

Factors affecting the technical efficiency of general hospitals in Iran: data envelopment analysis

BACKGROUND

Restrictions on resource accessibility and its optimal application is the main challenge in organizations nowadays. The aim of this research was to study the technical efficiency and its related factors in Tehran general hospitals.

MATERIALS AND METHODS

This descriptive analytical study was conducted retrospectively in 2014. Fifty-four hospitals with private, university, and social security ownerships from the total 110 general hospitals were randomly selected for inclusion into this study on the basis of the share of ownership. Data were collected using a checklist with three sections, including background variables, inputs, and outputs.

RESULTS

Seventeen (31.48%) hospitals had an efficiency score of 1 (highest efficiency score). The highest average efficiency score was in social security hospitals (84.32). Private and university hospitals ranked next with an average of 84.29 and 79.64, respectively. Analytical results showed that there was a significant relationship between hospital ownership, hospital type in terms of duty and specialization, educational field of the chief executive officer, and technical efficiency. There was no significant relationship between education level of hospital manager and technical efficiency.

CONCLUSION AND RECOMMENDATIONS

Most of the studied hospitals were operating at low efficiency. Therefore, policymakers should plan to improve the hospital operations and promote hospitals to an optimal level of efficiency.

Measuring efficiency of governmental hospitals in Palestine using stochastic frontier analysis

Background

The Palestinian government has been under increasing pressure to improve provision of health services while seeking to effectively employ its scare resources. Governmental hospitals remain the leading costly units as they consume about 60 % of governmental health budget. A clearer understanding of the technical efficiency of hospitals is crucial to shape future health policy reforms. In this paper, we used stochastic frontier analysis to measure technical efficiency of governmental hospitals, the first of its kind nationally.

Methods

We estimated maximum likelihood random-effects and time-invariant efficiency model developed by Battese and Coelli, 1988. Number of beds, number of doctors, number of nurses, and number of non-medical staff, were used as the input variables, and sum of number of treated inpatients and outpatients was used as output variable. Our dataset includes balanced panel data of 22 governmental hospitals over a period of 6 years. Cobb–Douglas function, translog function, and multi-output distance function were estimated using STATA 12.

Results

The average technical efficiency of hospitals was approximately 55 %, and ranged from 28 to 91 %. Doctors and nurses appear to be the most important factors in hospital production, as 1 % increase in number of doctors, results in an increase in the production of the hospital of 0.33 and 0.51 %, respectively. If hospitals increase all inputs by 1 %, their production would increase by 0.74 %. Hospitals production process has a decrease return to scale.

Conclusion

Despite continued investment in governmental hospitals, they remained relatively inefficient. Using the existing amount of resources, the amount of delivered outputs can be improved 45 % which provides insight into mismanagement of available resources. To address hospital inefficiency, it is important to increase the numbers of doctors and nurses. The number of non-medical staff should be reduced. Offering the option of early retirement, limit hiring, and transfer to primary health care centers are possible options. It is crucial to maintain a rich clinical skill-mix when implementing such measures. Adopting interventions to improve the quality of management in hospitals will improve efficiency. International benchmarking provides more insights on sources of hospital inefficiency.

Costs and Quality at the Hospital Level in the Nordic Countries

This article develops and analyzes patient register-based measures of quality for the major Nordic countries. Previous studies show that Finnish hospitals have significantly higher average productivity than hospitals in Sweden, Denmark, and Norway and also a substantial variation within each country. This paper examines whether quality differences can form part of the explanation and attempts to uncover quality-cost trade-offs. Data on costs and discharges in each diagnosis-related group for 160 acute hospitals in 2008-2009 were collected. Patient register-based measures of quality such as readmissions, mortality (in hospital or outside), and patient safety indices were developed and case-mix adjusted. Productivity is estimated using bootstrapped data envelopment analysis. Results indicate that case-mix adjustment is important, and there are significant differences in the case-mix adjusted performance measures as well as in productivity both at the national and hospital levels. For most quality indicators, the performance measures reveal room for improvement. There is a weak but statistical significant trade-off between productivity and inpatient readmissions within 30 days but a tendency that hospitals with high 30-day mortality also have higher costs. Hence, no clear cost-quality trade-off pattern was discovered. Patient registers can be used and developed to improve future quality and cost comparisons.

Outcome, Use of Resources and Their Relationship in the Treatment of AMI, Stroke and Hip Fracture at European Hospitals

The aim of the present study was to compare the quality (survival), use of resources and their relationship in the treatment of three major conditions (acute myocardial infarction (AMI), stroke and hip fracture), in hospitals in five European countries (Finland, Hungary, Italy, Norway and Sweden). The comparison of quality and use of resources was based on hospital-level random effects models estimated from patient-level data. After examining quality and use of resources separately, we analysed whether a cost-quality trade-off existed between the hospitals. Our results showed notable differences between hospitals and countries in both survival and use of resources. Some evidence would support increasing the horizontal integration: higher degrees of concentration of regional AMI care were associated with lower use of resources. A positive relation between cost and quality in the care of AMI patients existed in Hungary and Finland. In the care of stroke and hip fracture, we found no evidence of a cost-quality trade-off. Thus, the cost-quality association was inconsistent and prevailed for certain treatments or patient groups, but not in all countries.

