Cost inefficiency in Washington hospitals: a stochastic frontier approach using panel data

Measurement and characteristics of the temporal-spatial evolution of China's healthcare services efficiency

BACKGROUND

Healthcare services efficiency (HSE) is directly related to the healthcare demands of the general public and also plays an essential role in the country's coordinated economic and social development.

METHODS

In this study, the stochastic frontier approach (SFA)-Malmquist model was applied to measure the HSE of 31 Chinese provinces based on panel data from 2010-2020. Then, kernel density estimation, Markov chain, and exploratory spatial data analysis were adopted to study the temporal-spatial dynamic evolution characteristics of the HSE.

RESULTS

The study found that China's HSE showed an average value of approximately 0.841, indicating room for improvement. The HSE varied significantly across regions, presenting an "East > Central > West" distribution layout. The TFP of healthcare services in China grew by 1.6% per year, driven mainly by technological progress of 1.8% per year. The trend of the HSE shifting to a high level in China was significant, but its evolution exhibited stability of maintaining the original state, and it was harder to achieve leapfrog transfer. The temporal-spatial evolution of the HSE was also significantly affected by geospatial factors, with a clear spatial spillover effect and spatial agglomeration characteristics. Provinces with high-level HSE exhibited positive spatial spillover effects, while provinces with low-level HSE had negative spatial spillover effects. Thus, the "club convergence" phenomenon of "high efficiency concentration, low efficiency agglomeration, high levels of radiation, and low levels of suppression" was formed in the spatial distribution.

CONCLUSIONS

The results indicate that countermeasures should be taken to improve the HSE in China. Theoretical support for the improvement of HSE is provided in this paper.

Hospital cost efficiency: an examination of US acute care inpatient hospitals

The use of stochastic frontier models for inference on hospital efficiency is complicated by the inability to fully control for quality differences across hospitals. Additionally, the potential existence of cross-sectional dependence due to the presence of unobserved common factors leads to endogeneity problems that can bias both cost function and efficiency estimates. Using a panel consisting of 1518 hospitals for the years 1996-2013 (T = 18), I adopt techniques for dealing with long, cross-sectionally dependent panel data in order to estimate cost parameters and hospital specific efficiency. In particular, I employ the estimation technique proposed by Bai (Econometrica 77(4):1229-1279, 2009), which assumes that the unobservable heterogenous effects have a factor structure. I find evidence of considerable scale economies and that hospital cost inefficiencies have been increasing during the period of 1996-2013, and that the growth in expenditures is, in part, driven by spending that increases patient satisfaction, but that does not significantly contribute to improved patient health outcomes.

Determinants of transient and persistent hospital efficiency: The case of Italy

In this paper, we extend the 4-random-component closed skew-normal stochastic frontier model by including exogenous determinants of hospital persistent (long-run) and transient (short-run) inefficiency, separated from unobserved heterogeneity. We apply this new model to a dataset composed by 133 Italian hospitals during the period 2008-2013. We show that average total inefficiency is about 23%, higher than previous estimates; hence, a model where the different types of inefficiency and hospital unobserved characteristics are not confounded allows us to get less biased estimates of hospital inefficiency. Moreover, we find that transient efficiency is more important than persistent efficiency, as it accounts for 60% of the total one. Last, we find that ownership (for-profit hospitals are more transiently inefficient and less persistently inefficient than not-for-profit ones, whereas public hospitals are less transiently inefficient than not-for-profit ones), specialization (specialized hospitals are more transiently inefficient than general ones; i.e., there is evidence of scope economies in short-run efficiency), and size (large-sized hospitals are better than medium and small ones in terms of transient inefficiency) are determinants of both types of inefficiency, although we do not find any statistically significant effect of multihospital systems and teaching hospitals.

Measuring Efficiency of Secondary Healthcare Providers in Slovenia

The chief aim of this study was to analyze secondary healthcare providers' efficiency, focusing on the efficiency analysis of Slovene general hospitals. We intended to present a complete picture of technical, allocative, and cost or economic efficiency of general hospitals.

Healthcare managers’ perception of economies of scale

Purpose

The purpose of this paper is to explore how healthcare managers perceive economies of scale and the underlying mechanisms for how scale/size affects performance.

Design/methodology/approach

Data were collected in 20 in-depth interviews with healthcare professionals from 13 healthcare delivery organizations and from a public authority that finances and contracts healthcare services. Data were coded and analysed using content analysis.

Findings

The study concludes that the impact of scale on performance is perceived by healthcare professionals to be different for different types of healthcare services: For surgery, significant scale effects related to spreading of fixed cost, the experience curve, and potential for process improvement. For inpatient care, moderate scale effects related to spreading of fixed costs and costs of doctors on on-call duty. For outpatient care, small or no scale effects.

Research limitations/implications

The small sample of interviewees from a single geographical region and healthcare system limits the applicability of the findings.

Originality/value

The paper provides insights into how healthcare managers experience scale effects and how they consider economies of scale when planning hospital configuration. Also, past studies of economies of scale in hospitals proffer mixed results and the findings in this paper indicate a possible explanation for this inconclusiveness, i.e. differences in service mix between different hospitals.

Efficiency of physician specialist groups

This is the first study to use stochastic frontier analysis to simultaneously estimate the technical, cost and profit efficiency of physician practices for different physician specialist groups. We base our analysis on a unique panel data set of 4964 physician practices in Germany for the years 2008 to 2010. The data contains information on practice costs and revenues, services provided, as well as physician characteristics and practice characteristics. Additionally we consider a wide range additional variables not previously analyzed in this context (e.g. sub-specialization of physician groups and environmental factors such as physician density in the area). We investigate differences in cost, technical and profit efficiency utilizing production-/cost- and profit-functions with a translog functional form. We estimated the stochastic frontier using the comprehensive one-step approach for panel data following Battese and Coelli (Empir Econ 20(2): 325-332, 10). Overall findings indicate that participation in disease management programs and the degree of specialization are associated with significantly higher technical- cost-, and profit-efficiency for most physician specialist groups, e.g. due to the standardization of processes. In addition, our analyses show that group practices perform significantly better than single practices. This may be due to indivisibilities in expensive technical equipment, which can lead to different health care services being provided by different practice types. A more thorough look at specialist groups suggests that it is important to investigate all efficiency types for different physician groups, as results may depend on the type of efficiency analyzed as well as the physician group in question.

Profit efficiency of physician practices: a stochastic frontier approach using panel data

While determinants of efficiency have been the subject of a large number of studies in the inpatient sector, relatively little is known about factors influencing efficiency of physician practices in the outpatient sector. With our study, we provide the first paper to estimate physician practice profit efficiency and its' determinants. We base our analysis on a unique panel data set of 4964 physician practices for the years 2008 to 2010. The data contains information on practice costs and revenues, services provided, as well as physician and practice characteristics. We specify the profit function of the physician practice as a translog functional form. We estimated the stochastic frontier using the comprehensive one-step approach for panel data of Battese and Coelli (1995). For estimation of the profit function, we regressed yearly profit on several inputs, outputs and input/output price relationships, while we controlled for a range of control variables such as patients' case-mix or share of patients covered by statutory health insurance. We find that participation in disease management programs and the degree of physician practice specialization are associated with significantly higher profit efficiency. In addition, our analyses show that group practices perform significantly better than single practices.

A New Approach of Measuring Hospital Performance for Low- and Middle-income Countries

Efficiency of the hospitals affects the price of health services. Health care payments have equity implications. Evidence on hospital performance can support to design the policy; however, the recent literature on hospital efficiency produced conflicting results. Consequently, policy decisions are uncertain. Even the most of evidence were produced by using data from high income countries. Conflicting results were produced particularly due to differences in methods of measuring performance. Recently a management approach has been developed to measure the hospital performance. This approach to measure the hospital performance is very useful from policy perspective to improve health system from cost-effective way in low and middle income countries. Measuring hospital performance through management approach has some basic characteristics such as scoring management practices through double blind survey, measuring hospital outputs using various indicators, estimating the relationship between management practices and outputs of the hospitals. This approach has been successfully applied to developed countries; however, some revisions are required without violating the fundamental principle of this approach to replicate in low- and middle-income countries. The process has been clearly defined and applied to Nepal. As the results of this, the approach produced expected results. The paper contributes to improve the approach to measure hospital performance.