Individual and Regional-level Factors Contributing to Variation in Length of Stay After Cerebral Infarction in Six European Countries

Using patient-level data for cerebral infarction cases in 2007, gathered from Finland, Hungary, Italy, the Netherlands, Scotland and Sweden, we studied the variation in risk-adjusted length of stay (LoS) of acute hospital care and 1-year mortality, both within and between countries. In addition, we analysed the variance of LoS and associations of selected regional-level factors with LoS and 1-year mortality after cerebral infarction. The data show that LoS distributions are surprisingly different across countries and that there is significant deviation in the risk-adjusted regional-level LoS in all of the countries studied. We used negative binomial regression to model the individual-level LoS, and random intercept models and ordinary least squares regression for the regional-level analysis of risk-adjusted LoS, variance of LoS, 1-year risk-adjusted mortality and crude mortality for a period of 31-365 days. The observed variations between regions and countries in both LoS and mortality were not fully explained by either patient-level or regional-level factors. The results indicate that there may exist potential for efficiency gains in acute hospital care of cerebral infarction and that healthcare managers could learn from best practices.

Comparing efficiency of health systems across industrialized countries: a panel analysis

Background

Rankings from the World Health Organization (WHO) place the US health care system as one of the least efficient among Organization for Economic Cooperation and Development (OECD) countries. Researchers have questioned this, noting simplistic or inappropriate methodologies, poor measurement choice, and poor control variables. Our objective is to re-visit this question by using newer modeling techniques and a large panel of OECD data.

Methods

We primarily use the OECD Health Data for 25 OECD countries. We compare results from stochastic frontier analysis (SFA) and fixed effects models. We estimate total life expectancy as well as life expectancy at age 60. We explore a combination of control variables reflecting health care resources, health behaviors, and economic and environmental factors.

Results

The US never ranks higher than fifth out of all 36 models, but is also never the very last ranked country though it was close in several models. The SFA estimation approach produces the most consistent lead country, but the remaining countries did not maintain a steady rank.

Discussion

Our study sheds light on the fragility of health system rankings by using a large panel and applying the latest efficiency modeling techniques. The rankings are not robust to different statistical approaches, nor to variable inclusion decisions.

Conclusions

Future international comparisons should employ a range of methodologies to generate a more nuanced portrait of health care system efficiency.

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.

Nonparametric Optimization of Preference in Technical Efficiency in China

Applying nonparametric path-converged approach, the research innovatively provides the measurement of preference in technical efficiency by the ratio of labor elasticity to capital elasticity and further attempts to realize the optimization of preference in technical efficiency by a strategy of 30% abolishment of initial Drug Addition and a strategy with combination of smoothed governmental fiscal expenditure, which sheds fresh light on promoting hospitals’ efficiency in China from perspective of management engineering. With sample data of provincial public hospitals in Zhejiang Province during period of 200901-201306, the research obtains following conclusions. First, benchmark preference in technical efficiency shows production has shifted from physical capital preference to labor skilled preference in technical efficiency. Second, the changing trend of preference in technical efficiency validates initial Drug Addition and governmental fiscal expenditure pushes and restrains the labor skilled preference in technical efficiency respectively. Third, the strategy of 30% abolishment of Drug Addition will strengthen labor skilled preference in technical efficiency with less promotion intensity of initial Drug Addition. The strategy with combination of governmental fiscal expenditure restrains labor skilled preference in technical efficiency. The facts validate great urgency of raising payments for doctors and nurses so as to promoting efficiency effectively.

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.

Factors affecting the technical efficiency of health systems: A case study of Economic Cooperation Organization (ECO) countries (2004-10)

BACKGROUND

Improving efficiency of health sector is of particular importance in all countries. To reach this end, it is paramount to measure the efficiency. On the other hand, there are many factors that affect the efficiency of health systems. This study aimed to measure the Technical Efficiency (TE) of health systems in Economic Cooperation Organization (ECO) countries during 2004-10 and to determine the factors affecting their TE.

METHODS

This was a descriptive-analytical and panel study. The required data were gathered using library and field studies, available statistics and international websites through completing data collection forms. In this study, the TE of health systems in 10 ECO countries was measured using their available data and Data Envelopment Analysis (DEA) through two approaches. The first approach used GDP per capita, education and smoking as its inputs and life expectancy and infant mortality rates as the outputs. The second approach, also, used the health expenditures per capita, the number of physicians per thousand people, and the number of hospital beds per thousand people as its inputs and life expectancy and under-5 mortality rates as the outputs. Then, the factors affecting the TE of health systems were determined using the panel data logit model. Excel 2010, Win4Deap 1.1.2 and Stata 11.0 were used to analyze the collected data.

RESULTS

According to the first approach, the mean TE of health systems was 0.497 and based on the second one it was 0.563. Turkey and Turkmenistan had, respectively, the highest and lowest mean of efficiency. Also, the results of panel data logit model showed that only GDP per capita and health expenditures per capita had significant relationships with the TE of health systems.

CONCLUSION

In order to maximize the TE of health systems, health policy-makers should pay special attention to the proper use of healthcare resources according to the people's needs, the appropriate management of the health system resources, allocating adequate budgets to the health sector, establishing an appropriate referral system to provide better public access to health services according to their income and needs, among many others.