Assessing the relationships between hospital resources and activities: a systematic review

Face the challenge of minimizing their resource utilization without reducing the quality of healthcare. Achieving this aim requires precise analysis and optimization of various inputs and outputs. This paper presents a systematic review of the relationships between hospital resources (considered productivity inputs) and financial and activity outcomes (considered productivity outputs). Several electronic bibliographic databases and the Internet were searched for articles published between January 1990 and December 2013 that examined the relationships between hospital resources and financial and activity outcomes. We assessed the quality of the study design, the nature of the sample, input and output indicators, and the statistical methods used for each selected study. Thirty-eight original papers were selected. Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) were the most statistical methods used. Based on our analysis, we retained 18 input and 19 output indicators that could constitute the basis for hospital productivity benchmarking. Selecting a small set of shared economic and activity indicators is relevant for assessing the productivity of a hospital, measuring trends and performing national or international benchmarking. Such indicators should be combined with quality measures for a comprehensive evaluation approach.

Cost and technical efficiency of physician practices: a stochastic frontier approach using panel data

This is the first study to use stochastic frontier analysis to estimate both the technical and cost efficiency of physician practices. The analysis is based on panel data from 3,126 physician practices for the years 2006 through 2008. We specified the technical and cost frontiers as translog function, using the one-step approach of Battese and Coelli to detect factors that influence the efficiency of general practitioners and specialists. Variables that were not analyzed previously in this context (e.g., the degree of practice specialization) and a range of control variables such as a patients' case-mix were included in the estimation. Our results suggest that it is important to investigate both technical and cost efficiency, as results may depend on the type of efficiency analyzed. For example, the technical efficiency of group practices was significantly higher than that of solo practices, whereas the results for cost efficiency differed. This may be due to indivisibilities in expensive technical equipment, which can lead to different types of health care services being provided by different practice types (i.e., with group practices using more expensive inputs, leading to higher costs per case despite these practices being technically more efficient). Other practice characteristics such as participation in disease management programs show the same impact throughout both cost and technical efficiency: participation in disease management programs led to an increase in both, technical and cost efficiency, and may also have had positive effects on the quality of care. Future studies should take quality-related issues into account.

Measuring the performance of Critical Access Hospitals in Missouri using data envelopment analysis

PURPOSE

Rural hospitals are critical for access to health care, and for their contributions to local economies. However, many rural hospitals, especially critical access hospitals (CAHs) need to strive for more efficiency for continued viability. Routinely evaluating their performance, and providing feedback to management and policy makers, is therefore important.

METHOD

Three measures of relative efficiency are estimated for CAHs in Missouri using an Input-oriented Data Envelopment Analysis with a variable returns to scale assumption and compared with the efficiency of other rural hospitals in Missouri using Banker's F-test. Using 30-day readmission rate as a measure of quality, CAHs are evaluated against efficiency-quality dimensions.

FINDINGS

CAHs in Missouri had a slight decline in average technical efficiency, but they had a slight gain in average cost efficiency in 2009 compared to 2006. More than half of the CAHs were neither economically nor technically efficient in both years. The relative efficiency of other rural hospitals was statistically higher than that of CAHs in Missouri.

CONCLUSIONS

This study validates the finding of relative inefficiency of CAHs compared to other hospitals paid under the Prospective Payment System at a state level (Missouri). However, with considerable variation in socioeconomic as well as health care access indicators across states, a relative efficiency frontier may not be the only relevant indicator of value for the evaluation of the performance of CAHs. Access to health care and the impact on the local economy provided by these CAHs to the community are also critical indicators for more comprehensive performance evaluation.

Measuring Shared Inefficiency Between Hospital Cost Centers

In this article, a combination of data envelopment analysis, spreadsheet modeling and regression techniques is applied to a panel of nonprofit Washington State hospitals in an effort to determine whether (and if so, to what extent) inefficiency in one hospital cost center is shared with inefficiency in other cost centers. The findings suggest that a significant amount of inefficiency is shared across hospital cost centers. The authors further determine that certain cost centers contribute more to the overall performance of a given hospital than others. As such, managerial decisions and government policies designed to enhance hospital efficiency should be implemented differently, depending on the characteristics of the hospital in question.

What have we learned from the application of stochastic frontier analysis to U.S. hospitals?

This article focuses on the lessons learned from stochastic frontier analysis studies of U.S. hospitals, of which at least 27 have been published. A brief discussion of frontier techniques is provided, but a technical review of the literature is not included because overviews of estimation issues have been published recently. The primary focus is on the correlates of hospital inefficiency. In addition to examining the association of market pressures and hospital inefficiency, the authors also examined the relationship between inefficiency and hospital behavior (e.g., hospital exits) and inefficiency and other measures of hospital performance (e.g., outcome measures of quality). The authors found that consensus is emerging on the relationship of some factors to hospital efficiency; however, further research is needed to better understand others. The application of stochastic frontier analysis to specific policy issues is in its infancy; however, the methodology holds promise for being useful in certain contexts.

Productive innovations in hospitals: an empirical research on the relation between technology and productivity in the Dutch hospital industry

This paper studies the relationship between technology and productivity in Dutch hospitals. In most studies technical change is measured by a proxy, namely a time trend. In practice however, innovations slowly spread over all hospitals and so different hospitals are operating under different technologies at the same point in time. In this study we explicitly inventory specific and well-known innovations in the Dutch hospital industry in the past ten years. These innovations are aggregated into a limited number of homogenous innovation clusters, which are measured by a set of technology index numbers. The index numbers are included in the cost function specification and estimation. The results indicate that technical change is non-neutral and output- biased and that some technologies affect cost in beneficial ways.

Do hospitals practice cream skimming?

‘Cream skimming’ refers to choosing patients for some characteristic(s) other than their need for care, which enhances the profitability or reputation of the provider. Under capitation or other fixed payment schemes, this often means choosing less ill patients. We present a new methodology to measure cream skimming by hospitals. Our approach also provides a measure of a hospital's gain in productive efficiency by caring for patients with lower illness severity. Using a panel of Washington state hospitals, we find evidence that hospitals do practice cream skimming. However, we find little evidence to suggest that cream skimming varies by hospital size, profit status or time.

Measuring hospital inefficiency: the effects of controlling for quality and patient burden of illness

OBJECTIVE

To assess the impact of employing a variety of controls for hospital quality and patient burden of illness on the mean estimated inefficiency and relative ranking of hospitals generated by stochastic frontier analysis (SFA).

STUDY SETTING

This study included urban U.S. hospitals in 20 states operating in 2001. DATA DESIGN/DATA COLLECTION: We took hospital data for 1,290 hospitals from the American Hospital Association Annual Survey and the Medicare Cost Reports. We employed a variety of controls for hospital quality and patient burden of illness. Among the variables we used were a subset of the quality indicators generated from the application of the Patient Safety Indicator and Inpatient Quality Indicator modules of the Agency for Healthcare Research and Quality, Quality Indicator software to the Healthcare Cost and Utilization Project (HCUP), State Inpatient Databases. Measures of a component of patient burden of illness came from the application of the Comorbidity Software to HCUP data.

DATA ANALYSIS

We used SFA to estimate hospital cost-inefficiency. We tested key assumptions of the SFA model with likelihood ratio tests.

PRINCIPAL FINDINGS

The measures produced by the Comorbidity Software appear to account for variations in patient burden of illness that had previously been masquerading as inefficiency. Outcome measures of quality can provide useful insight into a hospital's operations but may have little impact on estimated inefficiency once controls for structural quality and patient burden of illness have been employed.

CONCLUSIONS

Choices about controlling for quality and patient burden of illness can have a nontrivial impact on mean estimated hospital inefficiency and the relative ranking of hospitals generated by SFA.

The Economics of Specialty Hospitals

Specialty hospitals, particularly those specializing in surgery and owned by physicians, have generated a relatively high degree of policy attention over the past several years. The main focus of policy debates has been in two areas: the extent to which specialty hospitals might compete unfairly with incumbent general hospitals and the extent to which physician ownership might be associated with higher usage. Largely absent from the debates, however, has been a discussion of the basic economic model of specialty hospitals. This article reviews existing literature, reports, and findings from site visits to explore the economic rationale for specialty hospitals. The discussion focuses on six factors associated with specialization: consumer demand, procedural operating margins, clinical efficiencies, procedural economies of scale, economies (and diseconomies) of scope, and competencies and learning. A better understanding of the economics of specialization will help policy makers evaluate the full spectrum of advantages and disadvantages of specialty hospitals.

Stochastic frontier analysis of hospital inefficiency: a review of empirical issues and an assessment of robustness

Twenty stochastic frontier analysis (SFA) studies of hospital inefficiency in the United States were analyzed. Results from best-practice methods were compared against previously used methods in hospital studies to ascertain the robustness of SFA in estimating cost inefficiency. To compare past studies and analyze new data, SFA methods were varied by (a) the assumptions of the structure of costs and distribution of the error term, (b) inclusion of quality and product descriptor measures, and (c) use of simultaneous and two-stage estimation techniques. SFA results were relatively insensitive to several model variations.

Advantages and Disadvantages of Single-Versus Multiple-Occupancy Rooms in Acute Care Environments

Private patient rooms have become the industry standard in the United States based on the assumption that they reduce the rate of hospital-acquired infections, facilitate patient care and management, and afford greater therapeutic benefits for patients. The objective of this article is to reviewand analyze the existing literature to identify the empirical evidence related to the advantages and disadvantages of single versus multiple-occupancy patient rooms in hospitals. Three substantive areas were identified for synthesis of the review: (a) first and operating cost of hospitals, (b) infection control, and (c) health care facility management and hospital design and therapeutic impacts. The analysis reveals that private patient rooms reduce the risk of hospital-acquired infections, allow for greater flexibility in operation and management, and have positive therapeutic impacts on patients. This review highlights the need to consider room occupancy issues along with other patient care issues and environmental and management policies.

The cost efficiency and clinical quality of institutional long-term care for the elderly

This study applied the stochastic frontier cost function with inefficiency effects to estimate the association between quality of care and cost efficiency in institutional long-term care wards for the elderly in Finland. We used several clinical quality indicators for indicating adverse care processes and outcomes, based on the Resident Assessment Instrument (RAI)/Minimum Data Set (MDS). Average cost inefficiency among the wards was 22%. We found an association between the clinical quality indicators and cost inefficiency. Higher prevalence of pressure ulcers was associated with higher costs, whereas the higher prevalence of use of depressants and hypnotics increased inefficiency.

Scope and scale inefficiencies in physician practices

Using a national data set, this paper looks at the efficiency of physician practices, focusing on scopes of service by comparing single specialty groups and multispecialty groups. An analysis of efficiency using DEA indicates that there are scope inefficiencies from combining different types of providers into a single practice. Most of the inefficiency is due to technical rather than allocative reasons. In addition, we find that larger practices are able to capture efficiencies of scope, but incur inefficiencies of scale.

The decomposition of cost efficiency: an empirical application of the shadow cost function model to Dutch general hospitals

This paper investigates the performance of the Dutch general hospital industry by a parametric method. In general, the parametric approaches find more difficulties in distinguishing between technical and allocative efficiencies than DEA. Only recently a class of models is developed based on shadow prices which have possibilities to distinguish between technical and allocative efficiency. However, these models cause some serious computational problems. This paper recommends an approach to overcome these problems by using an iterative two-stage estimation procedure. The estimation is conducted on a panel data set of Dutch general hospitals. Estimation shows that this method is effective. The parameter estimates are plausible, reliable and satisfy all theoretical requirements. In particular we find some reliable estimates for the individual hospitals' shadow prices. According to these shadow prices hospitals should reallocate their resources in favor of material supplies at the cost of other personnel and nursing personnel. The mean technical efficiency is about 86%, whereas the allocative efficiency is about 92%. The outcomes also show that technical progress is very small. Economies of scale are present only for small hospitals.

Non-parametric and parametric applications measuring efficiency in health care

This paper reviews 188 published papers on frontier efficiency measurement. The techniques used are mainly based on non-parametric data envelopment analysis, but there is increasing use of parametric techniques, such as stochastic frontier analysis. Applications both to hospitals and wider health care areas are reviewed and summarised, and some meta-type analysis undertaken. Results appear to confirm earlier findings that public provision demonstrates less variability than private. The paper is meant as a resource in itself, but also points to the future in terms of possible directions for research in efficiency measurement in health care and health.